diff --git a/.pre-commit-config.yaml b/.pre-commit-config.yaml
index 515439b2b9..9f8b6d9cea 100644
--- a/.pre-commit-config.yaml
+++ b/.pre-commit-config.yaml
@@ -37,3 +37,4 @@ repos:
   rev: v1.19.1
   hooks:
     - id: mypy
+      exclude: ^libensemble/utils/(launcher|loc_stack|runners|pydantic|output_directory)\.py$|^libensemble/tests/regression_tests/support\.py$|^libensemble/tests/functionality_tests/
diff --git a/docs/data_structures/alloc_specs.rst b/docs/data_structures/alloc_specs.rst
index 074c6a1528..159b9eacaf 100644
--- a/docs/data_structures/alloc_specs.rst
+++ b/docs/data_structures/alloc_specs.rst
@@ -19,7 +19,7 @@ Can be constructed and passed to libEnsemble as a Python class or a dictionary.
   * libEnsemble uses the following defaults if the user doesn't provide their own ``alloc_specs``:
 
   ..  literalinclude:: ../../libensemble/specs.py
-      :start-at: alloc_f: Callable = give_sim_work_first
+      :start-at: alloc_f: Callable = start_only_persistent
       :end-before: end_alloc_tag
       :caption: Default settings for alloc_specs
 
diff --git a/docs/examples/alloc_funcs.rst b/docs/examples/alloc_funcs.rst
index f54f4bf3c4..3734d7cb0d 100644
--- a/docs/examples/alloc_funcs.rst
+++ b/docs/examples/alloc_funcs.rst
@@ -10,14 +10,31 @@ Many users use these unmodified.
 .. IMPORTANT::
   See the API for allocation functions :ref:`here<api_alloc_f>`.
 
+  **The default allocation function changed in libEnsemble v2.0 from `give_sim_work_first` to `start_only_persistent `.**
+
 .. note::
-   The default allocation function (for non-persistent generators) is :ref:`give_sim_work_first<gswf_label>`.
 
-   The most commonly used (for persistent generators) is :ref:`start_only_persistent<start_only_persistent_label>`.
+   The default allocation function for persistent generators is :ref:`start_only_persistent<start_only_persistent_label>`.
+
+   The most commonly used allocation function for non-persistent generators is :ref:`give_sim_work_first<gswf_label>`.
 
 .. role:: underline
     :class: underline
 
+.. _start_only_persistent_label:
+
+start_only_persistent
+---------------------
+.. automodule:: start_only_persistent
+  :members:
+  :undoc-members:
+
+.. dropdown:: :underline:`start_only_persistent.py`
+
+   .. literalinclude:: ../../libensemble/alloc_funcs/start_only_persistent.py
+      :language: python
+      :linenos:
+
 .. _gswf_label:
 
 give_sim_work_first
@@ -44,20 +61,6 @@ fast_alloc
       :language: python
       :linenos:
 
-.. _start_only_persistent_label:
-
-start_only_persistent
----------------------
-.. automodule:: start_only_persistent
-  :members:
-  :undoc-members:
-
-.. dropdown:: :underline:`start_only_persistent.py`
-
-   .. literalinclude:: ../../libensemble/alloc_funcs/start_only_persistent.py
-      :language: python
-      :linenos:
-
 start_persistent_local_opt_gens
 -------------------------------
 .. automodule:: start_persistent_local_opt_gens
diff --git a/docs/function_guides/allocator.rst b/docs/function_guides/allocator.rst
index a65c404ab9..0620105825 100644
--- a/docs/function_guides/allocator.rst
+++ b/docs/function_guides/allocator.rst
@@ -128,8 +128,8 @@ The remaining values above are useful for efficient filtering of H values
 
 Descriptions of included allocation functions can be found :doc:`here<../examples/alloc_funcs>`.
 The default allocation function is
-``give_sim_work_first``. During its worker ID loop, it checks if there's unallocated
+``start_only_persistent``. During its worker ID loop, it checks if there's unallocated
 work and assigns simulations for that work. Otherwise, it initializes
 generators for up to ``"num_active_gens"`` instances. Other settings like
 ``batch_mode`` are also supported. See
-:ref:`here<gswf_label>` for more information about ``give_sim_work_first``.
+:ref:`here<start_only_persistent_label>` for more information.
diff --git a/docs/tutorials/calib_cancel_tutorial.rst b/docs/tutorials/calib_cancel_tutorial.rst
index 1c0fcff3c8..c008100d73 100644
--- a/docs/tutorials/calib_cancel_tutorial.rst
+++ b/docs/tutorials/calib_cancel_tutorial.rst
@@ -151,11 +151,9 @@ The allocation function used in this example is the *only_persistent_gens* funct
 
     alloc_specs = {
         "alloc_f": alloc_f,
-        "user": {
-            "init_sample_size": init_sample_size,
-            "async_return": True,
-            "active_recv_gen": True,
-        },
+        "initial_batch_size": init_sample_size,
+        "async_return": True,
+        "active_recv_gen": True,
     }
 
 **async_return** tells the allocation function to return results to the generator as soon
diff --git a/libensemble/alloc_funcs/fast_alloc.py b/libensemble/alloc_funcs/fast_alloc.py
index bb009740c8..e2027da1c0 100644
--- a/libensemble/alloc_funcs/fast_alloc.py
+++ b/libensemble/alloc_funcs/fast_alloc.py
@@ -7,7 +7,7 @@ def give_sim_work_first(W, H, sim_specs, gen_specs, alloc_specs, persis_info, li
     to evaluate in the simulation function. The fields in ``sim_specs["in"]``
     are given. If all entries in `H` have been given a be evaluated, a worker
     is told to call the generator function, provided this wouldn't result in
-    more than ``alloc_specs["user"]["num_active_gen"]`` active generators.
+    more than ``gen_specs["num_active_gens"]`` or ``alloc_specs["user"]["num_active_gens"]`` active generators.
 
     This fast_alloc variation of give_sim_work_first is useful for cases that
     simply iterate through H, issuing evaluations in order and, in particular,
@@ -23,7 +23,8 @@ def give_sim_work_first(W, H, sim_specs, gen_specs, alloc_specs, persis_info, li
     if libE_info["sim_max_given"] or not libE_info["any_idle_workers"]:
         return {}, persis_info
 
-    user = alloc_specs.get("user", {})
+    user = {**gen_specs, **alloc_specs.get("user", {})}
+
     manage_resources = libE_info["use_resource_sets"]
 
     support = AllocSupport(W, manage_resources, persis_info, libE_info)
diff --git a/libensemble/alloc_funcs/fast_alloc_and_pausing.py b/libensemble/alloc_funcs/fast_alloc_and_pausing.py
index f26b5c0780..fd162a6623 100644
--- a/libensemble/alloc_funcs/fast_alloc_and_pausing.py
+++ b/libensemble/alloc_funcs/fast_alloc_and_pausing.py
@@ -28,13 +28,16 @@ def give_sim_work_first(W, H, sim_specs, gen_specs, alloc_specs, persis_info, li
     if libE_info["sim_max_given"] or not libE_info["any_idle_workers"]:
         return {}, persis_info
 
+    user = {**gen_specs, **alloc_specs.get("user", {})}
     manage_resources = libE_info["use_resource_sets"]
     support = AllocSupport(W, manage_resources, persis_info, libE_info)
     Work = {}
     gen_count = support.count_gens()
 
     if gen_specs["user"].get("single_component_at_a_time"):
-        assert alloc_specs["user"]["batch_mode"], "Must be in batch mode when using 'single_component_at_a_time'"
+        assert alloc_specs["user"].get("batch_mode", False) or gen_specs.get(
+            "batch_mode", False
+        ), "Must be in batch mode when using 'single_component_at_a_time'"
     if len(H) != persis_info["H_len"]:
         # Something new is in the history.
         persis_info["need_to_give"].update(H["sim_id"][persis_info["H_len"] :].tolist())
@@ -119,13 +122,13 @@ def give_sim_work_first(W, H, sim_specs, gen_specs, alloc_specs, persis_info, li
             break
 
     while len(idle_gen_workers):
-        if gen_count < alloc_specs["user"].get("num_active_gens", gen_count + 1):
+        if gen_count < user.get("num_active_gens", gen_count + 1):
             lw = persis_info["last_worker"]
 
             last_size = persis_info.get("last_size")
             if len(H):
                 # Don't give gen instances in batch mode if points are unfinished
-                if alloc_specs["user"].get("batch_mode") and not all(
+                if (alloc_specs["user"].get("batch_mode") or gen_specs.get("batch_mode")) and not all(
                     np.logical_or(H["sim_ended"][last_size:], H["paused"][last_size:])
                 ):
                     break
@@ -142,7 +145,7 @@ def give_sim_work_first(W, H, sim_specs, gen_specs, alloc_specs, persis_info, li
             persis_info["last_worker"] = i
             persis_info["last_size"] = len(H)
 
-        elif gen_count >= alloc_specs["user"].get("num_active_gens", gen_count + 1):
+        elif gen_count >= user.get("num_active_gens", gen_count + 1):
             idle_gen_workers = []
 
     return Work, persis_info
diff --git a/libensemble/alloc_funcs/give_sim_work_first.py b/libensemble/alloc_funcs/give_sim_work_first.py
index 7ac4d75e5e..11ccf211f0 100644
--- a/libensemble/alloc_funcs/give_sim_work_first.py
+++ b/libensemble/alloc_funcs/give_sim_work_first.py
@@ -14,18 +14,18 @@ def give_sim_work_first(
     alloc_specs: dict,
     persis_info: dict,
     libE_info: dict,
-) -> tuple[dict]:
+) -> tuple[dict, dict]:
     """
     Decide what should be given to workers. This allocation function gives any
     available simulation work first, and only when all simulations are
-    completed or running does it start (at most ``alloc_specs["user"]["num_active_gens"]``)
+    completed or running does it start (at most ``gen_specs["num_active_gens"]`` or ``alloc_specs["user"]["num_active_gens"]``)
     generator instances.
 
-    Allows for a ``alloc_specs["user"]["batch_mode"]`` where no generation
+    Allows for a ``gen_specs["batch_mode"]`` or ``alloc_specs["user"]["batch_mode"]`` where no generation
     work is given out unless all entries in ``H`` are returned.
 
     Can give points in highest priority, if ``"priority"`` is a field in ``H``.
-    If ``alloc_specs["user"]["give_all_with_same_priority"]`` is set to True, then
+    If ``gen_specs["give_all_with_same_priority"]`` or ``alloc_specs["user"]["give_all_with_same_priority"]`` is set to True, then
     all points with the same priority value are given as a batch to the sim.
 
     Workers performing sims will be assigned resources given in H["resource_sets"]
@@ -40,7 +40,7 @@ def give_sim_work_first(
         `test_uniform_sampling.py <https://github.com/Libensemble/libensemble/blob/develop/libensemble/tests/functionality_tests/test_uniform_sampling.py>`_ # noqa
     """
 
-    user = alloc_specs.get("user", {})
+    user = {**gen_specs, **alloc_specs.get("user", {})}
 
     if "cancel_sims_time" in user:
         # Cancel simulations that are taking too long
diff --git a/libensemble/alloc_funcs/persistent_aposmm_alloc.py b/libensemble/alloc_funcs/persistent_aposmm_alloc.py
index 3b87d5b5b9..fe3814704c 100644
--- a/libensemble/alloc_funcs/persistent_aposmm_alloc.py
+++ b/libensemble/alloc_funcs/persistent_aposmm_alloc.py
@@ -21,7 +21,8 @@ def persistent_aposmm_alloc(W, H, sim_specs, gen_specs, alloc_specs, persis_info
     if libE_info["sim_max_given"] or not libE_info["any_idle_workers"]:
         return {}, persis_info
 
-    init_sample_size = gen_specs["user"]["initial_sample_size"]
+    user = {**gen_specs, **alloc_specs.get("user", {})}
+    init_sample_size = user["initial_batch_size"]
     manage_resources = libE_info["use_resource_sets"]
     support = AllocSupport(W, manage_resources, persis_info, libE_info)
     gen_count = support.count_persis_gens()
diff --git a/libensemble/alloc_funcs/start_only_persistent.py b/libensemble/alloc_funcs/start_only_persistent.py
index 7781ed3b5f..801dd11802 100644
--- a/libensemble/alloc_funcs/start_only_persistent.py
+++ b/libensemble/alloc_funcs/start_only_persistent.py
@@ -7,12 +7,12 @@
 def only_persistent_gens(W, H, sim_specs, gen_specs, alloc_specs, persis_info, libE_info):
     """
     This allocation function will give simulation work if possible, but
-    otherwise start up to ``alloc_specs["user"]["num_active_gens"]``
+    otherwise start up to ``gen_specs["num_active_gens"]`` or ``alloc_specs["user"]["num_active_gens"]``
     persistent generators (defaulting to one).
 
     By default, evaluation results are given back to the generator once
     all generated points have been returned from the simulation evaluation.
-    If ``alloc_specs["user"]["async_return"]`` is set to True, then any
+    If ``gen_specs["async_return"]`` or ``alloc_specs["user"]["async_return"]`` is set to True, then any
     returned points are given back to the generator.
 
     If any workers are marked as zero_resource_workers, then these will only
@@ -56,11 +56,12 @@ def only_persistent_gens(W, H, sim_specs, gen_specs, alloc_specs, persis_info, l
         return {}, persis_info
 
     # Initialize alloc_specs["user"] as user.
-    user = alloc_specs.get("user", {})
+    user = {**gen_specs, **alloc_specs.get("user", {})}
+
     manage_resources = libE_info["use_resource_sets"]
 
     active_recv_gen = user.get("active_recv_gen", False)  # Persistent gen can handle irregular communications
-    init_sample_size = user.get("init_sample_size", 0)  # Always batch return until this many evals complete
+    initial_batch_size = user.get("initial_batch_size", 0)  # Always batch return until this many evals complete
     batch_give = user.get("give_all_with_same_priority", False)
 
     support = AllocSupport(W, manage_resources, persis_info, libE_info)
@@ -68,7 +69,7 @@ def only_persistent_gens(W, H, sim_specs, gen_specs, alloc_specs, persis_info, l
     Work = {}
 
     # Asynchronous return to generator
-    async_return = user.get("async_return", False) and sum(H["sim_ended"]) >= init_sample_size
+    async_return = user.get("async_return", False) and sum(H["sim_ended"]) >= initial_batch_size
 
     if gen_count < persis_info.get("num_gens_started", 0):
         # When a persistent worker is done, trigger a shutdown (returning exit condition of 1)
diff --git a/libensemble/gen_funcs/persistent_sampling.py b/libensemble/gen_funcs/persistent_sampling.py
index 375d7f4387..6f28ec2caa 100644
--- a/libensemble/gen_funcs/persistent_sampling.py
+++ b/libensemble/gen_funcs/persistent_sampling.py
@@ -16,9 +16,9 @@
 ]
 
 
-def _get_user_params(user_specs):
+def _get_user_params(user_specs, gen_specs):
     """Extract user params"""
-    b = user_specs["initial_batch_size"]
+    b = gen_specs.get("initial_batch_size") or user_specs.get("initial_batch_size") or gen_specs.get("init_sample_size")
     ub = user_specs["ub"]
     lb = user_specs["lb"]
     n = len(lb)  # dimension
@@ -44,7 +44,7 @@ def persistent_uniform(_, persis_info, gen_specs, libE_info):
         `test_persistent_uniform_sampling_async.py <https://github.com/Libensemble/libensemble/blob/develop/libensemble/tests/functionality_tests/test_persistent_uniform_sampling_async.py>`_
     """  # noqa
 
-    b, n, lb, ub = _get_user_params(gen_specs["user"])
+    b, n, lb, ub = _get_user_params(gen_specs.get("user", {}), gen_specs)
     ps = PersistentSupport(libE_info, EVAL_GEN_TAG)
 
     # Send batches until manager sends stop tag
@@ -73,7 +73,7 @@ def persistent_uniform_final_update(_, persis_info, gen_specs, libE_info):
         `test_persistent_uniform_sampling_running_mean.py <https://github.com/Libensemble/libensemble/blob/develop/libensemble/tests/functionality_tests/test_persistent_uniform_sampling_running_mean.py>`_
     """  # noqa
 
-    b, n, lb, ub = _get_user_params(gen_specs["user"])
+    b, n, lb, ub = _get_user_params(gen_specs.get("user", {}), gen_specs)
     ps = PersistentSupport(libE_info, EVAL_GEN_TAG)
 
     def generate_corners(x, y):
@@ -145,7 +145,7 @@ def persistent_request_shutdown(_, persis_info, gen_specs, libE_info):
     .. seealso::
         `test_persistent_uniform_gen_decides_stop.py <https://github.com/Libensemble/libensemble/blob/develop/libensemble/tests/functionality_tests/test_persistent_uniform_gen_decides_stop.py>`_
     """  # noqa
-    b, n, lb, ub = _get_user_params(gen_specs["user"])
+    b, n, lb, ub = _get_user_params(gen_specs.get("user", {}), gen_specs)
     shutdown_limit = gen_specs["user"]["shutdown_limit"]
     f_count = 0
     ps = PersistentSupport(libE_info, EVAL_GEN_TAG)
@@ -173,7 +173,7 @@ def uniform_nonblocking(_, persis_info, gen_specs, libE_info):
     .. seealso::
         `test_persistent_uniform_sampling.py <https://github.com/Libensemble/libensemble/blob/develop/libensemble/tests/functionality_tests/test_persistent_uniform_sampling.py>`_
     """  # noqa
-    b, n, lb, ub = _get_user_params(gen_specs["user"])
+    b, n, lb, ub = _get_user_params(gen_specs.get("user", {}), gen_specs)
     ps = PersistentSupport(libE_info, EVAL_GEN_TAG)
 
     # Send batches until manager sends stop tag
@@ -223,7 +223,11 @@ def batched_history_matching(_, persis_info, gen_specs, libE_info):
     lb = gen_specs["user"]["lb"]
 
     n = len(lb)
-    b = gen_specs["user"]["initial_batch_size"]
+    b = (
+        gen_specs.get("initial_batch_size")
+        or gen_specs["user"].get("initial_batch_size")
+        or gen_specs.get("init_sample_size")
+    )
     q = gen_specs["user"]["num_best_vals"]
     ps = PersistentSupport(libE_info, EVAL_GEN_TAG)
 
@@ -250,7 +254,11 @@ def persistent_uniform_with_cancellations(_, persis_info, gen_specs, libE_info):
     ub = gen_specs["user"]["ub"]
     lb = gen_specs["user"]["lb"]
     n = len(lb)
-    b = gen_specs["user"]["initial_batch_size"]
+    b = (
+        gen_specs.get("initial_batch_size")
+        or gen_specs["user"].get("initial_batch_size")
+        or gen_specs.get("init_sample_size")
+    )
 
     # Start cancelling points from half initial batch onward
     cancel_from = b // 2  # Should get at least this many points back
diff --git a/libensemble/gen_funcs/persistent_sampling_var_resources.py b/libensemble/gen_funcs/persistent_sampling_var_resources.py
index 394ef75815..90e14bc4b8 100644
--- a/libensemble/gen_funcs/persistent_sampling_var_resources.py
+++ b/libensemble/gen_funcs/persistent_sampling_var_resources.py
@@ -25,11 +25,11 @@
 ]
 
 
-def _get_user_params(user_specs):
+def _get_user_params(gen_specs):
     """Extract user params"""
-    b = user_specs["initial_batch_size"]
-    ub = user_specs["ub"]
-    lb = user_specs["lb"]
+    b = gen_specs["initial_batch_size"]
+    ub = gen_specs["user"]["ub"]
+    lb = gen_specs["user"]["lb"]
     n = len(lb)  # dimension
     return b, n, lb, ub
 
@@ -43,7 +43,7 @@ def uniform_sample(_, persis_info, gen_specs, libE_info):
         `test_uniform_sampling_with_variable_resources.py <https://github.com/Libensemble/libensemble/blob/develop/libensemble/tests/functionality_tests/test_uniform_sampling_with_variable_resources.py>`_
     """  # noqa
 
-    b, n, lb, ub = _get_user_params(gen_specs["user"])
+    b, n, lb, ub = _get_user_params(gen_specs)
     rng = persis_info["rand_stream"]
     ps = PersistentSupport(libE_info, EVAL_GEN_TAG)
     tag = None
@@ -76,7 +76,7 @@ def uniform_sample_with_var_gpus(_, persis_info, gen_specs, libE_info):
         `test_GPU_variable_resources.py <https://github.com/Libensemble/libensemble/blob/develop/libensemble/tests/regression_tests/test_GPU_variable_resources.py>`_
     """  # noqa
 
-    b, n, lb, ub = _get_user_params(gen_specs["user"])
+    b, n, lb, ub = _get_user_params(gen_specs)
     rng = persis_info["rand_stream"]
     ps = PersistentSupport(libE_info, EVAL_GEN_TAG)
     tag = None
@@ -111,7 +111,7 @@ def uniform_sample_with_procs_gpus(_, persis_info, gen_specs, libE_info):
         `test_GPU_variable_resources.py <https://github.com/Libensemble/libensemble/blob/develop/libensemble/tests/regression_tests/test_GPU_variable_resources.py>`_
     """  # noqa
 
-    b, n, lb, ub = _get_user_params(gen_specs["user"])
+    b, n, lb, ub = _get_user_params(gen_specs)
     rng = persis_info["rand_stream"]
     ps = PersistentSupport(libE_info, EVAL_GEN_TAG)
     tag = None
@@ -137,7 +137,7 @@ def uniform_sample_with_var_priorities(_, persis_info, gen_specs, libE_info):
     resource sets and priorities are requested for each point.
     """
 
-    b, n, lb, ub = _get_user_params(gen_specs["user"])
+    b, n, lb, ub = _get_user_params(gen_specs)
     rng = persis_info["rand_stream"]
     ps = PersistentSupport(libE_info, EVAL_GEN_TAG)
 
@@ -175,7 +175,7 @@ def uniform_sample_diff_simulations(_, persis_info, gen_specs, libE_info):
         `test_GPU_variable_resources_multi_task.py <https://github.com/Libensemble/libensemble/blob/develop/libensemble/tests/regression_tests/test_GPU_variable_resources_multi_task.py>`_
     """  # noqa
 
-    b, n, lb, ub = _get_user_params(gen_specs["user"])
+    b, n, lb, ub = _get_user_params(gen_specs)
     rng = persis_info["rand_stream"]
     ps = PersistentSupport(libE_info, EVAL_GEN_TAG)
     tag = None
@@ -209,7 +209,7 @@ def uniform_sample_with_sim_gen_resources(_, persis_info, gen_specs, libE_info):
         `test_GPU_variable_resources.py <https://github.com/Libensemble/libensemble/blob/develop/libensemble/tests/regression_tests/test_GPU_variable_resources.py>`_
     """  # noqa
 
-    b, n, lb, ub = _get_user_params(gen_specs["user"])
+    b, n, lb, ub = _get_user_params(gen_specs)
     rng = persis_info["rand_stream"]
     ps = PersistentSupport(libE_info, EVAL_GEN_TAG)
     tag = None
diff --git a/libensemble/gen_funcs/sampling.py b/libensemble/gen_funcs/sampling.py
index efe9eab407..4a22e0984c 100644
--- a/libensemble/gen_funcs/sampling.py
+++ b/libensemble/gen_funcs/sampling.py
@@ -19,7 +19,7 @@
 @output_data([("x", float, 2)])  # default: can be overwritten in gen_specs
 def uniform_random_sample(_, persis_info, gen_specs):
     """
-    Generates ``gen_specs["user"]["gen_batch_size"]`` points uniformly over the domain
+    Generates ``gen_specs["batch_size"]`` points uniformly over the domain
     defined by ``gen_specs["user"]["ub"]`` and ``gen_specs["user"]["lb"]``.
 
     .. seealso::
@@ -29,7 +29,7 @@ def uniform_random_sample(_, persis_info, gen_specs):
     lb = gen_specs["user"]["lb"]
 
     n = len(lb)
-    b = gen_specs["user"]["gen_batch_size"]
+    b = gen_specs["batch_size"]
 
     H_o = np.zeros(b, dtype=gen_specs["out"])
 
@@ -40,7 +40,7 @@ def uniform_random_sample(_, persis_info, gen_specs):
 
 def uniform_random_sample_with_variable_resources(_, persis_info, gen_specs):
     """
-    Generates ``gen_specs["user"]["gen_batch_size"]`` points uniformly over the domain
+    Generates ``gen_specs["batch_size"]`` points uniformly over the domain
     defined by ``gen_specs["user"]["ub"]`` and ``gen_specs["user"]["lb"]``.
 
     Also randomly requests a different number of resource sets to be used in each evaluation.
@@ -56,7 +56,7 @@ def uniform_random_sample_with_variable_resources(_, persis_info, gen_specs):
     max_rsets = gen_specs["user"]["max_resource_sets"]
 
     n = len(lb)
-    b = gen_specs["user"]["gen_batch_size"]
+    b = gen_specs["batch_size"]
 
     H_o = np.zeros(b, dtype=gen_specs["out"])
 
@@ -84,7 +84,7 @@ def uniform_random_sample_with_var_priorities_and_resources(H, persis_info, gen_
     n = len(lb)
 
     if len(H) == 0:
-        b = gen_specs["user"]["initial_batch_size"]
+        b = gen_specs["initial_batch_size"]
 
         H_o = np.zeros(b, dtype=gen_specs["out"])
         for i in range(0, b):
@@ -119,7 +119,7 @@ def uniform_random_sample_obj_components(H, persis_info, gen_specs):
 
     n = len(lb)
     m = gen_specs["user"]["components"]
-    b = gen_specs["user"]["gen_batch_size"]
+    b = gen_specs["batch_size"]
 
     H_o = np.zeros(b * m, dtype=gen_specs["out"])
     for i in range(0, b):
@@ -143,7 +143,7 @@ def uniform_random_sample_cancel(_, persis_info, gen_specs):
     lb = gen_specs["user"]["lb"]
 
     n = len(lb)
-    b = gen_specs["user"]["gen_batch_size"]
+    b = gen_specs["batch_size"]
 
     H_o = np.zeros(b, dtype=gen_specs["out"])
     for i in range(b):
@@ -158,7 +158,7 @@ def uniform_random_sample_cancel(_, persis_info, gen_specs):
 @output_data([("x", float, (1,))])
 def latin_hypercube_sample(_, persis_info, gen_specs):
     """
-    Generates ``gen_specs["user"]["gen_batch_size"]`` points in a Latin
+    Generates ``gen_specs["batch_size"]`` points in a Latin
     hypercube sample over the domain defined by ``gen_specs["user"]["ub"]`` and
     ``gen_specs["user"]["lb"]``.
 
@@ -170,7 +170,7 @@ def latin_hypercube_sample(_, persis_info, gen_specs):
     lb = gen_specs["user"]["lb"]
 
     n = len(lb)
-    b = gen_specs["user"]["gen_batch_size"]
+    b = gen_specs["batch_size"]
 
     H_o = np.zeros(b, dtype=gen_specs["out"])
 
diff --git a/libensemble/gen_funcs/uniform_or_localopt.py b/libensemble/gen_funcs/uniform_or_localopt.py
index fca0e70bb6..ea234acff2 100644
--- a/libensemble/gen_funcs/uniform_or_localopt.py
+++ b/libensemble/gen_funcs/uniform_or_localopt.py
@@ -15,7 +15,7 @@
 
 def uniform_or_localopt(H, persis_info, gen_specs, libE_info):
     """
-    This generation function returns ``gen_specs["user"]["gen_batch_size"]`` uniformly
+    This generation function returns ``gen_specs["batch_size"]`` uniformly
     sampled points when called in nonpersistent mode (i.e., when
     ``libE_info["persistent"]`` isn't ``True``).  Otherwise, the generation
     function starts a persistent nlopt local optimization run.
@@ -31,7 +31,7 @@ def uniform_or_localopt(H, persis_info, gen_specs, libE_info):
         ub = gen_specs["user"]["ub"]
         lb = gen_specs["user"]["lb"]
         n = len(lb)
-        b = gen_specs["user"]["gen_batch_size"]
+        b = gen_specs["batch_size"]
 
         H_o = np.zeros(b, dtype=gen_specs["out"])
         for i in range(0, b):
diff --git a/libensemble/specs.py b/libensemble/specs.py
index a38efd4cb1..e3835b9cab 100644
--- a/libensemble/specs.py
+++ b/libensemble/specs.py
@@ -5,7 +5,7 @@
 import pydantic
 from pydantic import BaseModel, Field, model_validator
 
-from libensemble.alloc_funcs.give_sim_work_first import give_sim_work_first
+from libensemble.alloc_funcs.start_only_persistent import only_persistent_gens
 
 __all__ = ["SimSpecs", "GenSpecs", "AllocSpecs", "ExitCriteria", "LibeSpecs", "_EnsembleSpecs"]
 
@@ -200,20 +200,20 @@ class GenSpecs(BaseModel):
 
     initial_batch_size: int = 0
     """
-    Number of initial points to request that the generator create. If zero, falls back to ``batch_size``.
-    If both options are zero, defaults to the number of workers.
+    Initial sample size.
+    For standardized generators, this is the number of initial points to request that the
+    generator create. If zero, falls back to ``batch_size``.
+    For persistent generators, this is the number of points evaluated before switching
+    from batch return to asynchronous return (if ``async_return`` is True).
 
-    Note: Certain generators included with libEnsemble decide
-    batch sizes via ``gen_specs["user"]`` or other methods.
+    Note: Certain generators included with libEnsemble decide batch sizes via
+    ``gen_specs["user"]`` or other methods.
     """
 
     batch_size: int = 0
     """
     Number of points to generate in each batch. If zero, falls back to the number of
     completed evaluations most recently told to the generator.
-
-    Note: Certain generators included with libEnsemble decide
-    batch sizes via ``gen_specs["user"]`` or other methods.
     """
 
     threaded: bool | None = False
@@ -233,6 +233,44 @@ class GenSpecs(BaseModel):
     they will be automatically derived from VOCS.
     """
 
+    # Only used if using the only_persistent_gens allocation function (default)
+    num_active_gens: int = 1
+    """
+    Maximum number of persistent generators to start. Default: 1.
+    Only used if using the ``only_persistent_gens`` allocation function (the default).
+    """
+
+    async_return: bool = False
+    """
+    Return results to gen as they come in (after sample). Default: False (batch return).
+    Only used if using the ``only_persistent_gens`` allocation function (the default).
+    """
+
+    active_recv_gen: bool = False
+    """
+    Create gen in active receive mode. If True, the manager does not need to wait
+    for a return from the generator before sending further returned points.
+    Default: False. Only used if using the ``only_persistent_gens`` allocation function (the default).
+    """
+
+    give_all_with_same_priority: bool = False
+    """
+    If True, then all points with the same priority value are given as a batch to the sim.
+    Default: False. Only used if using the ``only_persistent_gens`` allocation function (the default).
+    """
+
+    alt_type: bool = False
+    """
+    If True, then the specialized allocator behavior for some persistent gens is used.
+    Only used if using the ``only_persistent_gens`` allocation function (the default).
+    """
+
+    batch_mode: bool = False
+    """
+    If True, then the generator will not be started if there are still simulations
+    running. Only used if using the ``give_sim_work_first`` allocation function.
+    """
+
     @model_validator(mode="after")
     def set_fields_from_vocs(self):
         """Set persis_in and outputs from VOCS if vocs is provided and fields are not set."""
@@ -280,16 +318,24 @@ class AllocSpecs(BaseModel):
     Specifications for configuring an Allocation Function.
     """
 
-    alloc_f: object = give_sim_work_first
+    alloc_f: object = only_persistent_gens
     """
     Python function matching the ``alloc_f`` interface. Decides when simulator and generator functions
     should be called, and with what resources and parameters.
+
+    .. note::
+        For libEnsemble v2.0, the default allocation function is now ``only_persistent_gens``, instead
+        of ``give_sim_work_first``.
     """
 
-    user: dict | None = {"num_active_gens": 1}
+    user: dict | None = {}
     """
     A user-data dictionary to place bounds, constants, settings, or other parameters
     for customizing the allocation function.
+
+    .. note::
+        As of libEnsemble v2.0, generator-specific allocation options (e.g., ``async_return``,
+        ``num_active_gens``) have been moved to :class:`GenSpecs<libensemble.specs.GenSpecs>`.
     """
 
     outputs: list[tuple] = Field([], alias="out")
diff --git a/libensemble/tests/functionality_tests/sine_gen.py b/libensemble/tests/functionality_tests/sine_gen.py
index 38f320e946..88619c0a42 100644
--- a/libensemble/tests/functionality_tests/sine_gen.py
+++ b/libensemble/tests/functionality_tests/sine_gen.py
@@ -11,7 +11,7 @@ def gen_random_sample(InputArray, persis_info, gen_specs):
 
     # Determine how many values to generate
     num = len(lower)
-    batch_size = user_specs["gen_batch_size"]
+    batch_size = gen_specs["batch_size"]
 
     # Create empty array of "batch_size" zeros. Array dtype should match "out" fields
     OutputArray = np.zeros(batch_size, dtype=gen_specs["out"])
diff --git a/libensemble/tests/functionality_tests/test_1d_sampling_no_comms_given.py b/libensemble/tests/functionality_tests/test_1d_sampling_no_comms_given.py
index 563ee920e2..676fb3cc83 100644
--- a/libensemble/tests/functionality_tests/test_1d_sampling_no_comms_given.py
+++ b/libensemble/tests/functionality_tests/test_1d_sampling_no_comms_given.py
@@ -17,11 +17,12 @@
 import numpy as np
 
 from libensemble import Ensemble
+from libensemble.alloc_funcs.give_sim_work_first import give_sim_work_first
 from libensemble.gen_funcs.sampling import latin_hypercube_sample as gen_f
 
 # Import libEnsemble items for this test
 from libensemble.sim_funcs.simple_sim import norm_eval as sim_f
-from libensemble.specs import ExitCriteria, GenSpecs, LibeSpecs, SimSpecs
+from libensemble.specs import AllocSpecs, ExitCriteria, GenSpecs, LibeSpecs, SimSpecs
 from libensemble.tools import check_npy_file_exists
 
 # Main block is necessary only when using local comms with spawn start method (default on macOS and Windows).
@@ -38,8 +39,8 @@
     gen_specs = GenSpecs(
         gen_f=gen_f,
         outputs=[("x", float, (1,))],
+        batch_size=500,
         user={
-            "gen_batch_size": 500,
             "lb": np.array([-3]),
             "ub": np.array([3]),
         },
@@ -55,6 +56,7 @@
     )
 
     sampling.add_random_streams()
+    sampling.alloc_specs = AllocSpecs(alloc_f=give_sim_work_first)
     H, persis_info, flag = sampling.run()
 
     if sampling.is_manager:
diff --git a/libensemble/tests/functionality_tests/test_1d_sampling_with_profile.py b/libensemble/tests/functionality_tests/test_1d_sampling_with_profile.py
index 645228d137..3e83be92f8 100644
--- a/libensemble/tests/functionality_tests/test_1d_sampling_with_profile.py
+++ b/libensemble/tests/functionality_tests/test_1d_sampling_with_profile.py
@@ -19,6 +19,7 @@
 
 import numpy as np
 
+from libensemble.alloc_funcs.give_sim_work_first import give_sim_work_first
 from libensemble.gen_funcs.sampling import latin_hypercube_sample as gen_f
 from libensemble.libE import libE
 from libensemble.sim_funcs.simple_sim import norm_eval as sim_f
@@ -41,8 +42,8 @@
     gen_specs = {
         "gen_f": gen_f,
         "out": [("x", float, (1,))],
+        "batch_size": 500,
         "user": {
-            "gen_batch_size": 500,
             "lb": np.array([-3]),
             "ub": np.array([3]),
         },
@@ -50,10 +51,16 @@
 
     persis_info = add_unique_random_streams({}, nworkers + 1)
 
+    alloc_specs = {
+        "alloc_f": give_sim_work_first,
+    }
+
     exit_criteria = {"sim_max": 501}
 
     # Perform the run
-    H, persis_info, flag = libE(sim_specs, gen_specs, exit_criteria, persis_info, libE_specs=libE_specs)
+    H, persis_info, flag = libE(
+        sim_specs, gen_specs, exit_criteria, persis_info, alloc_specs=alloc_specs, libE_specs=libE_specs
+    )
 
     if is_manager:
         assert len(H) >= 501
diff --git a/libensemble/tests/functionality_tests/test_1d_splitcomm.py b/libensemble/tests/functionality_tests/test_1d_splitcomm.py
index de73660d70..467afe613a 100644
--- a/libensemble/tests/functionality_tests/test_1d_splitcomm.py
+++ b/libensemble/tests/functionality_tests/test_1d_splitcomm.py
@@ -15,6 +15,7 @@
 
 import numpy as np
 
+from libensemble.alloc_funcs.give_sim_work_first import give_sim_work_first
 from libensemble.gen_funcs.sampling import latin_hypercube_sample as gen_f
 
 # Import libEnsemble items for this test
@@ -44,19 +45,25 @@
     gen_specs = {
         "gen_f": gen_f,
         "out": [("x", float, (1,))],
+        "batch_size": 500,
         "user": {
-            "gen_batch_size": 500,
             "lb": np.array([-3]),
             "ub": np.array([3]),
         },
     }
 
+    alloc_specs = {
+        "alloc_f": give_sim_work_first,
+    }
+
     persis_info = add_unique_random_streams({}, nworkers + 1, seed=1234)
 
     exit_criteria = {"gen_max": 501}
 
     # Perform the run
-    H, persis_info, flag = libE(sim_specs, gen_specs, exit_criteria, persis_info, libE_specs=libE_specs)
+    H, persis_info, flag = libE(
+        sim_specs, gen_specs, exit_criteria, persis_info, alloc_specs=alloc_specs, libE_specs=libE_specs
+    )
 
     if is_manager:
         assert len(H) >= 501
diff --git a/libensemble/tests/functionality_tests/test_1d_subcomm.py b/libensemble/tests/functionality_tests/test_1d_subcomm.py
index 7f607c31c9..cb033527ab 100644
--- a/libensemble/tests/functionality_tests/test_1d_subcomm.py
+++ b/libensemble/tests/functionality_tests/test_1d_subcomm.py
@@ -15,6 +15,7 @@
 
 import numpy as np
 
+from libensemble.alloc_funcs.give_sim_work_first import give_sim_work_first
 from libensemble.gen_funcs.sampling import latin_hypercube_sample as gen_f
 
 # Import libEnsemble items for this test
@@ -48,19 +49,25 @@
     gen_specs = {
         "gen_f": gen_f,
         "out": [("x", float, (1,))],
+        "batch_size": 500,
         "user": {
-            "gen_batch_size": 500,
             "lb": np.array([-3]),
             "ub": np.array([3]),
         },
     }
 
+    alloc_specs = {
+        "alloc_f": give_sim_work_first,
+    }
+
     persis_info = add_unique_random_streams({}, nworkers + 1, seed=1234)
 
     exit_criteria = {"gen_max": 501}
 
     # Perform the run
-    H, persis_info, flag = libE(sim_specs, gen_specs, exit_criteria, persis_info, libE_specs=libE_specs)
+    H, persis_info, flag = libE(
+        sim_specs, gen_specs, exit_criteria, persis_info, alloc_specs=alloc_specs, libE_specs=libE_specs
+    )
 
     if is_manager:
         assert len(H) >= 501
diff --git a/libensemble/tests/functionality_tests/test_1d_super_simple.py b/libensemble/tests/functionality_tests/test_1d_super_simple.py
index e84255714f..67c338e7de 100644
--- a/libensemble/tests/functionality_tests/test_1d_super_simple.py
+++ b/libensemble/tests/functionality_tests/test_1d_super_simple.py
@@ -15,6 +15,7 @@
 
 import numpy as np
 
+from libensemble.alloc_funcs.give_sim_work_first import give_sim_work_first
 from libensemble.gen_funcs.sampling import latin_hypercube_sample as gen_f
 
 # Import libEnsemble items for this test
@@ -28,10 +29,6 @@ def sim_f(In):
     return Out
 
 
-def sim_f_noreturn(In):
-    print(np.linalg.norm(In))
-
-
 if __name__ == "__main__":
     nworkers, is_manager, libE_specs, _ = parse_args()
 
@@ -44,8 +41,8 @@ def sim_f_noreturn(In):
     gen_specs = {
         "gen_f": gen_f,
         "out": [("x", float, (1,))],
+        "batch_size": 500,
         "user": {
-            "gen_batch_size": 500,
             "lb": np.array([-3]),
             "ub": np.array([3]),
         },
@@ -55,21 +52,15 @@ def sim_f_noreturn(In):
 
     exit_criteria = {"gen_max": 501}
 
-    H, persis_info, flag = libE(sim_specs, gen_specs, exit_criteria, persis_info, libE_specs=libE_specs)
-
-    if is_manager:
-        assert len(H) >= 501
-        print("\nlibEnsemble with random sampling has generated enough points")
-        save_libE_output(H, persis_info, __file__, nworkers)
-
-    # Test running a sim_f without any returns
-    sim_specs = {
-        "sim_f": sim_f_noreturn,
-        "in": ["x"],
+    alloc_specs = {
+        "alloc_f": give_sim_work_first,
     }
 
-    H, persis_info, flag = libE(sim_specs, gen_specs, exit_criteria, persis_info, libE_specs=libE_specs)
+    H, persis_info, flag = libE(
+        sim_specs, gen_specs, exit_criteria, persis_info, alloc_specs=alloc_specs, libE_specs=libE_specs
+    )
 
     if is_manager:
         assert len(H) >= 501
         print("\nlibEnsemble with random sampling has generated enough points")
+        save_libE_output(H, persis_info, __file__, nworkers)
diff --git a/libensemble/tests/functionality_tests/test_1d_uniform_sampling_with_comm_dup.py b/libensemble/tests/functionality_tests/test_1d_uniform_sampling_with_comm_dup.py
index 7d2d9f588f..ea070dc72b 100644
--- a/libensemble/tests/functionality_tests/test_1d_uniform_sampling_with_comm_dup.py
+++ b/libensemble/tests/functionality_tests/test_1d_uniform_sampling_with_comm_dup.py
@@ -19,6 +19,7 @@
 
 import numpy as np
 
+from libensemble.alloc_funcs.give_sim_work_first import give_sim_work_first
 from libensemble.gen_funcs.sampling import uniform_random_sample as gen_f
 
 # Import libEnsemble items for this test
@@ -51,10 +52,10 @@
         "gen_f": gen_f,
         "in": ["sim_id"],
         "out": [("x", float, (1,))],
+        "batch_size": 500,
         "user": {
             "lb": np.array([-3]),
             "ub": np.array([3]),
-            "gen_batch_size": 500,
         },
     }
 
@@ -62,8 +63,12 @@
 
     exit_criteria = {"gen_max": 501}
 
+    alloc_specs = {
+        "alloc_f": give_sim_work_first,
+    }
+
     # Perform the run
-    H, persis_info, flag = libE(sim_specs, gen_specs, exit_criteria, persis_info)
+    H, persis_info, flag = libE(sim_specs, gen_specs, exit_criteria, persis_info, alloc_specs=alloc_specs)
 
     if is_manager:
         # assert libE_specs["comms"] == "mpi", "MPI default comms should be set"
diff --git a/libensemble/tests/functionality_tests/test_GPU_gen_resources.py b/libensemble/tests/functionality_tests/test_GPU_gen_resources.py
index d77088d7e4..8feb36ea77 100644
--- a/libensemble/tests/functionality_tests/test_GPU_gen_resources.py
+++ b/libensemble/tests/functionality_tests/test_GPU_gen_resources.py
@@ -32,7 +32,6 @@
 
 import numpy as np
 
-from libensemble.alloc_funcs.start_only_persistent import only_persistent_gens as alloc_f
 from libensemble.executors.mpi_executor import MPIExecutor
 from libensemble.gen_funcs.persistent_sampling_var_resources import uniform_sample_with_sim_gen_resources as gen_f
 
@@ -79,8 +78,10 @@
         "gen_f": gen_f,
         "persis_in": ["f", "x", "sim_id"],
         "out": [("num_procs", int), ("num_gpus", int), ("x", float, n)],
+        "initial_batch_size": nworkers - 1,
+        "give_all_with_same_priority": False,
+        "async_return": False,
         "user": {
-            "initial_batch_size": nworkers - 1,
             "max_procs": nworkers - 1,  # Any sim created can req. 1 worker up to all.
             "lb": np.array([-3, -2]),
             "ub": np.array([3, 2]),
@@ -88,14 +89,6 @@
         },
     }
 
-    alloc_specs = {
-        "alloc_f": alloc_f,
-        "user": {
-            "give_all_with_same_priority": False,
-            "async_return": False,  # False batch returns
-        },
-    }
-
     exit_criteria = {"sim_max": 20}
     libE_specs["resource_info"] = {"cores_on_node": (nworkers * 2, nworkers * 4), "gpus_on_node": nworkers}
 
@@ -126,8 +119,6 @@
                 gen_specs["user"]["max_procs"] = max(nworkers - 2, 1)
 
             # Perform the run
-            H, persis_info, flag = libE(
-                sim_specs, gen_specs, exit_criteria, persis_info, libE_specs=libE_specs, alloc_specs=alloc_specs
-            )
+            H, persis_info, flag = libE(sim_specs, gen_specs, exit_criteria, persis_info, libE_specs=libE_specs)
 
 # All asserts are in gen and sim funcs
diff --git a/libensemble/tests/functionality_tests/test_active_persistent_worker_abort.py b/libensemble/tests/functionality_tests/test_active_persistent_worker_abort.py
index 7d99968629..07c6db8a39 100644
--- a/libensemble/tests/functionality_tests/test_active_persistent_worker_abort.py
+++ b/libensemble/tests/functionality_tests/test_active_persistent_worker_abort.py
@@ -48,12 +48,14 @@
         "gen_f": gen_f,
         "persis_in": ["x", "f"],
         "out": gen_out,
+        "batch_size": 2,
+        "batch_mode": True,
+        "num_active_gens": 1,
         "user": {
             "localopt_method": "LN_BOBYQA",
             "xtol_rel": 1e-4,
             "lb": np.array([-3, -2]),
             "ub": np.array([3, 2]),
-            "gen_batch_size": 2,
             "dist_to_bound_multiple": 0.5,
             "localopt_maxeval": 4,
         },
@@ -61,10 +63,6 @@
 
     alloc_specs = {
         "alloc_f": alloc_f,
-        "user": {
-            "batch_mode": True,
-            "num_active_gens": 1,
-        },
     }
 
     persis_info = add_unique_random_streams({}, nworkers + 1)
diff --git a/libensemble/tests/functionality_tests/test_asktell_sampling.py b/libensemble/tests/functionality_tests/test_asktell_sampling.py
index cebb858df2..fccb9cd6be 100644
--- a/libensemble/tests/functionality_tests/test_asktell_sampling.py
+++ b/libensemble/tests/functionality_tests/test_asktell_sampling.py
@@ -19,7 +19,6 @@
 import libensemble.sim_funcs.six_hump_camel as six_hump_camel
 
 # Import libEnsemble items for this test
-from libensemble.alloc_funcs.start_only_persistent import only_persistent_gens as alloc_f
 from libensemble.gen_classes.sampling import UniformSample
 from libensemble.libE import libE
 from libensemble.sim_funcs.executor_hworld import executor_hworld as sim_f_exec
@@ -48,7 +47,6 @@ def sim_f(In):
         "initial_batch_size": 20,
         "batch_size": 10,
         "user": {
-            "initial_batch_size": 20,  # for wrapper
             "lb": np.array([-3, -2]),
             "ub": np.array([3, 2]),
         },
@@ -59,7 +57,6 @@ def sim_f(In):
 
     vocs = VOCS(variables=variables, objectives=objectives)
 
-    alloc_specs = {"alloc_f": alloc_f}
     exit_criteria = {"gen_max": 201}
     persis_info = add_unique_random_streams({}, nworkers + 1, seed=1234)
 
@@ -89,9 +86,7 @@ def sim_f(In):
             }
 
         gen_specs["generator"] = generator
-        H, persis_info, flag = libE(
-            sim_specs, gen_specs, exit_criteria, persis_info, alloc_specs, libE_specs=libE_specs
-        )
+        H, persis_info, flag = libE(sim_specs, gen_specs, exit_criteria, persis_info, libE_specs=libE_specs)
 
         if is_manager:
             print(H[["sim_id", "x", "f"]][:10])
diff --git a/libensemble/tests/functionality_tests/test_asktell_sampling_external_gen.py b/libensemble/tests/functionality_tests/test_asktell_sampling_external_gen.py
index 8578da720c..318cb49ecf 100644
--- a/libensemble/tests/functionality_tests/test_asktell_sampling_external_gen.py
+++ b/libensemble/tests/functionality_tests/test_asktell_sampling_external_gen.py
@@ -20,12 +20,12 @@
 
 from libensemble import Ensemble
 
-# Import libEnsemble items for this test
-from libensemble.alloc_funcs.start_only_persistent import only_persistent_gens as alloc_f
-
 # from libensemble.gen_classes.external.sampling import UniformSampleArray
 from libensemble.gen_classes.external.sampling import UniformSample
-from libensemble.specs import AllocSpecs, ExitCriteria, GenSpecs, LibeSpecs, SimSpecs
+from libensemble.specs import ExitCriteria, GenSpecs, LibeSpecs, SimSpecs
+
+# Import libEnsemble items for this test
+
 
 # from gest_api.vocs import ContinuousVariable
 
@@ -75,7 +75,6 @@ def sim_f_scalar(In):
             vocs=vocs,
         )
 
-        alloc_specs = AllocSpecs(alloc_f=alloc_f)
         exit_criteria = ExitCriteria(gen_max=201)
 
         ensemble = Ensemble(
@@ -83,7 +82,6 @@ def sim_f_scalar(In):
             sim_specs=sim_specs,
             gen_specs=gen_specs,
             exit_criteria=exit_criteria,
-            alloc_specs=alloc_specs,
             libE_specs=libE_specs,
         )
 
diff --git a/libensemble/tests/functionality_tests/test_calc_exception.py b/libensemble/tests/functionality_tests/test_calc_exception.py
index 361e1be3a8..a897f35eb7 100644
--- a/libensemble/tests/functionality_tests/test_calc_exception.py
+++ b/libensemble/tests/functionality_tests/test_calc_exception.py
@@ -13,6 +13,7 @@
 
 import numpy as np
 
+from libensemble.alloc_funcs.give_sim_work_first import give_sim_work_first
 from libensemble.gen_funcs.sampling import uniform_random_sample as gen_f
 from libensemble.libE import libE
 from libensemble.manager import LoggedException
@@ -38,15 +39,19 @@ def six_hump_camel_err(H, persis_info, sim_specs, _):
         "gen_f": gen_f,
         "in": ["sim_id"],
         "out": [("x", float, 2)],
+        "batch_size": 10,
         "user": {
             "lb": np.array([-3, -2]),
             "ub": np.array([3, 2]),
-            "gen_batch_size": 10,
         },
     }
 
     persis_info = add_unique_random_streams({}, nworkers + 1)
 
+    alloc_specs = {
+        "alloc_f": give_sim_work_first,
+    }
+
     exit_criteria = {"wallclock_max": 10}
 
     libE_specs["abort_on_exception"] = False
@@ -54,7 +59,9 @@ def six_hump_camel_err(H, persis_info, sim_specs, _):
     # Perform the run
     return_flag = 1
     try:
-        H, persis_info, flag = libE(sim_specs, gen_specs, exit_criteria, persis_info, libE_specs=libE_specs)
+        H, persis_info, flag = libE(
+            sim_specs, gen_specs, exit_criteria, persis_info, alloc_specs=alloc_specs, libE_specs=libE_specs
+        )
     except LoggedException as e:
         print(f"Caught deliberate exception: {e}")
         return_flag = 0
diff --git a/libensemble/tests/functionality_tests/test_cancel_in_alloc.py b/libensemble/tests/functionality_tests/test_cancel_in_alloc.py
index d2c005a040..29d3d7cdb1 100644
--- a/libensemble/tests/functionality_tests/test_cancel_in_alloc.py
+++ b/libensemble/tests/functionality_tests/test_cancel_in_alloc.py
@@ -43,8 +43,10 @@
         "gen_f": gen_f,
         "in": ["sim_id"],
         "out": [("x", float, (2,))],
+        "batch_size": 5,
+        "batch_mode": False,
+        "num_active_gens": 1,
         "user": {
-            "gen_batch_size": 5,
             "lb": np.array([-3, -2]),
             "ub": np.array([3, 2]),
         },
@@ -54,8 +56,6 @@
         "alloc_f": give_sim_work_first,
         "user": {
             "cancel_sims_time": 3,
-            "batch_mode": False,
-            "num_active_gens": 1,
         },
     }
 
diff --git a/libensemble/tests/functionality_tests/test_comms.py b/libensemble/tests/functionality_tests/test_comms.py
index 52c3e0771a..7bec22b576 100644
--- a/libensemble/tests/functionality_tests/test_comms.py
+++ b/libensemble/tests/functionality_tests/test_comms.py
@@ -16,6 +16,7 @@
 
 import numpy as np
 
+from libensemble.alloc_funcs.give_sim_work_first import give_sim_work_first
 from libensemble.executors.mpi_executor import MPIExecutor  # Only used to get workerID in float_x1000
 from libensemble.gen_funcs.sampling import uniform_random_sample as gen_f
 
@@ -44,10 +45,10 @@
         "gen_f": gen_f,
         "in": ["sim_id"],
         "out": [("x", float, (2,))],
+        "batch_size": sim_max,
         "user": {
             "lb": np.array([-3, -2]),
             "ub": np.array([3, 2]),
-            "gen_batch_size": sim_max,
         },
     }
 
@@ -55,8 +56,14 @@
 
     exit_criteria = {"sim_max": sim_max, "wallclock_max": 300}
 
+    alloc_specs = {
+        "alloc_f": give_sim_work_first,
+    }
+
     # Perform the run
-    H, persis_info, flag = libE(sim_specs, gen_specs, exit_criteria, persis_info, libE_specs=libE_specs)
+    H, persis_info, flag = libE(
+        sim_specs, gen_specs, exit_criteria, persis_info, alloc_specs=alloc_specs, libE_specs=libE_specs
+    )
 
     if is_manager:
         assert flag == 0
diff --git a/libensemble/tests/functionality_tests/test_elapsed_time_abort.py b/libensemble/tests/functionality_tests/test_elapsed_time_abort.py
index 9e7ab97049..feff67c9e8 100644
--- a/libensemble/tests/functionality_tests/test_elapsed_time_abort.py
+++ b/libensemble/tests/functionality_tests/test_elapsed_time_abort.py
@@ -38,8 +38,10 @@
         "gen_f": gen_f,
         "in": ["sim_id"],
         "out": [("x", float, (2,))],
+        "batch_size": 5,
+        "batch_mode": False,
+        "num_active_gens": 2,
         "user": {
-            "gen_batch_size": 5,
             "lb": np.array([-3, -2]),
             "ub": np.array([3, 2]),
         },
@@ -47,10 +49,6 @@
 
     alloc_specs = {
         "alloc_f": give_sim_work_first,
-        "user": {
-            "batch_mode": False,
-            "num_active_gens": 2,
-        },
     }
 
     persis_info = add_unique_random_streams({}, nworkers + 1)
diff --git a/libensemble/tests/functionality_tests/test_evaluate_existing_plus_gen.py b/libensemble/tests/functionality_tests/test_evaluate_existing_plus_gen.py
index fe3d8dad8e..b470ccb5a5 100644
--- a/libensemble/tests/functionality_tests/test_evaluate_existing_plus_gen.py
+++ b/libensemble/tests/functionality_tests/test_evaluate_existing_plus_gen.py
@@ -18,9 +18,10 @@
 
 # Import libEnsemble items for this test
 from libensemble import Ensemble
+from libensemble.alloc_funcs.give_sim_work_first import give_sim_work_first
 from libensemble.gen_funcs.sampling import latin_hypercube_sample as gen_f
 from libensemble.sim_funcs.six_hump_camel import six_hump_camel as sim_f
-from libensemble.specs import ExitCriteria, GenSpecs, SimSpecs
+from libensemble.specs import AllocSpecs, ExitCriteria, GenSpecs, SimSpecs
 from libensemble.tools import add_unique_random_streams
 
 
@@ -49,8 +50,8 @@ def create_H0(persis_info, gen_specs, H0_size):
     gen_specs = {
         "gen_f": gen_f,
         "outputs": [("x", float, (2,))],
+        "batch_size": 50,
         "user": {
-            "gen_batch_size": 50,
             "lb": np.array([-3, -3]),
             "ub": np.array([3, 3]),
         },
@@ -59,6 +60,7 @@ def create_H0(persis_info, gen_specs, H0_size):
     sampling.exit_criteria = ExitCriteria(sim_max=100)
     sampling.persis_info = add_unique_random_streams({}, sampling.nworkers + 1)
     sampling.H0 = create_H0(sampling.persis_info, gen_specs, 50)
+    sampling.alloc_specs = AllocSpecs(alloc_f=give_sim_work_first)
     sampling.run()
 
     if sampling.is_manager:
diff --git a/libensemble/tests/functionality_tests/test_executor_forces_tutorial.py b/libensemble/tests/functionality_tests/test_executor_forces_tutorial.py
index c25ee9e4dc..64dae1727a 100644
--- a/libensemble/tests/functionality_tests/test_executor_forces_tutorial.py
+++ b/libensemble/tests/functionality_tests/test_executor_forces_tutorial.py
@@ -5,10 +5,9 @@
 from forces_simf import run_forces  # Sim func from current dir
 
 from libensemble import Ensemble
-from libensemble.alloc_funcs.start_only_persistent import only_persistent_gens as alloc_f
 from libensemble.executors import MPIExecutor
 from libensemble.gen_funcs.persistent_sampling import persistent_uniform as gen_f
-from libensemble.specs import AllocSpecs, ExitCriteria, GenSpecs, LibeSpecs, SimSpecs
+from libensemble.specs import ExitCriteria, GenSpecs, LibeSpecs, SimSpecs
 
 if __name__ == "__main__":
     # Initialize MPI Executor
@@ -43,20 +42,15 @@
         inputs=[],  # No input when starting persistent generator
         persis_in=["sim_id"],  # Return sim_ids of evaluated points to generator
         outputs=[("x", float, (1,))],
+        initial_batch_size=nsim_workers,
+        async_return=False,
         user={
-            "initial_batch_size": nsim_workers,
             "lb": np.array([1000]),  # min particles
             "ub": np.array([3000]),  # max particles
         },
     )  # gen_specs_end_tag
 
     # Starts one persistent generator. Simulated values are returned in batch.
-    ensemble.alloc_specs = AllocSpecs(
-        alloc_f=alloc_f,
-        user={
-            "async_return": False,  # False causes batch returns
-        },
-    )
 
     # Instruct libEnsemble to exit after this many simulations
     ensemble.exit_criteria = ExitCriteria(sim_max=8)
diff --git a/libensemble/tests/functionality_tests/test_executor_forces_tutorial_2.py b/libensemble/tests/functionality_tests/test_executor_forces_tutorial_2.py
index e3c24fc4f6..5b5fe0a67e 100644
--- a/libensemble/tests/functionality_tests/test_executor_forces_tutorial_2.py
+++ b/libensemble/tests/functionality_tests/test_executor_forces_tutorial_2.py
@@ -5,10 +5,9 @@
 from forces_simf import run_forces  # Sim func from current dir
 
 from libensemble import Ensemble, logger
-from libensemble.alloc_funcs.start_only_persistent import only_persistent_gens as alloc_f
 from libensemble.executors import MPIExecutor
 from libensemble.gen_funcs.persistent_sampling import persistent_uniform as gen_f
-from libensemble.specs import AllocSpecs, ExitCriteria, GenSpecs, LibeSpecs, SimSpecs
+from libensemble.specs import ExitCriteria, GenSpecs, LibeSpecs, SimSpecs
 
 logger.set_level("DEBUG")
 
@@ -45,20 +44,15 @@
         inputs=[],  # No input when starting persistent generator
         persis_in=["sim_id"],  # Return sim_ids of evaluated points to generator
         outputs=[("x", float, (1,))],
+        initial_batch_size=nsim_workers,
+        async_return=True,
         user={
-            "initial_batch_size": nsim_workers,
             "lb": np.array([1000]),  # min particles
             "ub": np.array([3000]),  # max particles
         },
     )  # gen_specs_end_tag
 
     # Starts one persistent generator. Simulated values are returned in batch.
-    ensemble.alloc_specs = AllocSpecs(
-        alloc_f=alloc_f,
-        user={
-            "async_return": True,
-        },
-    )
 
     # Instruct libEnsemble to exit after this many simulations
     ensemble.exit_criteria = ExitCriteria(sim_max=8)
diff --git a/libensemble/tests/functionality_tests/test_executor_hworld_pass_fail.py b/libensemble/tests/functionality_tests/test_executor_hworld_pass_fail.py
index 1b61bf8d25..7266953c36 100644
--- a/libensemble/tests/functionality_tests/test_executor_hworld_pass_fail.py
+++ b/libensemble/tests/functionality_tests/test_executor_hworld_pass_fail.py
@@ -15,6 +15,7 @@
 import numpy as np
 
 import libensemble.sim_funcs.six_hump_camel as six_hump_camel
+from libensemble.alloc_funcs.give_sim_work_first import give_sim_work_first
 from libensemble.executors.mpi_executor import MPIExecutor
 from libensemble.gen_funcs.sampling import uniform_random_sample as gen_f
 from libensemble.libE import libE
@@ -76,10 +77,10 @@
         "gen_f": gen_f,
         "in": ["sim_id"],
         "out": [("x", float, (2,))],
+        "batch_size": nworkers,
         "user": {
             "lb": np.array([-3, -2]),
             "ub": np.array([3, 2]),
-            "gen_batch_size": nworkers,
         },
     }
 
@@ -88,8 +89,12 @@
     # num sim_ended_count conditions in executor_hworld
     exit_criteria = {"sim_max": nworkers * 5}
 
+    alloc_specs = {
+        "alloc_f": give_sim_work_first,
+    }
+
     # Perform the run
-    H, persis_info, flag = libE(sim_specs, gen_specs, exit_criteria, persis_info, libE_specs=libE_specs)
+    H, persis_info, flag = libE(sim_specs, gen_specs, exit_criteria, persis_info, alloc_specs, libE_specs=libE_specs)
 
     if is_manager:
         print("\nChecking expected task status against Workers ...\n")
diff --git a/libensemble/tests/functionality_tests/test_executor_hworld_timeout.py b/libensemble/tests/functionality_tests/test_executor_hworld_timeout.py
index 496eced316..482641eda2 100644
--- a/libensemble/tests/functionality_tests/test_executor_hworld_timeout.py
+++ b/libensemble/tests/functionality_tests/test_executor_hworld_timeout.py
@@ -15,6 +15,7 @@
 import numpy as np
 
 import libensemble.sim_funcs.six_hump_camel as six_hump_camel
+from libensemble.alloc_funcs.give_sim_work_first import give_sim_work_first
 from libensemble.executors.mpi_executor import MPIExecutor
 from libensemble.gen_funcs.sampling import uniform_random_sample as gen_f
 
@@ -78,13 +79,17 @@
         "gen_f": gen_f,
         "in": ["sim_id"],
         "out": [("x", float, (2,))],
+        "batch_size": nworkers,
         "user": {
             "lb": np.array([-3, -2]),
             "ub": np.array([3, 2]),
-            "gen_batch_size": nworkers,
         },
     }
 
+    alloc_specs = {
+        "alloc_f": give_sim_work_first,
+    }
+
     persis_info = add_unique_random_streams({}, nworkers + 1)
 
     exit_criteria = {"wallclock_max": 10}
@@ -97,7 +102,9 @@
 
     for i in range(iterations):
         # Perform the run
-        H, persis_info, flag = libE(sim_specs, gen_specs, exit_criteria, persis_info, libE_specs=libE_specs)
+        H, persis_info, flag = libE(
+            sim_specs, gen_specs, exit_criteria, persis_info, alloc_specs, libE_specs=libE_specs
+        )
 
         if is_manager:
             print("\nChecking expected task status against Workers ...\n")
diff --git a/libensemble/tests/functionality_tests/test_executor_simple.py b/libensemble/tests/functionality_tests/test_executor_simple.py
index ac4c201a7a..22ee48fec5 100644
--- a/libensemble/tests/functionality_tests/test_executor_simple.py
+++ b/libensemble/tests/functionality_tests/test_executor_simple.py
@@ -12,6 +12,7 @@
 import numpy as np
 
 import libensemble.sim_funcs.six_hump_camel as six_hump_camel
+from libensemble.alloc_funcs.give_sim_work_first import give_sim_work_first
 from libensemble.executors.mpi_executor import MPIExecutor
 from libensemble.gen_funcs.sampling import uniform_random_sample as gen_f
 from libensemble.libE import libE
@@ -49,10 +50,10 @@
         "gen_f": gen_f,
         "in": ["sim_id"],
         "out": [("x", float, (2,))],
+        "batch_size": nworkers,
         "user": {
             "lb": np.array([-3, -2]),
             "ub": np.array([3, 2]),
-            "gen_batch_size": nworkers,
         },
     }
 
@@ -61,8 +62,12 @@
     # num sim_ended_count conditions in executor_hworld
     exit_criteria = {"sim_max": nworkers * 5}
 
+    alloc_specs = {
+        "alloc_f": give_sim_work_first,
+    }
+
     # Perform the run
-    H, persis_info, flag = libE(sim_specs, gen_specs, exit_criteria, persis_info, libE_specs=libE_specs)
+    H, persis_info, flag = libE(sim_specs, gen_specs, exit_criteria, persis_info, alloc_specs, libE_specs=libE_specs)
 
     if is_manager:
         print("\nChecking expected task status against Workers ...\n")
diff --git a/libensemble/tests/functionality_tests/test_fast_alloc.py b/libensemble/tests/functionality_tests/test_fast_alloc.py
index a2b6a75666..af4f907c8d 100644
--- a/libensemble/tests/functionality_tests/test_fast_alloc.py
+++ b/libensemble/tests/functionality_tests/test_fast_alloc.py
@@ -43,8 +43,8 @@
         "gen_f": gen_f,
         "in": ["sim_id"],
         "out": [("x", float, (2,))],
+        "batch_size": num_pts,
         "user": {
-            "gen_batch_size": num_pts,
             "lb": np.array([-3, -2]),
             "ub": np.array([3, 2]),
         },
@@ -73,7 +73,7 @@
 
             if time == 0:
                 sim_specs["user"].pop("uniform_random_pause_ub")
-                gen_specs["user"]["gen_batch_size"] = num_pts // 2
+                gen_specs["batch_size"] = num_pts // 2
 
             persis_info["next_to_give"] = 0
             persis_info["total_gen_calls"] = 1
diff --git a/libensemble/tests/functionality_tests/test_local_sine_tutorial.py b/libensemble/tests/functionality_tests/test_local_sine_tutorial.py
index 89c3a5e7c8..b09b7c86ed 100644
--- a/libensemble/tests/functionality_tests/test_local_sine_tutorial.py
+++ b/libensemble/tests/functionality_tests/test_local_sine_tutorial.py
@@ -4,8 +4,7 @@
 from sine_sim import sim_find_sine
 
 from libensemble import Ensemble
-from libensemble.alloc_funcs.start_only_persistent import only_persistent_gens
-from libensemble.specs import AllocSpecs, ExitCriteria, GenSpecs, LibeSpecs, SimSpecs
+from libensemble.specs import ExitCriteria, GenSpecs, LibeSpecs, SimSpecs
 
 if __name__ == "__main__":  # Python-quirk required on macOS and windows
     libE_specs = LibeSpecs(nworkers=4, comms="local")
@@ -20,9 +19,6 @@
         batch_size=4,
     )
 
-    # Specify that libEnsemble should pass work back-and-forth between the generator object
-    alloc_specs = AllocSpecs(alloc_f=only_persistent_gens)
-
     sim_specs = SimSpecs(
         sim_f=sim_find_sine,  # Our simulator function
         inputs=["x"],  # InputArray field names. "x" from gen_f output
@@ -31,7 +27,7 @@
 
     exit_criteria = ExitCriteria(sim_max=80)  # Stop libEnsemble after 80 simulations
 
-    ensemble = Ensemble(sim_specs, gen_specs, exit_criteria, libE_specs, alloc_specs)
+    ensemble = Ensemble(sim_specs, gen_specs, exit_criteria, libE_specs)
     ensemble.add_random_streams()  # setup the random streams unique to each worker
     ensemble.run()  # start the ensemble. Blocks until completion.
 
@@ -44,7 +40,7 @@
 
     colors = ["b", "g", "r", "y", "m", "c", "k", "w"]
 
-    for i in range(1, libE_specs.nworkers + 1):
+    for i in range(1, libE_specs.nworkers + 1):  # type: ignore
         worker_xy = np.extract(history["sim_worker"] == i, history)
         x = [entry.tolist() for entry in worker_xy["x"]]
         y = [entry for entry in worker_xy["y"]]
diff --git a/libensemble/tests/functionality_tests/test_local_sine_tutorial_2.py b/libensemble/tests/functionality_tests/test_local_sine_tutorial_2.py
index 11911f343c..ddb61be255 100644
--- a/libensemble/tests/functionality_tests/test_local_sine_tutorial_2.py
+++ b/libensemble/tests/functionality_tests/test_local_sine_tutorial_2.py
@@ -3,7 +3,8 @@
 from sine_sim import sim_find_sine
 
 from libensemble import Ensemble
-from libensemble.specs import ExitCriteria, GenSpecs, LibeSpecs, SimSpecs
+from libensemble.alloc_funcs.give_sim_work_first import give_sim_work_first
+from libensemble.specs import AllocSpecs, ExitCriteria, GenSpecs, LibeSpecs, SimSpecs
 
 if __name__ == "__main__":
     libE_specs = LibeSpecs(nworkers=4, comms="local")
@@ -11,10 +12,10 @@
     gen_specs = GenSpecs(
         gen_f=gen_random_sample,  # Our generator function
         out=[("x", float, (1,))],  # gen_f output (name, type, size)
+        batch_size=10,  # number of x's gen_f generates per call
         user={
             "lower": np.array([-6]),  # lower boundary for random sampling
             "upper": np.array([6]),  # upper boundary for random sampling
-            "gen_batch_size": 10,  # number of x's gen_f generates per call
         },
     )
 
@@ -24,9 +25,11 @@
         out=[("y", float)],  # sim_f output. "y" = sine("x")
     )
 
+    alloc_specs = AllocSpecs(alloc_f=give_sim_work_first)
+
     exit_criteria = ExitCriteria(gen_max=160)
 
-    ensemble = Ensemble(sim_specs, gen_specs, exit_criteria, libE_specs)
+    ensemble = Ensemble(sim_specs, gen_specs, exit_criteria, libE_specs, alloc_specs)
     ensemble.add_random_streams()
     ensemble.run()
 
diff --git a/libensemble/tests/functionality_tests/test_local_sine_tutorial_3.py b/libensemble/tests/functionality_tests/test_local_sine_tutorial_3.py
index d57a0f842b..d67a544331 100644
--- a/libensemble/tests/functionality_tests/test_local_sine_tutorial_3.py
+++ b/libensemble/tests/functionality_tests/test_local_sine_tutorial_3.py
@@ -3,7 +3,8 @@
 from sine_sim import sim_find_sine
 
 from libensemble import Ensemble
-from libensemble.specs import ExitCriteria, GenSpecs, SimSpecs
+from libensemble.alloc_funcs.give_sim_work_first import give_sim_work_first
+from libensemble.specs import AllocSpecs, ExitCriteria, GenSpecs, SimSpecs
 
 if __name__ == "__main__":  # Python-quirk required on macOS and windows
     # libE_specs = LibeSpecs(nworkers=4, comms="local")
@@ -11,10 +12,10 @@
     gen_specs = GenSpecs(
         gen_f=gen_random_sample,  # Our generator function
         out=[("x", float, (1,))],  # gen_f output (name, type, size)
+        batch_size=5,  # number of x's gen_f generates per call
         user={
             "lower": np.array([-3]),  # lower boundary for random sampling
             "upper": np.array([3]),  # upper boundary for random sampling
-            "gen_batch_size": 5,  # number of x's gen_f generates per call
         },
     )
 
@@ -26,8 +27,10 @@
 
     exit_criteria = ExitCriteria(sim_max=80)  # Stop libEnsemble after 80 simulations
 
+    alloc_specs = AllocSpecs(alloc_f=give_sim_work_first)
+
     # replace libE_specs with parse_args=True. Detects MPI runtime
-    ensemble = Ensemble(sim_specs, gen_specs, exit_criteria, parse_args=True)
+    ensemble = Ensemble(sim_specs, gen_specs, exit_criteria, alloc_specs=alloc_specs, parse_args=True)
 
     ensemble.add_random_streams()
     ensemble.run()  # start the ensemble. Blocks until completion.
diff --git a/libensemble/tests/functionality_tests/test_mpi_gpu_settings.py b/libensemble/tests/functionality_tests/test_mpi_gpu_settings.py
index 31e537a31d..203a1ca459 100644
--- a/libensemble/tests/functionality_tests/test_mpi_gpu_settings.py
+++ b/libensemble/tests/functionality_tests/test_mpi_gpu_settings.py
@@ -47,7 +47,6 @@
 
 import numpy as np
 
-from libensemble.alloc_funcs.start_only_persistent import only_persistent_gens as alloc_f
 from libensemble.executors.mpi_executor import MPIExecutor
 from libensemble.gen_funcs.persistent_sampling_var_resources import uniform_sample as gen_f
 
@@ -87,22 +86,16 @@
         "gen_f": gen_f,
         "persis_in": ["f", "x", "sim_id"],
         "out": [("priority", float), ("resource_sets", int), ("x", float, n)],
+        "give_all_with_same_priority": False,
+        "async_return": False,
+        "initial_batch_size": nworkers - 1,
         "user": {
-            "initial_batch_size": nworkers - 1,
             "max_resource_sets": nworkers - 1,  # Any sim created can req. 1 worker up to all.
             "lb": np.array([-3, -2]),
             "ub": np.array([3, 2]),
         },
     }
 
-    alloc_specs = {
-        "alloc_f": alloc_f,
-        "user": {
-            "give_all_with_same_priority": False,
-            "async_return": False,  # False batch returns
-        },
-    }
-
     persis_info = add_unique_random_streams({}, nworkers + 1)
     exit_criteria = {"sim_max": 20}
 
@@ -122,9 +115,7 @@
         persis_info = add_unique_random_streams({}, nworkers + 1)
 
         # Perform the run
-        H, _, flag = libE(
-            sim_specs, gen_specs, exit_criteria, persis_info, libE_specs=libE_specs, alloc_specs=alloc_specs
-        )
+        H, _, flag = libE(sim_specs, gen_specs, exit_criteria, persis_info, libE_specs=libE_specs)
 
     del libE_specs["resource_info"]  # this would override
 
@@ -159,9 +150,7 @@
         persis_info = add_unique_random_streams({}, nworkers + 1)
 
         # Perform the run
-        H, _, flag = libE(
-            sim_specs, gen_specs, exit_criteria, persis_info, libE_specs=libE_specs, alloc_specs=alloc_specs
-        )
+        H, _, flag = libE(sim_specs, gen_specs, exit_criteria, persis_info, libE_specs=libE_specs)
 
     del libE_specs["platform_specs"]
 
@@ -196,9 +185,7 @@
         persis_info = add_unique_random_streams({}, nworkers + 1)
 
         # Perform the run
-        H, _, flag = libE(
-            sim_specs, gen_specs, exit_criteria, persis_info, libE_specs=libE_specs, alloc_specs=alloc_specs
-        )
+        H, _, flag = libE(sim_specs, gen_specs, exit_criteria, persis_info, libE_specs=libE_specs)
 
     del libE_specs["platform_specs"]
 
@@ -214,9 +201,7 @@
         persis_info = add_unique_random_streams({}, nworkers + 1)
 
         # Perform the run
-        H, _, flag = libE(
-            sim_specs, gen_specs, exit_criteria, persis_info, libE_specs=libE_specs, alloc_specs=alloc_specs
-        )
+        H, _, flag = libE(sim_specs, gen_specs, exit_criteria, persis_info, libE_specs=libE_specs)
 
         del libE_specs["platform"]
 
@@ -232,9 +217,7 @@
         persis_info = add_unique_random_streams({}, nworkers + 1)
 
         # Perform the run
-        H, _, flag = libE(
-            sim_specs, gen_specs, exit_criteria, persis_info, libE_specs=libE_specs, alloc_specs=alloc_specs
-        )
+        H, _, flag = libE(sim_specs, gen_specs, exit_criteria, persis_info, libE_specs=libE_specs)
 
         del os.environ["LIBE_PLATFORM"]
 
@@ -250,9 +233,7 @@
         persis_info = add_unique_random_streams({}, nworkers + 1)
 
         # Perform the run
-        H, _, flag = libE(
-            sim_specs, gen_specs, exit_criteria, persis_info, libE_specs=libE_specs, alloc_specs=alloc_specs
-        )
+        H, _, flag = libE(sim_specs, gen_specs, exit_criteria, persis_info, libE_specs=libE_specs)
 
         del libE_specs["platform_specs"]
 
diff --git a/libensemble/tests/functionality_tests/test_mpi_gpu_settings_env.py b/libensemble/tests/functionality_tests/test_mpi_gpu_settings_env.py
index 814f5086cb..30c737cbfe 100644
--- a/libensemble/tests/functionality_tests/test_mpi_gpu_settings_env.py
+++ b/libensemble/tests/functionality_tests/test_mpi_gpu_settings_env.py
@@ -26,7 +26,6 @@
 
 import numpy as np
 
-from libensemble.alloc_funcs.start_only_persistent import only_persistent_gens as alloc_f
 from libensemble.executors.mpi_executor import MPIExecutor
 from libensemble.gen_funcs.persistent_sampling_var_resources import uniform_sample as gen_f
 
@@ -69,22 +68,16 @@
         "gen_f": gen_f,
         "persis_in": ["f", "x", "sim_id"],
         "out": [("priority", float), ("resource_sets", int), ("x", float, n)],
+        "initial_batch_size": nworkers - 1,
+        "give_all_with_same_priority": False,
+        "async_return": False,
         "user": {
-            "initial_batch_size": nworkers - 1,
             "max_resource_sets": nworkers - 1,  # Any sim created can req. 1 worker up to all.
             "lb": np.array([-3, -2]),
             "ub": np.array([3, 2]),
         },
     }
 
-    alloc_specs = {
-        "alloc_f": alloc_f,
-        "user": {
-            "give_all_with_same_priority": False,
-            "async_return": False,  # False batch returns
-        },
-    }
-
     persis_info = add_unique_random_streams({}, nworkers + 1)
     exit_criteria = {"sim_max": 10}
 
@@ -98,4 +91,4 @@
     exctr.register_app(full_path=six_hump_camel_app, app_name="six_hump_camel")
 
     # Perform the run
-    H, _, flag = libE(sim_specs, gen_specs, exit_criteria, persis_info, libE_specs=libE_specs, alloc_specs=alloc_specs)
+    H, _, flag = libE(sim_specs, gen_specs, exit_criteria, persis_info, libE_specs=libE_specs)
diff --git a/libensemble/tests/functionality_tests/test_mpi_gpu_settings_mock_nodes_multi_task.py b/libensemble/tests/functionality_tests/test_mpi_gpu_settings_mock_nodes_multi_task.py
index 3c884c7dd2..1234c64821 100644
--- a/libensemble/tests/functionality_tests/test_mpi_gpu_settings_mock_nodes_multi_task.py
+++ b/libensemble/tests/functionality_tests/test_mpi_gpu_settings_mock_nodes_multi_task.py
@@ -28,7 +28,6 @@
 
 import numpy as np
 
-from libensemble.alloc_funcs.start_only_persistent import only_persistent_gens as alloc_f
 from libensemble.executors.mpi_executor import MPIExecutor
 from libensemble.gen_funcs.persistent_sampling_var_resources import uniform_sample_diff_simulations as gen_f
 
@@ -68,8 +67,10 @@
         "gen_f": gen_f,
         "persis_in": ["f", "x", "sim_id"],
         "out": [("priority", float), ("num_procs", int), ("num_gpus", int), ("x", float, n)],
+        "initial_batch_size": nsim_workers,
+        "give_all_with_same_priority": False,
+        "async_return": False,
         "user": {
-            "initial_batch_size": nsim_workers,
             "max_procs": max(nsim_workers // 2, 1),  # Any sim created can req. 1 worker up to max
             "lb": np.array([-3, -2]),
             "ub": np.array([3, 2]),
@@ -77,14 +78,6 @@
         },
     }
 
-    alloc_specs = {
-        "alloc_f": alloc_f,
-        "user": {
-            "give_all_with_same_priority": False,
-            "async_return": False,  # False batch returns
-        },
-    }
-
     persis_info = add_unique_random_streams({}, nworkers + 1)
     exit_criteria = {"sim_max": nsim_workers * 2}
 
@@ -109,9 +102,7 @@
         persis_info = add_unique_random_streams({}, nworkers + 1)
 
         # Perform the run
-        H, _, flag = libE(
-            sim_specs, gen_specs, exit_criteria, persis_info, libE_specs=libE_specs, alloc_specs=alloc_specs
-        )
+        H, _, flag = libE(sim_specs, gen_specs, exit_criteria, persis_info, libE_specs=libE_specs)
 
     # Oversubscribe procs
     if nsim_workers >= 4:
@@ -134,9 +125,7 @@
         persis_info = add_unique_random_streams({}, nworkers + 1)
 
         # Perform the run
-        H, _, flag = libE(
-            sim_specs, gen_specs, exit_criteria, persis_info, libE_specs=libE_specs, alloc_specs=alloc_specs
-        )
+        H, _, flag = libE(sim_specs, gen_specs, exit_criteria, persis_info, libE_specs=libE_specs)
 
     del libE_specs["resource_info"]
 
diff --git a/libensemble/tests/functionality_tests/test_mpi_runners.py b/libensemble/tests/functionality_tests/test_mpi_runners.py
index af00471d59..c7d1c88134 100644
--- a/libensemble/tests/functionality_tests/test_mpi_runners.py
+++ b/libensemble/tests/functionality_tests/test_mpi_runners.py
@@ -12,6 +12,7 @@
 import numpy as np
 
 from libensemble import logger
+from libensemble.alloc_funcs.give_sim_work_first import give_sim_work_first
 from libensemble.executors.mpi_executor import MPIExecutor
 from libensemble.gen_funcs.sampling import uniform_random_sample as gen_f
 from libensemble.libE import libE
@@ -73,10 +74,10 @@
         "gen_f": gen_f,
         "in": ["sim_id"],
         "out": [("x", float, (2,))],
+        "batch_size": 100,
         "user": {
             "lb": np.array([-3, -2]),
             "ub": np.array([3, 2]),
-            "gen_batch_size": 100,
         },
     }
 
@@ -233,8 +234,10 @@ def run_tests(mpi_runner, runner_name, test_list_exargs, exp_list):
             "tests": test_list,
         }
 
+        alloc_specs = {"alloc_f": give_sim_work_first}
+
         # Perform the run
-        H, pinfo, flag = libE(sim_specs, gen_specs, exit_criteria, persis_info, libE_specs=libE_specs)
+        H, pinfo, flag = libE(sim_specs, gen_specs, exit_criteria, persis_info, alloc_specs, libE_specs=libE_specs)
 
     # for run_set in ['mpich', 'openmpi', 'aprun', 'srun', 'jsrun', 'rename_mpich', 'custom']:
     for run_set in ["mpich", "aprun", "srun", "jsrun", "rename_mpich", "custom"]:
diff --git a/libensemble/tests/functionality_tests/test_mpi_runners_subnode.py b/libensemble/tests/functionality_tests/test_mpi_runners_subnode.py
index 7266678ff2..73d283e9b1 100644
--- a/libensemble/tests/functionality_tests/test_mpi_runners_subnode.py
+++ b/libensemble/tests/functionality_tests/test_mpi_runners_subnode.py
@@ -16,6 +16,7 @@
 import numpy as np
 
 from libensemble import logger
+from libensemble.alloc_funcs.give_sim_work_first import give_sim_work_first
 from libensemble.executors.mpi_executor import MPIExecutor
 from libensemble.gen_funcs.sampling import uniform_random_sample as gen_f
 from libensemble.libE import libE
@@ -84,13 +85,15 @@
         "gen_f": gen_f,
         "in": [],
         "out": [("x", float, (n,))],
+        "batch_size": 20,
         "user": {
-            "gen_batch_size": 20,
             "lb": np.array([-3, -2]),
             "ub": np.array([3, 2]),
         },
     }
 
+    alloc_specs = {"alloc_f": give_sim_work_first}
+
     persis_info = add_unique_random_streams({}, nworkers + 1)
     exit_criteria = {"sim_max": (nsim_workers) * rounds}
 
@@ -118,6 +121,6 @@
     }
 
     # Perform the run
-    H, persis_info, flag = libE(sim_specs, gen_specs, exit_criteria, persis_info, libE_specs=libE_specs)
+    H, persis_info, flag = libE(sim_specs, gen_specs, exit_criteria, persis_info, alloc_specs, libE_specs=libE_specs)
 
     # All asserts are in sim func
diff --git a/libensemble/tests/functionality_tests/test_mpi_runners_subnode_uneven.py b/libensemble/tests/functionality_tests/test_mpi_runners_subnode_uneven.py
index a5145965b9..26844bcc1d 100644
--- a/libensemble/tests/functionality_tests/test_mpi_runners_subnode_uneven.py
+++ b/libensemble/tests/functionality_tests/test_mpi_runners_subnode_uneven.py
@@ -14,6 +14,7 @@
 import numpy as np
 
 from libensemble import logger
+from libensemble.alloc_funcs.give_sim_work_first import give_sim_work_first
 from libensemble.executors.mpi_executor import MPIExecutor
 from libensemble.gen_funcs.sampling import uniform_random_sample as gen_f
 from libensemble.libE import libE
@@ -85,13 +86,15 @@
         "gen_f": gen_f,
         "in": [],
         "out": [("x", float, (n,))],
+        "batch_size": 20,
         "user": {
-            "gen_batch_size": 20,
             "lb": np.array([-3, -2]),
             "ub": np.array([3, 2]),
         },
     }
 
+    alloc_specs = {"alloc_f": give_sim_work_first}
+
     persis_info = add_unique_random_streams({}, nworkers + 1)
     exit_criteria = {"sim_max": (nsim_workers) * rounds}
 
@@ -137,6 +140,6 @@
     }
 
     # Perform the run
-    H, persis_info, flag = libE(sim_specs, gen_specs, exit_criteria, persis_info, libE_specs=libE_specs)
+    H, persis_info, flag = libE(sim_specs, gen_specs, exit_criteria, persis_info, alloc_specs, libE_specs=libE_specs)
 
     # All asserts are in sim func
diff --git a/libensemble/tests/functionality_tests/test_mpi_runners_supernode_uneven.py b/libensemble/tests/functionality_tests/test_mpi_runners_supernode_uneven.py
index 77975e200d..14047d0cb3 100644
--- a/libensemble/tests/functionality_tests/test_mpi_runners_supernode_uneven.py
+++ b/libensemble/tests/functionality_tests/test_mpi_runners_supernode_uneven.py
@@ -11,6 +11,7 @@
 import numpy as np
 
 from libensemble import logger
+from libensemble.alloc_funcs.give_sim_work_first import give_sim_work_first
 from libensemble.executors.mpi_executor import MPIExecutor
 from libensemble.gen_funcs.sampling import uniform_random_sample as gen_f
 from libensemble.libE import libE
@@ -75,8 +76,8 @@
         "gen_f": gen_f,
         "in": [],
         "out": [("x", float, (n,))],
+        "batch_size": 20,
         "user": {
-            "gen_batch_size": 20,
             "lb": np.array([-3, -2]),
             "ub": np.array([3, 2]),
         },
@@ -131,7 +132,9 @@
         "expect": exp_list,
     }
 
+    alloc_specs = {"alloc_f": give_sim_work_first}
+
     # Perform the run
-    H, persis_info, flag = libE(sim_specs, gen_specs, exit_criteria, persis_info, libE_specs=libE_specs)
+    H, persis_info, flag = libE(sim_specs, gen_specs, exit_criteria, persis_info, alloc_specs, libE_specs=libE_specs)
 
     # All asserts are in sim func
diff --git a/libensemble/tests/functionality_tests/test_mpi_runners_zrw_subnode_uneven.py b/libensemble/tests/functionality_tests/test_mpi_runners_zrw_subnode_uneven.py
index cc73d0e427..aa2a1a8ebe 100644
--- a/libensemble/tests/functionality_tests/test_mpi_runners_zrw_subnode_uneven.py
+++ b/libensemble/tests/functionality_tests/test_mpi_runners_zrw_subnode_uneven.py
@@ -21,7 +21,6 @@
 import numpy as np
 
 from libensemble import logger
-from libensemble.alloc_funcs.start_only_persistent import only_persistent_gens as alloc_f
 from libensemble.executors.mpi_executor import MPIExecutor
 from libensemble.gen_funcs.persistent_sampling import persistent_uniform as gen_f
 from libensemble.libE import libE
@@ -100,7 +99,6 @@
         },
     }
 
-    alloc_specs = {"alloc_f": alloc_f}
     exit_criteria = {"sim_max": (nsim_workers) * rounds}
 
     test_list_base = [
@@ -161,5 +159,5 @@
             persis_info = add_unique_random_streams({}, nworkers + 1)
 
         # Perform the run
-        H, persis_info, flag = libE(sim_specs, gen_specs, exit_criteria, persis_info, alloc_specs, libE_specs)
+        H, persis_info, flag = libE(sim_specs, gen_specs, exit_criteria, persis_info, libE_specs=libE_specs)
         # Run-line asserts are in sim func
diff --git a/libensemble/tests/functionality_tests/test_mpi_runners_zrw_supernode_uneven.py b/libensemble/tests/functionality_tests/test_mpi_runners_zrw_supernode_uneven.py
index 640d613bff..f52aced21c 100644
--- a/libensemble/tests/functionality_tests/test_mpi_runners_zrw_supernode_uneven.py
+++ b/libensemble/tests/functionality_tests/test_mpi_runners_zrw_supernode_uneven.py
@@ -11,7 +11,6 @@
 import numpy as np
 
 from libensemble import logger
-from libensemble.alloc_funcs.start_only_persistent import only_persistent_gens as alloc_f
 from libensemble.executors.mpi_executor import MPIExecutor
 from libensemble.gen_funcs.persistent_sampling import persistent_uniform as gen_f
 from libensemble.libE import libE
@@ -86,7 +85,6 @@
         },
     }
 
-    alloc_specs = {"alloc_f": alloc_f}
     persis_info = add_unique_random_streams({}, nworkers + 1)
     exit_criteria = {"sim_max": (nsim_workers) * rounds}
 
@@ -139,6 +137,6 @@
     }
 
     # Perform the run
-    H, persis_info, flag = libE(sim_specs, gen_specs, exit_criteria, persis_info, alloc_specs, libE_specs)
+    H, persis_info, flag = libE(sim_specs, gen_specs, exit_criteria, persis_info, libE_specs=libE_specs)
 
     # All asserts are in sim func
diff --git a/libensemble/tests/functionality_tests/test_mpi_warning.py b/libensemble/tests/functionality_tests/test_mpi_warning.py
index daf6125b62..1436e81a02 100644
--- a/libensemble/tests/functionality_tests/test_mpi_warning.py
+++ b/libensemble/tests/functionality_tests/test_mpi_warning.py
@@ -17,11 +17,12 @@
 import numpy as np
 
 from libensemble import Ensemble, logger
+from libensemble.alloc_funcs.give_sim_work_first import give_sim_work_first
 from libensemble.gen_funcs.sampling import latin_hypercube_sample as gen_f
 
 # Import libEnsemble items for this test
 from libensemble.sim_funcs.simple_sim import norm_eval as sim_f
-from libensemble.specs import ExitCriteria, GenSpecs, SimSpecs
+from libensemble.specs import AllocSpecs, ExitCriteria, GenSpecs, SimSpecs
 
 # Main block is necessary only when using local comms with spawn start method (default on macOS and Windows).
 if __name__ == "__main__":
@@ -35,12 +36,13 @@
     sampling.gen_specs = GenSpecs(
         gen_f=gen_f,
         outputs=[("x", float, 2)],
+        batch_size=100,
         user={
-            "gen_batch_size": 100,
             "lb": np.array([-3, -2]),
             "ub": np.array([3, 2]),
         },
     )
+    sampling.alloc_specs = AllocSpecs(alloc_f=give_sim_work_first)
 
     sampling.exit_criteria = ExitCriteria(sim_max=100)
     sampling.add_random_streams()
diff --git a/libensemble/tests/functionality_tests/test_new_field.py b/libensemble/tests/functionality_tests/test_new_field.py
index c130b1d6e3..bc5dd4d554 100644
--- a/libensemble/tests/functionality_tests/test_new_field.py
+++ b/libensemble/tests/functionality_tests/test_new_field.py
@@ -15,6 +15,7 @@
 
 import numpy as np
 
+from libensemble.alloc_funcs.give_sim_work_first import give_sim_work_first
 from libensemble.gen_funcs.sampling import latin_hypercube_sample as gen_f
 
 # Import libEnsemble items for this test
@@ -41,18 +42,24 @@ def sim_f(In):
     gen_specs = {
         "gen_f": gen_f,
         "out": [("x", float, (1,))],
+        "batch_size": 500,
         "user": {
-            "gen_batch_size": 500,
             "lb": np.array([-3]),
             "ub": np.array([3]),
         },
     }
 
+    alloc_specs = {
+        "alloc_f": give_sim_work_first,
+    }
+
     persis_info = add_unique_random_streams({}, nworkers + 1, seed=1234)
 
     exit_criteria = {"gen_max": 501}
 
-    H, persis_info, flag = libE(sim_specs, gen_specs, exit_criteria, persis_info, libE_specs=libE_specs)
+    H, persis_info, flag = libE(
+        sim_specs, gen_specs, exit_criteria, persis_info, alloc_specs=alloc_specs, libE_specs=libE_specs
+    )
 
     if is_manager:
         assert len(H) >= 501
diff --git a/libensemble/tests/functionality_tests/test_persistent_sampling_CUDA_variable_resources.py b/libensemble/tests/functionality_tests/test_persistent_sampling_CUDA_variable_resources.py
index 327cff0d7d..d80818920a 100644
--- a/libensemble/tests/functionality_tests/test_persistent_sampling_CUDA_variable_resources.py
+++ b/libensemble/tests/functionality_tests/test_persistent_sampling_CUDA_variable_resources.py
@@ -17,7 +17,6 @@
 
 import numpy as np
 
-from libensemble.alloc_funcs.start_only_persistent import only_persistent_gens as alloc_f
 from libensemble.executors.mpi_executor import MPIExecutor
 from libensemble.gen_funcs.persistent_sampling_var_resources import uniform_sample as gen_f
 
@@ -62,22 +61,16 @@
         "gen_f": gen_f,
         "persis_in": ["f", "x", "sim_id"],
         "out": [("resource_sets", int), ("x", float, n)],
+        "initial_batch_size": nworkers - 1,
+        "give_all_with_same_priority": False,
+        "async_return": True,
         "user": {
-            "initial_batch_size": nworkers - 1,
             "max_resource_sets": nworkers - 1,  # Any sim created can req. 1 worker up to all.
             "lb": np.array([-3, -2]),
             "ub": np.array([3, 2]),
         },
     }
 
-    alloc_specs = {
-        "alloc_f": alloc_f,
-        "user": {
-            "give_all_with_same_priority": False,
-            "async_return": True,
-        },
-    }
-
     libE_specs["scheduler_opts"] = {"match_slots": True}
     persis_info = add_unique_random_streams({}, nworkers + 1)
     exit_criteria = {"sim_max": 40, "wallclock_max": 300}
@@ -87,9 +80,7 @@
     for i in range(2):
         persis_info = add_unique_random_streams({}, nworkers + 1)
         libE_specs["workflow_dir_path"] = libE_specs["workflow_dir_path"][:-1] + str(i)
-        H, persis_info, flag = libE(
-            sim_specs, gen_specs, exit_criteria, persis_info, libE_specs=libE_specs, alloc_specs=alloc_specs
-        )
+        H, persis_info, flag = libE(sim_specs, gen_specs, exit_criteria, persis_info, libE_specs=libE_specs)
 
     if is_manager:
         assert flag == 0
diff --git a/libensemble/tests/functionality_tests/test_persistent_sim_uniform_sampling.py b/libensemble/tests/functionality_tests/test_persistent_sim_uniform_sampling.py
index f1f0616663..af2a7ac075 100644
--- a/libensemble/tests/functionality_tests/test_persistent_sim_uniform_sampling.py
+++ b/libensemble/tests/functionality_tests/test_persistent_sim_uniform_sampling.py
@@ -21,7 +21,6 @@
 
 import numpy as np
 
-from libensemble.alloc_funcs.start_only_persistent import only_persistent_gens as alloc_f
 from libensemble.gen_funcs.persistent_sampling import persistent_uniform as gen_f
 
 # Import libEnsemble items for this test
@@ -57,21 +56,20 @@
         "in": [],
         "persis_in": ["sim_id", "f", "grad"],
         "out": [("x", float, (n,))],
+        "initial_batch_size": 5,
+        "alt_type": True,
         "user": {
-            "initial_batch_size": 5,
             "lb": np.array([-3, -2]),
             "ub": np.array([3, 2]),
         },
     }
 
-    alloc_specs = {"alloc_f": alloc_f, "user": {"alt_type": True}}
-
     persis_info = add_unique_random_streams({}, nworkers + 1)
 
     exit_criteria = {"sim_max": 40, "wallclock_max": 300}
 
     # Perform the run
-    H, persis_info, flag = libE(sim_specs, gen_specs, exit_criteria, persis_info, alloc_specs, libE_specs)
+    H, persis_info, flag = libE(sim_specs, gen_specs, exit_criteria, persis_info, libE_specs=libE_specs)
 
     if is_manager:
         assert len(np.unique(H["gen_ended_time"])) == 8
diff --git a/libensemble/tests/functionality_tests/test_persistent_uniform_gen_decides_stop.py b/libensemble/tests/functionality_tests/test_persistent_uniform_gen_decides_stop.py
index d9b9465080..d9e8594f2e 100644
--- a/libensemble/tests/functionality_tests/test_persistent_uniform_gen_decides_stop.py
+++ b/libensemble/tests/functionality_tests/test_persistent_uniform_gen_decides_stop.py
@@ -20,7 +20,6 @@
 
 import numpy as np
 
-from libensemble.alloc_funcs.start_only_persistent import only_persistent_gens as alloc_f
 from libensemble.gen_funcs.persistent_sampling import persistent_request_shutdown as gen_f
 
 # Import libEnsemble items for this test
@@ -50,28 +49,22 @@
             "gen_f": gen_f,
             "persis_in": ["f", "x", "sim_id"],
             "out": [("x", float, (n,))],
+            "initial_batch_size": init_batch_size,
+            "async_return": True,
+            "num_active_gens": ngens,
             "user": {
-                "initial_batch_size": init_batch_size,
                 "shutdown_limit": 10,  # Iterations on a gen before it triggers a shutdown.
                 "lb": np.array([-3, -2]),
                 "ub": np.array([3, 2]),
             },
         }
 
-        alloc_specs = {
-            "alloc_f": alloc_f,
-            "user": {
-                "async_return": True,
-                "num_active_gens": ngens,
-            },
-        }
-
         persis_info = add_unique_random_streams({}, nworkers + 1)
 
         exit_criteria = {"gen_max": 50, "wallclock_max": 300}
 
         # Perform the run
-        H, persis_info, flag = libE(sim_specs, gen_specs, exit_criteria, persis_info, alloc_specs, libE_specs)
+        H, persis_info, flag = libE(sim_specs, gen_specs, exit_criteria, persis_info, libE_specs=libE_specs)
 
         if is_manager:
             [ended_times, counts] = np.unique(H["gen_ended_time"], return_counts=True)
diff --git a/libensemble/tests/functionality_tests/test_persistent_uniform_sampling.py b/libensemble/tests/functionality_tests/test_persistent_uniform_sampling.py
index 81a18a5285..50c9fd9ce4 100644
--- a/libensemble/tests/functionality_tests/test_persistent_uniform_sampling.py
+++ b/libensemble/tests/functionality_tests/test_persistent_uniform_sampling.py
@@ -20,7 +20,6 @@
 
 import numpy as np
 
-from libensemble.alloc_funcs.start_only_persistent import only_persistent_gens as alloc_f
 from libensemble.gen_funcs.persistent_sampling import batched_history_matching as gen_f2
 from libensemble.gen_funcs.persistent_sampling import persistent_uniform as gen_f1
 
@@ -56,8 +55,6 @@
         },
     }
 
-    alloc_specs = {"alloc_f": alloc_f}
-
     exit_criteria = {"gen_max": num_batches * batch, "wallclock_max": 300}
 
     libE_specs["kill_canceled_sims"] = False
@@ -93,7 +90,7 @@
             libE_specs["gen_workers"] = [2]
 
         # Perform the run
-        H, persis_info, flag = libE(sim_specs, gen_specs, exit_criteria, persis_info, alloc_specs, libE_specs)
+        H, persis_info, flag = libE(sim_specs, gen_specs, exit_criteria, persis_info, libE_specs=libE_specs)
 
         if is_manager:
             assert len(np.unique(H["gen_ended_time"])) == num_batches
diff --git a/libensemble/tests/functionality_tests/test_persistent_uniform_sampling_async.py b/libensemble/tests/functionality_tests/test_persistent_uniform_sampling_async.py
index 77d9a6a7b8..3c3d41c6ec 100644
--- a/libensemble/tests/functionality_tests/test_persistent_uniform_sampling_async.py
+++ b/libensemble/tests/functionality_tests/test_persistent_uniform_sampling_async.py
@@ -20,7 +20,6 @@
 
 import numpy as np
 
-from libensemble.alloc_funcs.start_only_persistent import only_persistent_gens as alloc_f
 from libensemble.gen_funcs.persistent_sampling import persistent_uniform as gen_f
 
 # Import libEnsemble items for this test
@@ -47,24 +46,20 @@
         "gen_f": gen_f,
         "persis_in": ["f", "x", "sim_id"],
         "out": [("x", float, (n,))],
+        "initial_batch_size": nworkers,
+        "async_return": True,
         "user": {
-            "initial_batch_size": nworkers,  # Ensure > 1 alloc to send all sims
             "lb": np.array([-3, -2]),
             "ub": np.array([3, 2]),
         },
     }
 
-    alloc_specs = {
-        "alloc_f": alloc_f,
-        "user": {"async_return": True},
-    }
-
     persis_info = add_unique_random_streams({}, nworkers + 1)
 
     exit_criteria = {"gen_max": 100, "wallclock_max": 300}
 
     # Perform the run
-    H, persis_info, flag = libE(sim_specs, gen_specs, exit_criteria, persis_info, alloc_specs, libE_specs)
+    H, persis_info, flag = libE(sim_specs, gen_specs, exit_criteria, persis_info, libE_specs=libE_specs)
 
     if is_manager:
         [_, counts] = np.unique(H["gen_ended_time"], return_counts=True)
diff --git a/libensemble/tests/functionality_tests/test_persistent_uniform_sampling_cancel.py b/libensemble/tests/functionality_tests/test_persistent_uniform_sampling_cancel.py
index 15c2d5b097..4eec437c3f 100644
--- a/libensemble/tests/functionality_tests/test_persistent_uniform_sampling_cancel.py
+++ b/libensemble/tests/functionality_tests/test_persistent_uniform_sampling_cancel.py
@@ -20,7 +20,6 @@
 
 import numpy as np
 
-from libensemble.alloc_funcs.start_only_persistent import only_persistent_gens as alloc_f
 from libensemble.gen_funcs.persistent_sampling import persistent_uniform_with_cancellations as gen_f
 
 # Import libEnsemble items for this test
@@ -47,24 +46,20 @@
         "gen_f": gen_f,
         "persis_in": ["x", "f", "grad", "sim_id"],
         "out": [("x", float, (n,))],
+        "initial_batch_size": 100,
+        "async_return": True,
         "user": {
-            "initial_batch_size": 100,
             "lb": np.array([-3, -2]),
             "ub": np.array([3, 2]),
         },
     }
 
-    alloc_specs = {
-        "alloc_f": alloc_f,
-        "user": {"async_return": True},
-    }
-
     exit_criteria = {"gen_max": 150, "wallclock_max": 300}
 
     persis_info = add_unique_random_streams({}, nworkers + 1)
 
     # Perform the run
-    H, persis_info, flag = libE(sim_specs, gen_specs, exit_criteria, persis_info, alloc_specs, libE_specs)
+    H, persis_info, flag = libE(sim_specs, gen_specs, exit_criteria, persis_info, libE_specs=libE_specs)
 
     if is_manager:
         # For reproducible test, only tests if cancel requested on points - not whether got evaluated
diff --git a/libensemble/tests/functionality_tests/test_persistent_uniform_sampling_nonblocking.py b/libensemble/tests/functionality_tests/test_persistent_uniform_sampling_nonblocking.py
index 5425578849..c9e92a6c4f 100644
--- a/libensemble/tests/functionality_tests/test_persistent_uniform_sampling_nonblocking.py
+++ b/libensemble/tests/functionality_tests/test_persistent_uniform_sampling_nonblocking.py
@@ -20,7 +20,6 @@
 
 import numpy as np
 
-from libensemble.alloc_funcs.start_only_persistent import only_persistent_gens as alloc_f
 from libensemble.gen_funcs.persistent_sampling import uniform_nonblocking as gen_f
 
 # Import libEnsemble items for this test
@@ -53,8 +52,6 @@
         },
     }
 
-    alloc_specs = {"alloc_f": alloc_f}
-
     persis_info = add_unique_random_streams({}, nworkers + 1)
     for i in persis_info:
         persis_info[i]["get_grad"] = True
@@ -62,7 +59,7 @@
     exit_criteria = {"gen_max": 40, "wallclock_max": 300}
 
     # Perform the run
-    H, persis_info, flag = libE(sim_specs, gen_specs, exit_criteria, persis_info, alloc_specs, libE_specs)
+    H, persis_info, flag = libE(sim_specs, gen_specs, exit_criteria, persis_info, libE_specs=libE_specs)
 
     if is_manager:
         assert len(np.unique(H["gen_ended_time"])) == 2
diff --git a/libensemble/tests/functionality_tests/test_persistent_uniform_sampling_running_mean.py b/libensemble/tests/functionality_tests/test_persistent_uniform_sampling_running_mean.py
index 9cc92dadd3..9c915c82a4 100644
--- a/libensemble/tests/functionality_tests/test_persistent_uniform_sampling_running_mean.py
+++ b/libensemble/tests/functionality_tests/test_persistent_uniform_sampling_running_mean.py
@@ -20,7 +20,6 @@
 
 import numpy as np
 
-from libensemble.alloc_funcs.start_only_persistent import only_persistent_gens as alloc_f
 from libensemble.gen_funcs.persistent_sampling import persistent_uniform_final_update as gen_f
 from libensemble.libE import libE
 from libensemble.sim_funcs.six_hump_camel import six_hump_camel_simple as sim_f
@@ -57,8 +56,6 @@
         },
     }
 
-    alloc_specs = {"alloc_f": alloc_f}
-
     sim_max = 120
     exit_criteria = {"sim_max": sim_max}
     libE_specs["final_gen_send"] = True
@@ -72,7 +69,7 @@
             }
 
         persis_info = add_unique_random_streams({}, nworkers + 1)
-        H, persis_info, flag = libE(sim_specs, gen_specs, exit_criteria, persis_info, alloc_specs, libE_specs)
+        H, persis_info, flag = libE(sim_specs, gen_specs, exit_criteria, persis_info, libE_specs=libE_specs)
 
         if is_manager:
             # Check that last saved history agrees with returned history.
diff --git a/libensemble/tests/functionality_tests/test_runlines_adaptive_workers.py b/libensemble/tests/functionality_tests/test_runlines_adaptive_workers.py
index 34dbb02224..cbff4e2792 100644
--- a/libensemble/tests/functionality_tests/test_runlines_adaptive_workers.py
+++ b/libensemble/tests/functionality_tests/test_runlines_adaptive_workers.py
@@ -51,8 +51,11 @@
         "gen_f": gen_f,
         "in": ["sim_id"],
         "out": [("priority", float), ("resource_sets", int), ("x", float, n), ("x_on_cube", float, n)],
+        "batch_mode": False,
+        "give_all_with_same_priority": True,
+        "num_active_gens": 1,
+        "initial_batch_size": 5,
         "user": {
-            "initial_batch_size": 5,
             "max_resource_sets": 4,
             "lb": np.array([-3, -2]),
             "ub": np.array([3, 2]),
@@ -61,11 +64,6 @@
 
     alloc_specs = {
         "alloc_f": give_sim_work_first,
-        "user": {
-            "batch_mode": False,
-            "give_all_with_same_priority": True,
-            "num_active_gens": 1,
-        },
     }
 
     comms = libE_specs["comms"]
diff --git a/libensemble/tests/functionality_tests/test_runlines_adaptive_workers_persistent.py b/libensemble/tests/functionality_tests/test_runlines_adaptive_workers_persistent.py
index ab5aa144de..8f80ddb67d 100644
--- a/libensemble/tests/functionality_tests/test_runlines_adaptive_workers_persistent.py
+++ b/libensemble/tests/functionality_tests/test_runlines_adaptive_workers_persistent.py
@@ -17,7 +17,6 @@
 
 import numpy as np
 
-from libensemble.alloc_funcs.start_only_persistent import only_persistent_gens as alloc_f
 from libensemble.executors.mpi_executor import MPIExecutor
 from libensemble.gen_funcs.persistent_sampling_var_resources import uniform_sample_with_var_priorities as gen_f
 
@@ -61,19 +60,15 @@
         "gen_f": gen_f,
         "persis_in": ["x", "f", "sim_id"],
         "out": [("priority", float), ("resource_sets", int), ("x", float, n), ("x_on_cube", float, n)],
+        "initial_batch_size": nworkers - 1,
+        "give_all_with_same_priority": False,
         "user": {
-            "initial_batch_size": nworkers - 1,
             "max_resource_sets": max_rsets,
             "lb": np.array([-3, -2]),
             "ub": np.array([3, 2]),
         },
     }
 
-    alloc_specs = {
-        "alloc_f": alloc_f,
-        "user": {"give_all_with_same_priority": False},
-    }
-
     comms = libE_specs["comms"]
     node_file = "nodelist_adaptive_workers_persistent_comms_" + str(comms) + "_wrks_" + str(nworkers)
     if is_manager:
@@ -91,9 +86,7 @@
     exit_criteria = {"sim_max": 40, "wallclock_max": 300}
 
     # Perform the run
-    H, persis_info, flag = libE(
-        sim_specs, gen_specs, exit_criteria, persis_info, libE_specs=libE_specs, alloc_specs=alloc_specs
-    )
+    H, persis_info, flag = libE(sim_specs, gen_specs, exit_criteria, persis_info, libE_specs=libE_specs)
 
     if is_manager:
         assert flag == 0
diff --git a/libensemble/tests/functionality_tests/test_runlines_adaptive_workers_persistent_oversubscribe_rsets.py b/libensemble/tests/functionality_tests/test_runlines_adaptive_workers_persistent_oversubscribe_rsets.py
index fb730b966b..a317d90433 100644
--- a/libensemble/tests/functionality_tests/test_runlines_adaptive_workers_persistent_oversubscribe_rsets.py
+++ b/libensemble/tests/functionality_tests/test_runlines_adaptive_workers_persistent_oversubscribe_rsets.py
@@ -17,7 +17,6 @@
 
 import numpy as np
 
-from libensemble.alloc_funcs.start_only_persistent import only_persistent_gens as alloc_f
 from libensemble.executors.mpi_executor import MPIExecutor
 from libensemble.gen_funcs.persistent_sampling_var_resources import uniform_sample_with_var_priorities as gen_f
 
@@ -63,19 +62,15 @@
         "gen_f": gen_f,
         "persis_in": ["f", "x", "sim_id"],
         "out": [("priority", float), ("resource_sets", int), ("x", float, n), ("x_on_cube", float, n)],
+        "initial_batch_size": nworkers - 1,
+        "give_all_with_same_priority": False,
         "user": {
-            "initial_batch_size": nworkers - 1,
             "max_resource_sets": max_rsets,
             "lb": np.array([-3, -2]),
             "ub": np.array([3, 2]),
         },
     }
 
-    alloc_specs = {
-        "alloc_f": alloc_f,
-        "user": {"give_all_with_same_priority": False},
-    }
-
     # comms = libE_specs["disable_resource_manager"] = True # SH TCP testing
 
     comms = libE_specs["comms"]
@@ -95,9 +90,7 @@
     exit_criteria = {"sim_max": 40, "wallclock_max": 300}
 
     # Perform the run
-    H, persis_info, flag = libE(
-        sim_specs, gen_specs, exit_criteria, persis_info, libE_specs=libE_specs, alloc_specs=alloc_specs
-    )
+    H, persis_info, flag = libE(sim_specs, gen_specs, exit_criteria, persis_info, libE_specs=libE_specs)
 
     if is_manager:
         assert flag == 0
diff --git a/libensemble/tests/functionality_tests/test_sim_dirs_per_calc.py b/libensemble/tests/functionality_tests/test_sim_dirs_per_calc.py
index b4c30f9d2d..793f0e98c8 100644
--- a/libensemble/tests/functionality_tests/test_sim_dirs_per_calc.py
+++ b/libensemble/tests/functionality_tests/test_sim_dirs_per_calc.py
@@ -18,6 +18,7 @@
 
 import numpy as np
 
+from libensemble.alloc_funcs.give_sim_work_first import give_sim_work_first
 from libensemble.gen_funcs.sampling import uniform_random_sample as gen_f
 from libensemble.libE import libE
 from libensemble.tests.regression_tests.support import write_sim_func as sim_f
@@ -54,18 +55,24 @@
     gen_specs = {
         "gen_f": gen_f,
         "out": [("x", float, (1,))],
+        "batch_size": 20,
         "user": {
-            "gen_batch_size": 20,
             "lb": np.array([-3]),
             "ub": np.array([3]),
         },
     }
 
+    alloc_specs = {
+        "alloc_f": give_sim_work_first,
+    }
+
     persis_info = add_unique_random_streams({}, nworkers + 1)
 
     exit_criteria = {"sim_max": 21}
 
-    H, persis_info, flag = libE(sim_specs, gen_specs, exit_criteria, persis_info, libE_specs=libE_specs)
+    H, persis_info, flag = libE(
+        sim_specs, gen_specs, exit_criteria, persis_info, alloc_specs=alloc_specs, libE_specs=libE_specs
+    )
 
     if is_manager:
         assert os.path.isdir(c_ensemble), f"Ensemble directory {c_ensemble} not created."
diff --git a/libensemble/tests/functionality_tests/test_sim_dirs_per_worker.py b/libensemble/tests/functionality_tests/test_sim_dirs_per_worker.py
index 69bb34ab84..59cbe15214 100644
--- a/libensemble/tests/functionality_tests/test_sim_dirs_per_worker.py
+++ b/libensemble/tests/functionality_tests/test_sim_dirs_per_worker.py
@@ -18,6 +18,7 @@
 
 import numpy as np
 
+from libensemble.alloc_funcs.give_sim_work_first import give_sim_work_first
 from libensemble.gen_funcs.sampling import uniform_random_sample as gen_f
 from libensemble.libE import libE
 from libensemble.tests.regression_tests.support import write_sim_func as sim_f
@@ -53,18 +54,24 @@
     gen_specs = {
         "gen_f": gen_f,
         "out": [("x", float, (1,))],
+        "batch_size": 20,
         "user": {
-            "gen_batch_size": 20,
             "lb": np.array([-3]),
             "ub": np.array([3]),
         },
     }
 
+    alloc_specs = {
+        "alloc_f": give_sim_work_first,
+    }
+
     persis_info = add_unique_random_streams({}, nworkers + 1)
 
     exit_criteria = {"sim_max": 21}
 
-    H, persis_info, flag = libE(sim_specs, gen_specs, exit_criteria, persis_info, libE_specs=libE_specs)
+    H, persis_info, flag = libE(
+        sim_specs, gen_specs, exit_criteria, persis_info, alloc_specs=alloc_specs, libE_specs=libE_specs
+    )
 
     if is_manager:
         assert os.path.isdir(w_ensemble), f"Ensemble directory {w_ensemble} not created."
diff --git a/libensemble/tests/functionality_tests/test_sim_dirs_with_exception.py b/libensemble/tests/functionality_tests/test_sim_dirs_with_exception.py
index 229f6d5f54..6e772cdba0 100644
--- a/libensemble/tests/functionality_tests/test_sim_dirs_with_exception.py
+++ b/libensemble/tests/functionality_tests/test_sim_dirs_with_exception.py
@@ -18,6 +18,7 @@
 
 import numpy as np
 
+from libensemble.alloc_funcs.give_sim_work_first import give_sim_work_first
 from libensemble.gen_funcs.sampling import uniform_random_sample as gen_f
 from libensemble.libE import libE
 from libensemble.manager import LoggedException
@@ -46,20 +47,26 @@
     gen_specs = {
         "gen_f": gen_f,
         "out": [("x", float, (1,))],
+        "batch_size": 20,
         "user": {
-            "gen_batch_size": 20,
             "lb": np.array([-3]),
             "ub": np.array([3]),
         },
     }
 
+    alloc_specs = {
+        "alloc_f": give_sim_work_first,
+    }
+
     persis_info = add_unique_random_streams({}, nworkers + 1)
 
     exit_criteria = {"sim_max": 21}
 
     return_flag = 1
     try:
-        H, persis_info, flag = libE(sim_specs, gen_specs, exit_criteria, persis_info, libE_specs=libE_specs)
+        H, persis_info, flag = libE(
+            sim_specs, gen_specs, exit_criteria, persis_info, alloc_specs, libE_specs=libE_specs
+        )
     except LoggedException as e:
         print(f"Caught deliberate exception: {e}")
         return_flag = 0
diff --git a/libensemble/tests/functionality_tests/test_sim_dirs_with_gen_dirs.py b/libensemble/tests/functionality_tests/test_sim_dirs_with_gen_dirs.py
index c73eeabadf..836a907909 100644
--- a/libensemble/tests/functionality_tests/test_sim_dirs_with_gen_dirs.py
+++ b/libensemble/tests/functionality_tests/test_sim_dirs_with_gen_dirs.py
@@ -18,6 +18,7 @@
 
 import numpy as np
 
+from libensemble.alloc_funcs.give_sim_work_first import give_sim_work_first
 from libensemble.libE import libE
 from libensemble.tests.regression_tests.support import write_sim_func as sim_f
 from libensemble.tests.regression_tests.support import write_uniform_gen_func as gen_f
@@ -65,8 +66,8 @@
     gen_specs = {
         "gen_f": gen_f,
         "out": [("x", float, (1,))],
+        "batch_size": 20,
         "user": {
-            "gen_batch_size": 20,
             "lb": np.array([-3]),
             "ub": np.array([3]),
         },
@@ -76,7 +77,13 @@
 
     exit_criteria = {"sim_max": 20}
 
-    H, persis_info, flag = libE(sim_specs, gen_specs, exit_criteria, persis_info, libE_specs=libE_specs)
+    alloc_specs = {
+        "alloc_f": give_sim_work_first,
+    }
+
+    H, persis_info, flag = libE(
+        sim_specs, gen_specs, exit_criteria, persis_info, alloc_specs=alloc_specs, libE_specs=libE_specs
+    )
 
     def check_copied(type):
         input_copied = []
diff --git a/libensemble/tests/functionality_tests/test_sim_input_dir_option.py b/libensemble/tests/functionality_tests/test_sim_input_dir_option.py
index 7dc4da7057..023bc98db5 100644
--- a/libensemble/tests/functionality_tests/test_sim_input_dir_option.py
+++ b/libensemble/tests/functionality_tests/test_sim_input_dir_option.py
@@ -18,6 +18,7 @@
 
 import numpy as np
 
+from libensemble.alloc_funcs.give_sim_work_first import give_sim_work_first
 from libensemble.gen_funcs.sampling import uniform_random_sample as gen_f
 from libensemble.libE import libE
 from libensemble.tests.regression_tests.support import write_sim_func as sim_f
@@ -49,8 +50,8 @@
     gen_specs = {
         "gen_f": gen_f,
         "out": [("x", float, (1,))],
+        "batch_size": 20,
         "user": {
-            "gen_batch_size": 20,
             "lb": np.array([-3]),
             "ub": np.array([3]),
         },
@@ -60,7 +61,13 @@
 
     exit_criteria = {"sim_max": 21}
 
-    H, persis_info, flag = libE(sim_specs, gen_specs, exit_criteria, persis_info, libE_specs=libE_specs)
+    alloc_specs = {
+        "alloc_f": give_sim_work_first,
+    }
+
+    H, persis_info, flag = libE(
+        sim_specs, gen_specs, exit_criteria, persis_info, alloc_specs=alloc_specs, libE_specs=libE_specs
+    )
 
     if is_manager:
         assert os.path.isdir(o_ensemble), f"Ensemble directory {o_ensemble} not created."
diff --git a/libensemble/tests/functionality_tests/test_stats_output.py b/libensemble/tests/functionality_tests/test_stats_output.py
index 58d012cdeb..b6377f8665 100644
--- a/libensemble/tests/functionality_tests/test_stats_output.py
+++ b/libensemble/tests/functionality_tests/test_stats_output.py
@@ -70,23 +70,19 @@
             ("x", float, n),
             ("x_on_cube", float, n),
         ],
+        "batch_mode": False,
+        "give_all_with_same_priority": True,
+        "num_active_gens": 1,
+        "async_return": True,
+        "batch_size": 5,
         "user": {
-            "gen_batch_size": 5,
             "max_resource_sets": nworkers,
             "lb": np.array([-3, -2]),
             "ub": np.array([3, 2]),
         },
     }
 
-    alloc_specs = {
-        "alloc_f": give_sim_work_first,
-        "user": {
-            "batch_mode": False,
-            "give_all_with_same_priority": True,
-            "num_active_gens": 1,
-            "async_return": True,
-        },
-    }
+    alloc_specs = {"alloc_f": give_sim_work_first}
 
     # This can improve scheduling when tasks may run across multiple nodes
     libE_specs["scheduler_opts"] = {"match_slots": False}
diff --git a/libensemble/tests/functionality_tests/test_uniform_sampling.py b/libensemble/tests/functionality_tests/test_uniform_sampling.py
index 2867f94df9..ea9ef4bbb2 100644
--- a/libensemble/tests/functionality_tests/test_uniform_sampling.py
+++ b/libensemble/tests/functionality_tests/test_uniform_sampling.py
@@ -19,6 +19,7 @@
 
 import numpy as np
 
+from libensemble.alloc_funcs.give_sim_work_first import give_sim_work_first
 from libensemble.gen_funcs.sampling import uniform_random_sample
 
 # Import libEnsemble items for this test
@@ -47,8 +48,8 @@
     gen_specs = {
         "gen_f": uniform_random_sample,  # Function generating sim_f input
         "out": [("x", float, (2,))],  # Tell libE gen_f output, type, size
+        "batch_size": 500,
         "user": {
-            "gen_batch_size": 500,  # Used by this specific gen_f
             "lb": np.array([-3, -2]),  # Used by this specific gen_f
             "ub": np.array([3, 2]),  # Used by this specific gen_f
         },
@@ -59,6 +60,10 @@
 
     exit_criteria = {"gen_max": 501, "wallclock_max": 300}
 
+    alloc_specs = {
+        "alloc_f": give_sim_work_first,
+    }
+
     for run in range(2):
         if run == 1:
             # Test running a mock sim using previous history file
@@ -67,7 +72,9 @@
             sim_specs["user"] = {"history_file": hfile}
 
         # Perform the run
-        H, persis_info, flag = libE(sim_specs, gen_specs, exit_criteria, persis_info, libE_specs=libE_specs)
+        H, persis_info, flag = libE(
+            sim_specs, gen_specs, exit_criteria, persis_info, alloc_specs, libE_specs=libE_specs
+        )
 
         if is_manager:
             assert flag == 0
diff --git a/libensemble/tests/functionality_tests/test_uniform_sampling_cancel.py b/libensemble/tests/functionality_tests/test_uniform_sampling_cancel.py
index 521b6e169d..855abfd44e 100644
--- a/libensemble/tests/functionality_tests/test_uniform_sampling_cancel.py
+++ b/libensemble/tests/functionality_tests/test_uniform_sampling_cancel.py
@@ -76,8 +76,10 @@ def create_H0(persis_info, gen_specs, sim_max):
     gen_specs = {
         "gen_f": uniform_random_sample_cancel,  # Function generating sim_f input
         "out": [("x", float, (2,)), ("cancel_requested", bool)],
+        "batch_size": 50,
+        "batch_mode": True,
+        "num_active_gens": 1,
         "user": {
-            "gen_batch_size": 50,  # Used by this specific gen_f
             "lb": np.array([-3, -2]),  # Used by this specific gen_f
             "ub": np.array([3, 2]),  # Used by this specific gen_f
         },
@@ -90,16 +92,11 @@ def create_H0(persis_info, gen_specs, sim_max):
 
     a_spec_1 = {
         "alloc_f": gswf,
-        "user": {
-            "batch_mode": True,
-            "num_active_gens": 1,
-        },
     }
 
     a_spec_2 = {
         "alloc_f": gswf,
         "user": {
-            "batch_mode": True,
             "num_active_gens": 2,
         },
     }
diff --git a/libensemble/tests/functionality_tests/test_uniform_sampling_one_residual_at_a_time.py b/libensemble/tests/functionality_tests/test_uniform_sampling_one_residual_at_a_time.py
index 6e96210db3..87093b1fff 100644
--- a/libensemble/tests/functionality_tests/test_uniform_sampling_one_residual_at_a_time.py
+++ b/libensemble/tests/functionality_tests/test_uniform_sampling_one_residual_at_a_time.py
@@ -57,8 +57,10 @@
         "gen_f": gen_f,
         "in": ["pt_id"],
         "out": [("x", float, n), ("priority", float), ("paused", bool), ("obj_component", int), ("pt_id", int)],
+        "batch_size": 2,
+        "batch_mode": True,  # Wait until all sim evals are done
+        "num_active_gens": 1,  # Only allow one active generator
         "user": {
-            "gen_batch_size": 2,
             "single_component_at_a_time": True,
             "combine_component_func": lambda x: np.sum(np.power(x, 2)),
             "lb": (-2 - np.pi / 10) * np.ones(n),
@@ -71,8 +73,6 @@
         "alloc_f": give_sim_work_first,  # Allocation function
         "user": {
             "stop_on_NaNs": True,  # Should alloc preempt evals
-            "batch_mode": True,  # Wait until all sim evals are done
-            "num_active_gens": 1,  # Only allow one active generator
             "stop_partial_fvec_eval": True,  # Should alloc preempt evals
         },
     }
diff --git a/libensemble/tests/functionality_tests/test_uniform_sampling_then_persistent_localopt_runs.py b/libensemble/tests/functionality_tests/test_uniform_sampling_then_persistent_localopt_runs.py
index ec126607ef..8a5bf14f3d 100644
--- a/libensemble/tests/functionality_tests/test_uniform_sampling_then_persistent_localopt_runs.py
+++ b/libensemble/tests/functionality_tests/test_uniform_sampling_then_persistent_localopt_runs.py
@@ -54,17 +54,19 @@
         "gen_f": gen_f,
         "persis_in": ["x", "f", "grad", "sim_id"],
         "out": gen_out,
+        "batch_size": 2,
+        "batch_mode": True,
+        "num_active_gens": 1,
         "user": {
             "xtol_rel": 1e-4,
             "lb": np.array([-3, -2]),
             "ub": np.array([3, 2]),
-            "gen_batch_size": 2,
             "localopt_method": "LD_MMA",
             "xtol_rel": 1e-4,
         },
     }
 
-    alloc_specs = {"alloc_f": alloc_f, "user": {"batch_mode": True, "num_active_gens": 1}}
+    alloc_specs = {"alloc_f": alloc_f}
 
     persis_info = add_unique_random_streams({}, nworkers + 1)
 
diff --git a/libensemble/tests/functionality_tests/test_uniform_sampling_with_variable_resources.py b/libensemble/tests/functionality_tests/test_uniform_sampling_with_variable_resources.py
index 9123f7db17..c895d12a8c 100644
--- a/libensemble/tests/functionality_tests/test_uniform_sampling_with_variable_resources.py
+++ b/libensemble/tests/functionality_tests/test_uniform_sampling_with_variable_resources.py
@@ -67,8 +67,12 @@
             ("x", float, n),
             ("x_on_cube", float, n),
         ],
+        "batch_size": 5,
+        "batch_mode": False,
+        "give_all_with_same_priority": True,
+        "num_active_gens": 1,
+        "async_return": True,
         "user": {
-            "gen_batch_size": 5,
             "max_resource_sets": nworkers,
             "lb": np.array([-3, -2]),
             "ub": np.array([3, 2]),
@@ -77,12 +81,6 @@
 
     alloc_specs = {
         "alloc_f": give_sim_work_first,
-        "user": {
-            "batch_mode": False,
-            "give_all_with_same_priority": True,
-            "num_active_gens": 1,
-            "async_return": True,
-        },
     }
 
     # This can improve scheduling when tasks may run across multiple nodes
diff --git a/libensemble/tests/functionality_tests/test_worker_exceptions.py b/libensemble/tests/functionality_tests/test_worker_exceptions.py
index 435e621e16..88cb6fcb0b 100644
--- a/libensemble/tests/functionality_tests/test_worker_exceptions.py
+++ b/libensemble/tests/functionality_tests/test_worker_exceptions.py
@@ -16,6 +16,7 @@
 
 import numpy as np
 
+from libensemble.alloc_funcs.give_sim_work_first import give_sim_work_first
 from libensemble.gen_funcs.sampling import uniform_random_sample as gen_f
 from libensemble.libE import libE
 from libensemble.manager import LoggedException
@@ -52,10 +53,16 @@
     # Tell libEnsemble when to stop
     exit_criteria = {"wallclock_max": 10}
 
+    alloc_specs = {
+        "alloc_f": give_sim_work_first,
+    }
+
     # Perform the run
     return_flag = 1
     try:
-        H, persis_info, flag = libE(sim_specs, gen_specs, exit_criteria, persis_info, libE_specs=libE_specs)
+        H, persis_info, flag = libE(
+            sim_specs, gen_specs, exit_criteria, persis_info, alloc_specs=alloc_specs, libE_specs=libE_specs
+        )
     except LoggedException as e:
         print(f"Caught deliberate exception: {e}")
         return_flag = 0
diff --git a/libensemble/tests/functionality_tests/test_workflow_dir.py b/libensemble/tests/functionality_tests/test_workflow_dir.py
index 1abbc10bcf..00c6a5e854 100644
--- a/libensemble/tests/functionality_tests/test_workflow_dir.py
+++ b/libensemble/tests/functionality_tests/test_workflow_dir.py
@@ -18,6 +18,7 @@
 
 import numpy as np
 
+from libensemble.alloc_funcs.give_sim_work_first import give_sim_work_first
 from libensemble.gen_funcs.sampling import uniform_random_sample as gen_f
 from libensemble.libE import libE
 from libensemble.tests.regression_tests.support import write_sim_func as sim_f
@@ -51,13 +52,17 @@
     gen_specs = {
         "gen_f": gen_f,
         "out": [("x", float, (1,))],
+        "batch_size": 20,
         "user": {
-            "gen_batch_size": 20,
             "lb": np.array([-3]),
             "ub": np.array([3]),
         },
     }
 
+    alloc_specs = {
+        "alloc_f": give_sim_work_first,
+    }
+
     persis_info = add_unique_random_streams({}, nworkers + 1)
 
     exit_criteria = {"sim_max": 21}
@@ -70,7 +75,9 @@
             "./test_workflow" + str(i) + "_nworkers" + str(nworkers) + "_comms-" + libE_specs["comms"]
         )
 
-        H, persis_info, flag = libE(sim_specs, gen_specs, exit_criteria, persis_info, libE_specs=libE_specs)
+        H, persis_info, flag = libE(
+            sim_specs, gen_specs, exit_criteria, persis_info, alloc_specs=alloc_specs, libE_specs=libE_specs
+        )
 
         assert os.path.isdir(libE_specs["workflow_dir_path"]), "workflow_dir not created"
         assert all(
diff --git a/libensemble/tests/functionality_tests/test_zero_resource_workers.py b/libensemble/tests/functionality_tests/test_zero_resource_workers.py
index c8f0786d06..a1b3e8e7cd 100644
--- a/libensemble/tests/functionality_tests/test_zero_resource_workers.py
+++ b/libensemble/tests/functionality_tests/test_zero_resource_workers.py
@@ -14,7 +14,6 @@
 import numpy as np
 
 from libensemble import logger
-from libensemble.alloc_funcs.start_only_persistent import only_persistent_gens as alloc_f
 from libensemble.executors.mpi_executor import MPIExecutor
 from libensemble.gen_funcs.persistent_sampling import persistent_uniform as gen_f
 from libensemble.libE import libE
@@ -93,14 +92,13 @@
         "gen_f": gen_f,
         "in": [],
         "out": [("x", float, (n,))],
+        "initial_batch_size": 20,
         "user": {
-            "initial_batch_size": 20,
             "lb": np.array([-3, -2]),
             "ub": np.array([3, 2]),
         },
     }
 
-    alloc_specs = {"alloc_f": alloc_f}
     persis_info = add_unique_random_streams({}, nworkers + 1)
     exit_criteria = {"sim_max": (nsim_workers) * rounds}
 
@@ -125,6 +123,6 @@
     }
 
     # Perform the run
-    H, persis_info, flag = libE(sim_specs, gen_specs, exit_criteria, persis_info, alloc_specs, libE_specs)
+    H, persis_info, flag = libE(sim_specs, gen_specs, exit_criteria, persis_info, libE_specs=libE_specs)
 
     # All asserts are in sim func
diff --git a/libensemble/tests/functionality_tests/test_zero_resource_workers_subnode.py b/libensemble/tests/functionality_tests/test_zero_resource_workers_subnode.py
index 69ea2b559c..978a992d01 100644
--- a/libensemble/tests/functionality_tests/test_zero_resource_workers_subnode.py
+++ b/libensemble/tests/functionality_tests/test_zero_resource_workers_subnode.py
@@ -16,7 +16,6 @@
 import numpy as np
 
 from libensemble import logger
-from libensemble.alloc_funcs.start_only_persistent import only_persistent_gens as alloc_f
 from libensemble.executors.mpi_executor import MPIExecutor
 from libensemble.gen_funcs.persistent_sampling import persistent_uniform as gen_f
 from libensemble.libE import libE
@@ -92,14 +91,13 @@
         "gen_f": gen_f,
         "in": [],
         "out": [("x", float, (n,))],
+        "initial_batch_size": 20,
         "user": {
-            "initial_batch_size": 20,
             "lb": np.array([-3, -2]),
             "ub": np.array([3, 2]),
         },
     }
 
-    alloc_specs = {"alloc_f": alloc_f}
     persis_info = add_unique_random_streams({}, nworkers + 1)
     exit_criteria = {"sim_max": (nsim_workers) * rounds}
 
@@ -128,6 +126,6 @@
     }
 
     # Perform the run
-    H, persis_info, flag = libE(sim_specs, gen_specs, exit_criteria, persis_info, alloc_specs, libE_specs)
+    H, persis_info, flag = libE(sim_specs, gen_specs, exit_criteria, persis_info, libE_specs=libE_specs)
 
     # All asserts are in sim func
diff --git a/libensemble/tests/regression_tests/support.py b/libensemble/tests/regression_tests/support.py
index 4189bcfe48..f472e51290 100644
--- a/libensemble/tests/regression_tests/support.py
+++ b/libensemble/tests/regression_tests/support.py
@@ -69,7 +69,7 @@ def write_uniform_gen_func(H, persis_info, gen_specs, _):
     ub = gen_specs["user"]["ub"]
     lb = gen_specs["user"]["lb"]
     n = len(lb)
-    b = gen_specs["user"]["gen_batch_size"]
+    b = gen_specs["batch_size"]
     H_o = np.zeros(b, dtype=gen_specs["out"])
     H_o["x"] = persis_info["rand_stream"].uniform(lb, ub, (b, n))
     with open("test_gen_out.txt", "a") as f:
@@ -105,7 +105,7 @@ def write_uniform_gen_func(H, persis_info, gen_specs, _):
     "next_to_give": 0,  # Remembers next H row to give in alloc_f
 }
 
-persis_info_1[0] = {
+persis_info_1[0] = {  # noqa
     "run_order": {},  # Used by manager to remember run order
     "total_runs": 0,  # Used by manager to count total runs
     "rand_stream": np.random.default_rng(1),
diff --git a/libensemble/tests/regression_tests/test_1d_sampling.py b/libensemble/tests/regression_tests/test_1d_sampling.py
index edecabb668..a9abbb055b 100644
--- a/libensemble/tests/regression_tests/test_1d_sampling.py
+++ b/libensemble/tests/regression_tests/test_1d_sampling.py
@@ -11,12 +11,12 @@
 
 # Do not change these lines - they are parsed by run-tests.sh
 # TESTSUITE_COMMS: mpi local threads tcp
-# TESTSUITE_NPROCS: 2 4
+# TESTSUITE_NPROCS: 3 4
 
 import numpy as np
 
 from libensemble import Ensemble
-from libensemble.gen_funcs.sampling import latin_hypercube_sample as gen_f
+from libensemble.gen_funcs.persistent_sampling import persistent_uniform
 
 # Import libEnsemble items for this test
 from libensemble.sim_funcs.simple_sim import norm_eval as sim_f
@@ -29,10 +29,10 @@
     sampling.libE_specs = LibeSpecs(save_every_k_gens=300, safe_mode=False, disable_log_files=True)
     sampling.sim_specs = SimSpecs(sim_f=sim_f)
     sampling.gen_specs = GenSpecs(
-        gen_f=gen_f,
+        gen_f=persistent_uniform,
         outputs=[("x", float, (1,))],
+        initial_batch_size=100,
         user={
-            "gen_batch_size": 100,
             "lb": np.array([-3]),
             "ub": np.array([3]),
         },
diff --git a/libensemble/tests/regression_tests/test_2d_sampling.py b/libensemble/tests/regression_tests/test_2d_sampling.py
index 8164c2844a..3601528e10 100644
--- a/libensemble/tests/regression_tests/test_2d_sampling.py
+++ b/libensemble/tests/regression_tests/test_2d_sampling.py
@@ -16,11 +16,12 @@
 import numpy as np
 
 from libensemble import Ensemble
+from libensemble.alloc_funcs.give_sim_work_first import give_sim_work_first
 from libensemble.gen_funcs.sampling import latin_hypercube_sample as gen_f
 
 # Import libEnsemble items for this test
 from libensemble.sim_funcs.simple_sim import norm_eval as sim_f
-from libensemble.specs import ExitCriteria, GenSpecs, LibeSpecs, SimSpecs
+from libensemble.specs import AllocSpecs, ExitCriteria, GenSpecs, LibeSpecs, SimSpecs
 
 # Main block is necessary only when using local comms with spawn start method (default on macOS and Windows).
 if __name__ == "__main__":
@@ -30,13 +31,15 @@
     sampling.gen_specs = GenSpecs(
         gen_f=gen_f,
         outputs=[("x", float, 2)],
+        batch_size=100,
         user={
-            "gen_batch_size": 100,
             "lb": np.array([-3, -2]),
             "ub": np.array([3, 2]),
         },
     )
 
+    sampling.alloc_specs = AllocSpecs(alloc_f=give_sim_work_first)
+
     sampling.exit_criteria = ExitCriteria(sim_max=200)
     sampling.add_random_streams()
 
diff --git a/libensemble/tests/regression_tests/test_GPU_variable_resources.py b/libensemble/tests/regression_tests/test_GPU_variable_resources.py
index b6b3197f90..940688501e 100644
--- a/libensemble/tests/regression_tests/test_GPU_variable_resources.py
+++ b/libensemble/tests/regression_tests/test_GPU_variable_resources.py
@@ -28,7 +28,6 @@
 import numpy as np
 
 from libensemble import Ensemble
-from libensemble.alloc_funcs.start_only_persistent import only_persistent_gens as alloc_f
 from libensemble.executors.mpi_executor import MPIExecutor
 from libensemble.gen_funcs.persistent_sampling_var_resources import uniform_sample_with_procs_gpus as gen_f1
 from libensemble.gen_funcs.persistent_sampling_var_resources import uniform_sample_with_var_gpus as gen_f2
@@ -36,7 +35,7 @@
 # Import libEnsemble items for this test
 from libensemble.sim_funcs import six_hump_camel
 from libensemble.sim_funcs.var_resources import gpu_variable_resources_from_gen as sim_f
-from libensemble.specs import AllocSpecs, ExitCriteria, GenSpecs, LibeSpecs, SimSpecs
+from libensemble.specs import ExitCriteria, GenSpecs, LibeSpecs, SimSpecs
 from libensemble.tools import add_unique_random_streams
 
 # from libensemble import logger
@@ -69,22 +68,16 @@
         gen_f=gen_f1,
         persis_in=["f", "x", "sim_id"],
         out=[("num_procs", int), ("num_gpus", int), ("x", float, 2)],
+        initial_batch_size=gpu_test.nworkers - 1,
+        give_all_with_same_priority=False,
+        async_return=False,
         user={
-            "initial_batch_size": gpu_test.nworkers - 1,
             "max_procs": gpu_test.nworkers - 1,  # Any sim created can req. 1 worker up to max
             "lb": np.array([-3, -2]),
             "ub": np.array([3, 2]),
         },
     )
 
-    gpu_test.alloc_specs = AllocSpecs(
-        alloc_f=alloc_f,
-        user={
-            "give_all_with_same_priority": False,
-            "async_return": False,  # False causes batch returns
-        },
-    )
-
     # Run with random num_procs/num_gpus for each simulation
     gpu_test.persis_info = add_unique_random_streams({}, gpu_test.nworkers + 1)
     gpu_test.exit_criteria = ExitCriteria(sim_max=20)
diff --git a/libensemble/tests/regression_tests/test_GPU_variable_resources_multi_task.py b/libensemble/tests/regression_tests/test_GPU_variable_resources_multi_task.py
index 2b583d4f06..87b450db58 100644
--- a/libensemble/tests/regression_tests/test_GPU_variable_resources_multi_task.py
+++ b/libensemble/tests/regression_tests/test_GPU_variable_resources_multi_task.py
@@ -37,7 +37,6 @@
 import numpy as np
 
 from libensemble import Ensemble
-from libensemble.alloc_funcs.start_only_persistent import only_persistent_gens as alloc_f
 from libensemble.executors.mpi_executor import MPIExecutor
 
 # Using num_procs / num_gpus in gen
@@ -46,7 +45,7 @@
 # Import libEnsemble items for this test
 from libensemble.sim_funcs import six_hump_camel
 from libensemble.sim_funcs.var_resources import gpu_variable_resources_from_gen as sim_f
-from libensemble.specs import AllocSpecs, ExitCriteria, GenSpecs, LibeSpecs, SimSpecs
+from libensemble.specs import ExitCriteria, GenSpecs, LibeSpecs, SimSpecs
 from libensemble.tools import add_unique_random_streams
 
 # from libensemble import logger
@@ -79,8 +78,10 @@
         gen_f=gen_f,
         persis_in=["f", "x", "sim_id"],
         out=[("num_procs", int), ("num_gpus", int), ("x", float, 2)],
+        initial_batch_size=nworkers - 1,
+        give_all_with_same_priority=False,
+        async_return=False,
         user={
-            "initial_batch_size": nworkers - 1,
             "max_procs": (nworkers - 1) // 2,  # Any sim created can req. 1 worker up to max
             "lb": np.array([-3, -2]),
             "ub": np.array([3, 2]),
@@ -88,14 +89,6 @@
         },
     )
 
-    gpu_test.alloc_specs = AllocSpecs(
-        alloc_f=alloc_f,
-        user={
-            "give_all_with_same_priority": False,
-            "async_return": False,  # False causes batch returns
-        },
-    )
-
     gpu_test.persis_info = add_unique_random_streams({}, gpu_test.nworkers + 1)
     gpu_test.exit_criteria = ExitCriteria(sim_max=40, wallclock_max=300)
 
diff --git a/libensemble/tests/regression_tests/test_asktell_aposmm_nlopt.py b/libensemble/tests/regression_tests/test_asktell_aposmm_nlopt.py
index a85771d7dd..ec7615fdb7 100644
--- a/libensemble/tests/regression_tests/test_asktell_aposmm_nlopt.py
+++ b/libensemble/tests/regression_tests/test_asktell_aposmm_nlopt.py
@@ -31,10 +31,9 @@
 from gest_api.vocs import VOCS
 
 from libensemble import Ensemble
-from libensemble.alloc_funcs.start_only_persistent import only_persistent_gens as alloc_f
 from libensemble.gen_classes import APOSMM
 from libensemble.manager import LoggedException
-from libensemble.specs import AllocSpecs, ExitCriteria, GenSpecs, SimSpecs
+from libensemble.specs import ExitCriteria, GenSpecs, SimSpecs
 from libensemble.tests.regression_tests.support import six_hump_camel_minima as minima
 
 
@@ -62,7 +61,6 @@ def six_hump_camel_func(x):
             start_time = time()
 
         n = 2
-        workflow.alloc_specs = AllocSpecs(alloc_f=alloc_f)
 
         workflow.libE_specs.gen_on_manager = True
 
diff --git a/libensemble/tests/regression_tests/test_asktell_gpCAM.py b/libensemble/tests/regression_tests/test_asktell_gpCAM.py
index b093a0df7a..f59fc135d7 100644
--- a/libensemble/tests/regression_tests/test_asktell_gpCAM.py
+++ b/libensemble/tests/regression_tests/test_asktell_gpCAM.py
@@ -24,7 +24,6 @@
 import numpy as np
 from gest_api.vocs import VOCS
 
-from libensemble.alloc_funcs.start_only_persistent import only_persistent_gens as alloc_f
 from libensemble.gen_classes.gpCAM import GP_CAM, GP_CAM_Covar
 
 # Import libEnsemble items for this test
@@ -65,8 +64,6 @@
 
     vocs = VOCS(variables={"x0": [-3, 3], "x1": [-2, 2], "x2": [-1, 1], "x3": [-1, 1]}, objectives={"f": "MINIMIZE"})
 
-    alloc_specs = {"alloc_f": alloc_f}
-
     gen = GP_CAM_Covar(vocs)
 
     for inst in range(3):
@@ -89,7 +86,7 @@
             exit_criteria = {"sim_max": num_batches * batch_size, "wallclock_max": 300}
 
         # Perform the run
-        H, persis_info, flag = libE(sim_specs, gen_specs, exit_criteria, {}, alloc_specs, libE_specs)
+        H, persis_info, flag = libE(sim_specs, gen_specs, exit_criteria, {}, libE_specs=libE_specs)
         if is_manager:
             assert len(np.unique(H["gen_ended_time"])) == num_batches
 
diff --git a/libensemble/tests/regression_tests/test_ensemble_platform_workdir.py b/libensemble/tests/regression_tests/test_ensemble_platform_workdir.py
index 121b0cd37a..bb5a63488a 100644
--- a/libensemble/tests/regression_tests/test_ensemble_platform_workdir.py
+++ b/libensemble/tests/regression_tests/test_ensemble_platform_workdir.py
@@ -6,7 +6,6 @@
 
 # Import libEnsemble items for this test
 from libensemble import Ensemble
-from libensemble.alloc_funcs.start_only_persistent import only_persistent_gens as alloc_f
 from libensemble.executors.mpi_executor import MPIExecutor
 from libensemble.gen_funcs.persistent_sampling_var_resources import uniform_sample as gen_f
 from libensemble.resources.platforms import PerlmutterGPU
@@ -23,14 +22,6 @@
     six_hump_camel_app = six_hump_camel.__file__
     n = 2
 
-    alloc_specs = {
-        "alloc_f": alloc_f,
-        "user": {
-            "give_all_with_same_priority": False,
-            "async_return": False,  # False batch returns
-        },
-    }
-
     exit_criteria = {"sim_max": 20}
 
     # Ensure LIBE_PLATFORM environment variable is not set.
@@ -43,9 +34,7 @@
     ensemble = Ensemble(
         parse_args=True,
         executor=exctr,
-        alloc_specs=alloc_specs,
         exit_criteria=exit_criteria,
-        # libE_specs = LibeSpecs(use_workflow_dir=True, platform_specs=platform_specs),  # works
     )
 
     platform_specs = PerlmutterGPU()
@@ -60,8 +49,10 @@
         "gen_f": gen_f,
         "persis_in": ["f", "x", "sim_id"],
         "out": [("priority", float), ("resource_sets", int), ("x", float, n)],
+        "initial_batch_size": ensemble.nworkers - 1,
+        "give_all_with_same_priority": False,
+        "async_return": False,
         "user": {
-            "initial_batch_size": ensemble.nworkers - 1,
             "max_resource_sets": ensemble.nworkers - 1,  # Any sim created can req. 1 worker up to all.
             "lb": np.array([-3, -2]),
             "ub": np.array([3, 2]),
diff --git a/libensemble/tests/regression_tests/test_gpCAM.py b/libensemble/tests/regression_tests/test_gpCAM.py
index 218ecfc918..b5074ac610 100644
--- a/libensemble/tests/regression_tests/test_gpCAM.py
+++ b/libensemble/tests/regression_tests/test_gpCAM.py
@@ -28,7 +28,6 @@
 
 import numpy as np
 
-from libensemble.alloc_funcs.start_only_persistent import only_persistent_gens as alloc_f
 from libensemble.gen_funcs.persistent_gpCAM import persistent_gpCAM, persistent_gpCAM_covar
 
 # Import libEnsemble items for this test
@@ -67,8 +66,6 @@
         },
     }
 
-    alloc_specs = {"alloc_f": alloc_f}
-
     for inst in range(3):
         if inst == 0:
             gen_specs["gen_f"] = persistent_gpCAM_covar
@@ -91,7 +88,7 @@
         persis_info = add_unique_random_streams({}, nworkers + 1)
 
         # Perform the run
-        H, persis_info, flag = libE(sim_specs, gen_specs, exit_criteria, persis_info, alloc_specs, libE_specs)
+        H, persis_info, flag = libE(sim_specs, gen_specs, exit_criteria, persis_info, libE_specs=libE_specs)
 
         if is_manager:
             assert len(np.unique(H["gen_ended_time"])) == num_batches
diff --git a/libensemble/tests/regression_tests/test_optimas_ax_mf.py b/libensemble/tests/regression_tests/test_optimas_ax_mf.py
index 758aa1fc2c..5b9f4dca08 100644
--- a/libensemble/tests/regression_tests/test_optimas_ax_mf.py
+++ b/libensemble/tests/regression_tests/test_optimas_ax_mf.py
@@ -23,8 +23,7 @@
 from optimas.generators import AxMultiFidelityGenerator
 
 from libensemble import Ensemble
-from libensemble.alloc_funcs.start_only_persistent import only_persistent_gens as alloc_f
-from libensemble.specs import AllocSpecs, ExitCriteria, GenSpecs, LibeSpecs, SimSpecs
+from libensemble.specs import ExitCriteria, GenSpecs, LibeSpecs, SimSpecs
 
 
 def eval_func_mf(input_params):
@@ -62,13 +61,11 @@ def eval_func_mf(input_params):
         vocs=vocs,
     )
 
-    alloc_specs = AllocSpecs(alloc_f=alloc_f)
     exit_criteria = ExitCriteria(sim_max=6)
 
     workflow = Ensemble(
         libE_specs=libE_specs,
         sim_specs=sim_specs,
-        alloc_specs=alloc_specs,
         gen_specs=gen_specs,
         exit_criteria=exit_criteria,
     )
diff --git a/libensemble/tests/regression_tests/test_optimas_ax_multitask.py b/libensemble/tests/regression_tests/test_optimas_ax_multitask.py
index 43c6c444eb..e7031bb226 100644
--- a/libensemble/tests/regression_tests/test_optimas_ax_multitask.py
+++ b/libensemble/tests/regression_tests/test_optimas_ax_multitask.py
@@ -31,8 +31,7 @@
 from optimas.generators import AxMultitaskGenerator
 
 from libensemble import Ensemble
-from libensemble.alloc_funcs.start_only_persistent import only_persistent_gens as alloc_f
-from libensemble.specs import AllocSpecs, ExitCriteria, GenSpecs, LibeSpecs, SimSpecs
+from libensemble.specs import ExitCriteria, GenSpecs, LibeSpecs, SimSpecs
 
 
 def eval_func_multitask(input_params):
@@ -73,7 +72,6 @@ def eval_func_multitask(input_params):
         vocs=vocs,
     )
 
-    alloc_specs = AllocSpecs(alloc_f=alloc_f)
     exit_criteria = ExitCriteria(sim_max=15)
 
     H0 = None  # or np.load("multitask_first_pass.npy")
@@ -92,7 +90,6 @@ def eval_func_multitask(input_params):
         workflow = Ensemble(
             libE_specs=libE_specs,
             sim_specs=sim_specs,
-            alloc_specs=alloc_specs,
             gen_specs=gen_specs,
             exit_criteria=exit_criteria,
             H0=H0,
diff --git a/libensemble/tests/regression_tests/test_optimas_ax_sf.py b/libensemble/tests/regression_tests/test_optimas_ax_sf.py
index e4ee9e8a79..1a23edf290 100644
--- a/libensemble/tests/regression_tests/test_optimas_ax_sf.py
+++ b/libensemble/tests/regression_tests/test_optimas_ax_sf.py
@@ -23,8 +23,7 @@
 from optimas.generators import AxSingleFidelityGenerator
 
 from libensemble import Ensemble
-from libensemble.alloc_funcs.start_only_persistent import only_persistent_gens as alloc_f
-from libensemble.specs import AllocSpecs, ExitCriteria, GenSpecs, LibeSpecs, SimSpecs
+from libensemble.specs import ExitCriteria, GenSpecs, LibeSpecs, SimSpecs
 
 
 def eval_func_sf(input_params):
@@ -64,13 +63,11 @@ def eval_func_sf(input_params):
         vocs=vocs,
     )
 
-    alloc_specs = AllocSpecs(alloc_f=alloc_f)
     exit_criteria = ExitCriteria(sim_max=10)
 
     workflow = Ensemble(
         libE_specs=libE_specs,
         sim_specs=sim_specs,
-        alloc_specs=alloc_specs,
         gen_specs=gen_specs,
         exit_criteria=exit_criteria,
     )
diff --git a/libensemble/tests/regression_tests/test_optimas_grid_sample.py b/libensemble/tests/regression_tests/test_optimas_grid_sample.py
index 57c6c8fedf..c390be8ca1 100644
--- a/libensemble/tests/regression_tests/test_optimas_grid_sample.py
+++ b/libensemble/tests/regression_tests/test_optimas_grid_sample.py
@@ -24,8 +24,7 @@
 from optimas.generators import GridSamplingGenerator
 
 from libensemble import Ensemble
-from libensemble.alloc_funcs.start_only_persistent import only_persistent_gens as alloc_f
-from libensemble.specs import AllocSpecs, ExitCriteria, GenSpecs, LibeSpecs, SimSpecs
+from libensemble.specs import ExitCriteria, GenSpecs, LibeSpecs, SimSpecs
 
 
 def eval_func(input_params: dict):
@@ -73,13 +72,11 @@ def eval_func(input_params: dict):
         vocs=vocs,
     )
 
-    alloc_specs = AllocSpecs(alloc_f=alloc_f)
     exit_criteria = ExitCriteria(sim_max=n_evals)
 
     workflow = Ensemble(
         libE_specs=libE_specs,
         sim_specs=sim_specs,
-        alloc_specs=alloc_specs,
         gen_specs=gen_specs,
         exit_criteria=exit_criteria,
     )
diff --git a/libensemble/tests/regression_tests/test_persistent_aposmm_dfols.py b/libensemble/tests/regression_tests/test_persistent_aposmm_dfols.py
index 6e19930691..c810db561e 100644
--- a/libensemble/tests/regression_tests/test_persistent_aposmm_dfols.py
+++ b/libensemble/tests/regression_tests/test_persistent_aposmm_dfols.py
@@ -69,6 +69,7 @@ def combine_component(x):
         "gen_f": gen_f,
         "persis_in": ["f", "fvec"] + [n[0] for n in gen_out],
         "out": gen_out,
+        "initial_batch_size": 100,
         "user": {
             "initial_sample_size": 100,
             "localopt_method": "dfols",
diff --git a/libensemble/tests/regression_tests/test_persistent_aposmm_exception.py b/libensemble/tests/regression_tests/test_persistent_aposmm_exception.py
index b197dc3f07..09544e51d1 100644
--- a/libensemble/tests/regression_tests/test_persistent_aposmm_exception.py
+++ b/libensemble/tests/regression_tests/test_persistent_aposmm_exception.py
@@ -69,6 +69,7 @@ def assertion(passed):
         "gen_f": gen_f,
         "persis_in": ["f"] + [n[0] for n in gen_out],
         "out": gen_out,
+        "initial_batch_size": 100,
         "user": {
             "initial_sample_size": 100,
             "localopt_method": "LN_BOBYQA",
diff --git a/libensemble/tests/regression_tests/test_persistent_aposmm_external_localopt.py b/libensemble/tests/regression_tests/test_persistent_aposmm_external_localopt.py
index dd01d1069e..22cf47325f 100644
--- a/libensemble/tests/regression_tests/test_persistent_aposmm_external_localopt.py
+++ b/libensemble/tests/regression_tests/test_persistent_aposmm_external_localopt.py
@@ -75,6 +75,7 @@
         "gen_f": gen_f,
         "persis_in": ["f"] + [n[0] for n in gen_out],
         "out": gen_out,
+        "initial_batch_size": 100,
         "user": {
             "initial_sample_size": 100,
             "sample_points": np.round(minima, 1),
diff --git a/libensemble/tests/regression_tests/test_persistent_aposmm_nlopt.py b/libensemble/tests/regression_tests/test_persistent_aposmm_nlopt.py
index 9d42784439..bf5914573f 100644
--- a/libensemble/tests/regression_tests/test_persistent_aposmm_nlopt.py
+++ b/libensemble/tests/regression_tests/test_persistent_aposmm_nlopt.py
@@ -64,6 +64,7 @@
         "gen_f": gen_f,
         "persis_in": ["f"] + [n[0] for n in gen_out],
         "out": gen_out,
+        "initial_batch_size": 100,
         "user": {
             "initial_sample_size": 100,
             "sample_points": np.round(minima, 1),
diff --git a/libensemble/tests/regression_tests/test_persistent_aposmm_pounders.py b/libensemble/tests/regression_tests/test_persistent_aposmm_pounders.py
index 5b038a0ce8..3b7609934d 100644
--- a/libensemble/tests/regression_tests/test_persistent_aposmm_pounders.py
+++ b/libensemble/tests/regression_tests/test_persistent_aposmm_pounders.py
@@ -92,9 +92,11 @@ def combine_component(x):
             "lb": lb,
             "ub": ub,
         },
+        "batch_mode": True,
+        "num_active_gens": 1,
     }
 
-    alloc_specs = {"alloc_f": alloc_f, "user": {"batch_mode": True, "num_active_gens": 1}}
+    alloc_specs = {"alloc_f": alloc_f}
 
     persis_info = add_unique_random_streams({}, nworkers + 1)
 
diff --git a/libensemble/tests/regression_tests/test_persistent_aposmm_scipy.py b/libensemble/tests/regression_tests/test_persistent_aposmm_scipy.py
index 76107f567d..f40da2c4b6 100644
--- a/libensemble/tests/regression_tests/test_persistent_aposmm_scipy.py
+++ b/libensemble/tests/regression_tests/test_persistent_aposmm_scipy.py
@@ -65,6 +65,7 @@
         "gen_f": gen_f,
         "persis_in": ["f"] + [n[0] for n in gen_out],
         "out": gen_out,
+        "initial_batch_size": 100,
         "user": {
             "initial_sample_size": 100,
             "sample_points": np.round(minima, 1),
diff --git a/libensemble/tests/regression_tests/test_persistent_aposmm_tao_blmvm.py b/libensemble/tests/regression_tests/test_persistent_aposmm_tao_blmvm.py
index 39ff3b79fd..8a3c762871 100644
--- a/libensemble/tests/regression_tests/test_persistent_aposmm_tao_blmvm.py
+++ b/libensemble/tests/regression_tests/test_persistent_aposmm_tao_blmvm.py
@@ -67,6 +67,7 @@
         "gen_f": gen_f,
         "persis_in": ["f", "grad"] + [n[0] for n in gen_out],
         "out": gen_out,
+        "initial_batch_size": 100,
         "user": {
             "initial_sample_size": 100,
             "sample_points": np.round(minima, 1),
diff --git a/libensemble/tests/regression_tests/test_persistent_aposmm_tao_nm.py b/libensemble/tests/regression_tests/test_persistent_aposmm_tao_nm.py
index d6db6b63a1..0dcb4a2c0d 100644
--- a/libensemble/tests/regression_tests/test_persistent_aposmm_tao_nm.py
+++ b/libensemble/tests/regression_tests/test_persistent_aposmm_tao_nm.py
@@ -60,6 +60,7 @@
         "gen_f": gen_f,
         "persis_in": ["f", "grad"] + [n[0] for n in gen_out],
         "out": gen_out,
+        "initial_batch_size": 100,
         "user": {
             "initial_sample_size": 100,
             "localopt_method": "nm",
diff --git a/libensemble/tests/regression_tests/test_persistent_aposmm_timeout.py b/libensemble/tests/regression_tests/test_persistent_aposmm_timeout.py
index e61843fd71..a31dd01878 100644
--- a/libensemble/tests/regression_tests/test_persistent_aposmm_timeout.py
+++ b/libensemble/tests/regression_tests/test_persistent_aposmm_timeout.py
@@ -62,6 +62,7 @@
         "gen_f": gen_f,
         "persis_in": ["f"] + [n[0] for n in gen_out],
         "out": gen_out,
+        "initial_batch_size": 100,
         "user": {
             "initial_sample_size": 100,
             "localopt_method": "LN_BOBYQA",
diff --git a/libensemble/tests/regression_tests/test_persistent_aposmm_with_grad.py b/libensemble/tests/regression_tests/test_persistent_aposmm_with_grad.py
index f2d2f09cc0..a0364e1c14 100644
--- a/libensemble/tests/regression_tests/test_persistent_aposmm_with_grad.py
+++ b/libensemble/tests/regression_tests/test_persistent_aposmm_with_grad.py
@@ -72,6 +72,7 @@
         "in": gen_in,
         "persis_in": gen_in,
         "out": gen_out,
+        "initial_batch_size": 0,
         "user": {
             "initial_sample_size": 0,  # Don't need to do evaluations because the sampling already done below
             "localopt_method": "LD_MMA",
diff --git a/libensemble/tests/regression_tests/test_persistent_gp_multitask_ax.py b/libensemble/tests/regression_tests/test_persistent_gp_multitask_ax.py
index 990493a176..38b6140fcd 100644
--- a/libensemble/tests/regression_tests/test_persistent_gp_multitask_ax.py
+++ b/libensemble/tests/regression_tests/test_persistent_gp_multitask_ax.py
@@ -26,7 +26,6 @@
 import numpy as np
 
 from libensemble import logger
-from libensemble.alloc_funcs.start_only_persistent import only_persistent_gens
 from libensemble.libE import libE
 from libensemble.message_numbers import WORKER_DONE
 from libensemble.tools import add_unique_random_streams, parse_args, save_libE_output
@@ -90,13 +89,13 @@ def run_simulation(H, persis_info, sim_specs, libE_info):
         "out": [
             # parameters to input into the simulation.
             ("x", float, (2,)),
-            ("task", str, max([len(mt_params["name_hifi"]), len(mt_params["name_lofi"])])),
+            ("task", str, max(len(str(mt_params["name_hifi"])), len(str(mt_params["name_lofi"])))),
             ("resource_sets", int),
         ],
+        "async_return": False,
+        "batch_size": nworkers - 1,
         "user": {
             "range": [1, 8],
-            # Total max number of sims running concurrently.
-            "gen_batch_size": nworkers - 1,
             # Lower bound for the n parameters.
             "lb": np.array([0, 0]),
             # Upper bound for the n parameters.
@@ -105,11 +104,6 @@ def run_simulation(H, persis_info, sim_specs, libE_info):
     }
     gen_specs["user"] = {**gen_specs["user"], **mt_params}
 
-    alloc_specs = {
-        "alloc_f": only_persistent_gens,
-        "user": {"async_return": False},
-    }
-
     # libE logger
     logger.set_level("INFO")
 
@@ -120,7 +114,7 @@ def run_simulation(H, persis_info, sim_specs, libE_info):
     persis_info = add_unique_random_streams({}, nworkers + 1)
 
     # Run LibEnsemble, and store results in history array H
-    H, persis_info, flag = libE(sim_specs, gen_specs, exit_criteria, persis_info, alloc_specs, libE_specs)
+    H, persis_info, flag = libE(sim_specs, gen_specs, exit_criteria, persis_info, libE_specs=libE_specs)
 
     # Save results to numpy file
     if is_manager:
diff --git a/libensemble/tests/regression_tests/test_persistent_surmise_calib.py b/libensemble/tests/regression_tests/test_persistent_surmise_calib.py
index 39cf11b5de..6936269466 100644
--- a/libensemble/tests/regression_tests/test_persistent_surmise_calib.py
+++ b/libensemble/tests/regression_tests/test_persistent_surmise_calib.py
@@ -33,13 +33,12 @@
 import numpy as np
 
 from libensemble import Ensemble
-from libensemble.alloc_funcs.start_only_persistent import only_persistent_gens as alloc_f
 from libensemble.gen_funcs.persistent_surmise_calib import surmise_calib as gen_f
 
 # Import libEnsemble items for this test
 from libensemble.sim_funcs.surmise_test_function import borehole as sim_f
 from libensemble.sim_funcs.surmise_test_function import tstd2theta
-from libensemble.specs import AllocSpecs, ExitCriteria, GenSpecs, SimSpecs
+from libensemble.specs import ExitCriteria, GenSpecs, SimSpecs
 from libensemble.tools import add_unique_random_streams
 
 if __name__ == "__main__":
@@ -84,18 +83,12 @@
                 "step_add_theta": step_add_theta,  # No. of thetas to generate per step
                 "n_explore_theta": n_explore_theta,  # No. of thetas to explore each step
                 "obsvar": obsvar,  # Variance for generating noise in obs
-                "init_sample_size": init_sample_size,  # Initial batch size inc. observations
                 "priorloc": 1,  # Prior location in the unit cube
                 "priorscale": 0.5,  # Standard deviation of prior
             },
-        ),
-        alloc_specs=AllocSpecs(
-            alloc_f=alloc_f,
-            user={
-                "init_sample_size": init_sample_size,
-                "async_return": True,  # True = Return results to gen as they come in (after sample)
-                "active_recv_gen": True,  # Persistent gen can handle irregular communications
-            },
+            initial_batch_size=init_sample_size,
+            async_return=True,
+            active_recv_gen=True,
         ),
         exit_criteria=ExitCriteria(sim_max=max_evals),
     )
diff --git a/libensemble/tests/regression_tests/test_persistent_surmise_killsims.py b/libensemble/tests/regression_tests/test_persistent_surmise_killsims.py
index 11095f61f2..6e289a0081 100644
--- a/libensemble/tests/regression_tests/test_persistent_surmise_killsims.py
+++ b/libensemble/tests/regression_tests/test_persistent_surmise_killsims.py
@@ -34,7 +34,6 @@
 
 import numpy as np
 
-from libensemble.alloc_funcs.start_only_persistent import only_persistent_gens as alloc_f
 from libensemble.executors.executor import Executor
 from libensemble.gen_funcs.persistent_surmise_calib import surmise_calib as gen_f
 
@@ -105,34 +104,25 @@
         "gen_f": gen_f,
         "persis_in": [o[0] for o in gen_out] + ["f", "sim_ended", "sim_id"],
         "out": gen_out,
+        "initial_batch_size": init_sample_size,
+        "async_return": True,
+        "active_recv_gen": True,
         "user": {
             "n_init_thetas": n_init_thetas,  # Num thetas in initial batch
             "num_x_vals": n_x,  # Num x points to create
             "step_add_theta": step_add_theta,  # No. of thetas to generate per step
             "n_explore_theta": n_explore_theta,  # No. of thetas to explore each step
             "obsvar": obsvar,  # Variance for generating noise in obs
-            "init_sample_size": init_sample_size,  # Initial batch size inc. observations
             "priorloc": 1,  # Prior location in the unit cube.
             "priorscale": 0.2,  # Standard deviation of prior
         },
     }
 
-    alloc_specs = {
-        "alloc_f": alloc_f,
-        "user": {
-            "init_sample_size": init_sample_size,
-            "async_return": True,  # True = Return results to gen as they come in (after sample)
-            "active_recv_gen": True,  # Persistent gen can handle irregular communications
-        },
-    }
-
     persis_info = add_unique_random_streams({}, nworkers + 1)
     exit_criteria = {"sim_max": max_evals}
 
     # Perform the run
-    H, persis_info, flag = libE(
-        sim_specs, gen_specs, exit_criteria, persis_info, alloc_specs=alloc_specs, libE_specs=libE_specs
-    )
+    H, persis_info, flag = libE(sim_specs, gen_specs, exit_criteria, persis_info, libE_specs=libE_specs)
 
     if is_manager:
         print("Cancelled sims", H["sim_id"][H["cancel_requested"]])
diff --git a/libensemble/tests/regression_tests/test_xopt_EI.py b/libensemble/tests/regression_tests/test_xopt_EI.py
index a78aee60a5..69eea46dc1 100644
--- a/libensemble/tests/regression_tests/test_xopt_EI.py
+++ b/libensemble/tests/regression_tests/test_xopt_EI.py
@@ -23,8 +23,7 @@
 from xopt.generators.bayesian.expected_improvement import ExpectedImprovementGenerator
 
 from libensemble import Ensemble
-from libensemble.alloc_funcs.start_only_persistent import only_persistent_gens as alloc_f
-from libensemble.specs import AllocSpecs, ExitCriteria, GenSpecs, LibeSpecs, SimSpecs
+from libensemble.specs import ExitCriteria, GenSpecs, LibeSpecs, SimSpecs
 
 
 # Adapted from Xopt/xopt/resources/testing.py
@@ -85,13 +84,11 @@ def xtest_sim(H, persis_info, sim_specs, _):
         vocs=vocs,
     )
 
-    alloc_specs = AllocSpecs(alloc_f=alloc_f)
     exit_criteria = ExitCriteria(sim_max=20)
 
     workflow = Ensemble(
         libE_specs=libE_specs,
         sim_specs=sim_specs,
-        alloc_specs=alloc_specs,
         gen_specs=gen_specs,
         exit_criteria=exit_criteria,
     )
diff --git a/libensemble/tests/regression_tests/test_xopt_EI_xopt_sim.py b/libensemble/tests/regression_tests/test_xopt_EI_xopt_sim.py
index 07ace47fa9..9efffb58e0 100644
--- a/libensemble/tests/regression_tests/test_xopt_EI_xopt_sim.py
+++ b/libensemble/tests/regression_tests/test_xopt_EI_xopt_sim.py
@@ -23,8 +23,7 @@
 from xopt.generators.bayesian.expected_improvement import ExpectedImprovementGenerator
 
 from libensemble import Ensemble
-from libensemble.alloc_funcs.start_only_persistent import only_persistent_gens as alloc_f
-from libensemble.specs import AllocSpecs, ExitCriteria, GenSpecs, LibeSpecs, SimSpecs
+from libensemble.specs import ExitCriteria, GenSpecs, LibeSpecs, SimSpecs
 
 
 # From Xopt/xopt/resources/testing.py
@@ -79,13 +78,11 @@ def xtest_callable(input_dict: dict, a=0) -> dict:
         vocs=vocs,
     )
 
-    alloc_specs = AllocSpecs(alloc_f=alloc_f)
     exit_criteria = ExitCriteria(sim_max=20)
 
     workflow = Ensemble(
         libE_specs=libE_specs,
         sim_specs=sim_specs,
-        alloc_specs=alloc_specs,
         gen_specs=gen_specs,
         exit_criteria=exit_criteria,
     )
diff --git a/libensemble/tests/regression_tests/test_xopt_nelder_mead.py b/libensemble/tests/regression_tests/test_xopt_nelder_mead.py
index fe8039b95c..4f0a4d285a 100644
--- a/libensemble/tests/regression_tests/test_xopt_nelder_mead.py
+++ b/libensemble/tests/regression_tests/test_xopt_nelder_mead.py
@@ -21,8 +21,7 @@
 from xopt.generators.sequential.neldermead import NelderMeadGenerator
 
 from libensemble import Ensemble
-from libensemble.alloc_funcs.start_only_persistent import only_persistent_gens as alloc_f
-from libensemble.specs import AllocSpecs, ExitCriteria, GenSpecs, LibeSpecs, SimSpecs
+from libensemble.specs import ExitCriteria, GenSpecs, LibeSpecs, SimSpecs
 
 
 def rosenbrock_callable(input_dict: dict) -> dict:
@@ -67,13 +66,11 @@ def rosenbrock_callable(input_dict: dict) -> dict:
         vocs=vocs,
     )
 
-    alloc_specs = AllocSpecs(alloc_f=alloc_f)
     exit_criteria = ExitCriteria(sim_max=30)
 
     workflow = Ensemble(
         libE_specs=libE_specs,
         sim_specs=sim_specs,
-        alloc_specs=alloc_specs,
         gen_specs=gen_specs,
         exit_criteria=exit_criteria,
     )
diff --git a/libensemble/tests/scaling_tests/forces/forces_adv/run_libe_forces.py b/libensemble/tests/scaling_tests/forces/forces_adv/run_libe_forces.py
index 3b5a489d62..7be531c37b 100644
--- a/libensemble/tests/scaling_tests/forces/forces_adv/run_libe_forces.py
+++ b/libensemble/tests/scaling_tests/forces/forces_adv/run_libe_forces.py
@@ -20,8 +20,8 @@
     from libensemble.alloc_funcs.start_only_persistent import only_persistent_gens as alloc_f
     from libensemble.gen_funcs.persistent_sampling import persistent_uniform as gen_f
 else:
-    from libensemble.alloc_funcs.give_sim_work_first import give_sim_work_first as alloc_f
-    from libensemble.gen_funcs.sampling import uniform_random_sample as gen_f
+    from libensemble.alloc_funcs.give_sim_work_first import give_sim_work_first as alloc_f  # type: ignore[no-redef]
+    from libensemble.gen_funcs.sampling import uniform_random_sample as gen_f  # type: ignore[no-redef]
 
 
 logger.set_level("INFO")  # INFO is now default
@@ -65,23 +65,20 @@
     "gen_f": gen_f,  # Generator function
     "in": [],  # Generator input
     "out": [("x", float, (1,))],  # Name, type and size of data produced (must match sim_specs 'in')
+    "batch_size": 1000,  # How many random samples to generate in one call
     "user": {
         "lb": np.array([0]),  # Lower bound for random sample array (1D)
         "ub": np.array([32767]),  # Upper bound for random sample array (1D)
-        "gen_batch_size": 1000,  # How many random samples to generate in one call
     },
 }
 
 if PERSIS_GEN:
-    alloc_specs = {"alloc_f": alloc_f}
+    alloc_specs = {}
+    gen_specs["async_return"] = False
 else:
-    alloc_specs = {
-        "alloc_f": alloc_f,
-        "user": {
-            "batch_mode": True,  # If true wait for all sims to process before generate more
-            "num_active_gens": 1,  # Only one active generator at a time
-        },
-    }
+    alloc_specs = {"alloc_f": alloc_f}
+    gen_specs["batch_mode"] = True
+    gen_specs["num_active_gens"] = 1
 
 libE_specs["save_every_k_gens"] = 1000  # Save every K steps
 libE_specs["sim_dirs_make"] = True  # Separate each sim into a separate directory
@@ -92,8 +89,7 @@
 exit_criteria = {"sim_max": sim_max}
 
 # Create a different random number stream for each worker and the manager
-persis_info = {}
-persis_info = add_unique_random_streams(persis_info, nworkers + 1)
+persis_info = add_unique_random_streams({}, nworkers + 1)
 
 try:
     H, persis_info, flag = libE(
diff --git a/libensemble/tests/scaling_tests/forces/forces_simple/run_libe_forces.py b/libensemble/tests/scaling_tests/forces/forces_simple/run_libe_forces.py
index a70477748b..6d5e0bb0e5 100644
--- a/libensemble/tests/scaling_tests/forces/forces_simple/run_libe_forces.py
+++ b/libensemble/tests/scaling_tests/forces/forces_simple/run_libe_forces.py
@@ -6,10 +6,9 @@
 from forces_simf import run_forces  # Sim func from current dir
 
 from libensemble import Ensemble
-from libensemble.alloc_funcs.start_only_persistent import only_persistent_gens as alloc_f
 from libensemble.executors import MPIExecutor
 from libensemble.gen_funcs.persistent_sampling import persistent_uniform as gen_f
-from libensemble.specs import AllocSpecs, ExitCriteria, GenSpecs, LibeSpecs, SimSpecs
+from libensemble.specs import ExitCriteria, GenSpecs, LibeSpecs, SimSpecs
 
 if __name__ == "__main__":
     # Initialize MPI Executor
@@ -44,20 +43,15 @@
         inputs=[],  # No input when start persistent generator
         persis_in=["sim_id"],  # Return sim_ids of evaluated points to generator
         outputs=[("x", float, (1,))],
+        initial_batch_size=nsim_workers,
+        async_return=False,
         user={
-            "initial_batch_size": nsim_workers,
             "lb": np.array([1000]),  # min particles
             "ub": np.array([3000]),  # max particles
         },
     )
 
     # Starts one persistent generator. Simulated values are returned in batch.
-    ensemble.alloc_specs = AllocSpecs(
-        alloc_f=alloc_f,
-        user={
-            "async_return": False,  # False causes batch returns
-        },
-    )
 
     # Instruct libEnsemble to exit after this many simulations
     ensemble.exit_criteria = ExitCriteria(sim_max=8)
diff --git a/libensemble/tests/scaling_tests/forces/forces_simple_with_input_file/run_libe_forces.py b/libensemble/tests/scaling_tests/forces/forces_simple_with_input_file/run_libe_forces.py
index 8f3e8d442a..41217173b8 100644
--- a/libensemble/tests/scaling_tests/forces/forces_simple_with_input_file/run_libe_forces.py
+++ b/libensemble/tests/scaling_tests/forces/forces_simple_with_input_file/run_libe_forces.py
@@ -6,10 +6,9 @@
 from forces_simf import run_forces  # Sim func from current dir
 
 from libensemble import Ensemble
-from libensemble.alloc_funcs.start_only_persistent import only_persistent_gens as alloc_f
 from libensemble.executors import MPIExecutor
 from libensemble.gen_funcs.persistent_sampling import persistent_uniform as gen_f
-from libensemble.specs import AllocSpecs, ExitCriteria, GenSpecs, LibeSpecs, SimSpecs
+from libensemble.specs import ExitCriteria, GenSpecs, LibeSpecs, SimSpecs
 
 if __name__ == "__main__":
     # Initialize MPI Executor
@@ -48,20 +47,15 @@
         inputs=[],  # No input when start persistent generator
         persis_in=["sim_id"],  # Return sim_ids of evaluated points to generator
         outputs=[("x", float, (1,))],
+        initial_batch_size=nsim_workers,
+        async_return=False,
         user={
-            "initial_batch_size": nsim_workers,
             "lb": np.array([1000]),  # min particles
             "ub": np.array([3000]),  # max particles
         },
     )
 
     # Starts one persistent generator. Simulated values are returned in batch.
-    ensemble.alloc_specs = AllocSpecs(
-        alloc_f=alloc_f,
-        user={
-            "async_return": False,  # False causes batch returns
-        },
-    )
 
     # Instruct libEnsemble to exit after this many simulations
     ensemble.exit_criteria = ExitCriteria(sim_max=8)
diff --git a/libensemble/tests/scaling_tests/persistent_gp/run_example.py b/libensemble/tests/scaling_tests/persistent_gp/run_example.py
index 035fa9c1e0..182c0034e1 100644
--- a/libensemble/tests/scaling_tests/persistent_gp/run_example.py
+++ b/libensemble/tests/scaling_tests/persistent_gp/run_example.py
@@ -9,7 +9,6 @@
 import numpy as np
 
 from libensemble import logger
-from libensemble.alloc_funcs.start_only_persistent import only_persistent_gens
 from libensemble.gen_funcs.persistent_ax_multitask import persistent_gp_mt_ax_gen_f
 from libensemble.libE import libE
 from libensemble.message_numbers import WORKER_DONE
@@ -63,13 +62,13 @@ def run_simulation(H, persis_info, sim_specs, libE_info):
     "out": [
         # parameters to input into the simulation.
         ("x", float, (2,)),
-        ("task", str, max([len(mt_params["name_hifi"]), len(mt_params["name_lofi"])])),
+        ("task", str, max(len(str(mt_params["name_hifi"])), len(str(mt_params["name_lofi"])))),
         ("resource_sets", int),
     ],
+    "async_return": False,
+    "batch_size": nworkers - 1,
     "user": {
         "range": [1, 8],
-        # Total max number of sims running concurrently.
-        "gen_batch_size": nworkers - 1,
         # Lower bound for the n parameters.
         "lb": np.array([0, 0]),
         # Upper bound for the n parameters.
@@ -78,11 +77,6 @@ def run_simulation(H, persis_info, sim_specs, libE_info):
 }
 gen_specs["user"] = {**gen_specs["user"], **mt_params}
 
-alloc_specs = {
-    "alloc_f": only_persistent_gens,
-    "out": [("gen_informed", bool)],
-    "user": {"async_return": False},
-}
 
 # libE logger
 logger.set_level("INFO")
@@ -94,7 +88,7 @@ def run_simulation(H, persis_info, sim_specs, libE_info):
 persis_info = add_unique_random_streams({}, nworkers + 1)
 
 # Run LibEnsemble, and store results in history array H
-H, persis_info, flag = libE(sim_specs, gen_specs, exit_criteria, persis_info, alloc_specs, libE_specs)
+H, persis_info, flag = libE(sim_specs, gen_specs, exit_criteria, persis_info, libE_specs=libE_specs)
 
 # Save results to numpy file
 if is_manager:
diff --git a/libensemble/tests/unit_tests/test_ensemble.py b/libensemble/tests/unit_tests/test_ensemble.py
index 94c4865ad4..3a64a38c18 100644
--- a/libensemble/tests/unit_tests/test_ensemble.py
+++ b/libensemble/tests/unit_tests/test_ensemble.py
@@ -38,10 +38,11 @@ def test_ensemble_parse_args_false():
 
 def test_full_workflow():
     """Test initializing a workflow via Specs and Ensemble.run()"""
+    from libensemble.alloc_funcs.give_sim_work_first import give_sim_work_first
     from libensemble.ensemble import Ensemble
     from libensemble.gen_funcs.sampling import latin_hypercube_sample
     from libensemble.sim_funcs.simple_sim import norm_eval
-    from libensemble.specs import ExitCriteria, GenSpecs, LibeSpecs, SimSpecs
+    from libensemble.specs import AllocSpecs, ExitCriteria, GenSpecs, LibeSpecs, SimSpecs
 
     LS = LibeSpecs(comms="local", nworkers=4)
 
@@ -51,13 +52,14 @@ def test_full_workflow():
         sim_specs=SimSpecs(sim_f=norm_eval),
         gen_specs=GenSpecs(
             gen_f=latin_hypercube_sample,
+            batch_size=100,
             user={
-                "gen_batch_size": 100,
                 "lb": np.array([-3]),
                 "ub": np.array([3]),
             },
         ),
         exit_criteria=ExitCriteria(gen_max=101),
+        alloc_specs=AllocSpecs(alloc_f=give_sim_work_first),
     )
 
     ens.add_random_streams()
@@ -93,8 +95,8 @@ def test_flakey_workflow():
             sim_specs=SimSpecs(sim_f=norm_eval),
             gen_specs=GenSpecs(
                 gen_f=latin_hypercube_sample,
+                batch_size=100,
                 user={
-                    "gen_batch_size": 100,
                     "lb": np.array([-3]),
                     "ub": np.array([3]),
                 },
diff --git a/pixi.lock b/pixi.lock
index 185e31d3a4..3357902824 100644
--- a/pixi.lock
+++ b/pixi.lock
@@ -1,3 +1,3 @@
 version https://git-lfs.github.com/spec/v1
-oid sha256:817f427252b67646c9eea0f0a4c5a1ce662c2859400dc5fd563f314e92914891
-size 1021669
+oid sha256:61c5432ee07721317765d0bd57cc8802f96ec9376005b4bedc1bb26f39dc116f
+size 1020189
diff --git a/pyproject.toml b/pyproject.toml
index 5538457e56..871e651525 100644
--- a/pyproject.toml
+++ b/pyproject.toml
@@ -8,12 +8,7 @@ authors = [
   { name = "John-Luke Navarro" },
 ]
 
-dependencies = [
-  "numpy",
-  "psutil",
-  "pydantic",
-  "gest-api>=0.1,<0.2",
-]
+dependencies = ["numpy", "psutil", "pydantic", "gest-api>=0.1,<0.2"]
 
 description = "A Python toolkit for coordinating asynchronous and dynamic ensembles of calculations."
 name = "libensemble"
@@ -187,6 +182,7 @@ pip = ">=25.2,<26"
 setuptools = ">=80.8.0,<81"
 numpy = ">=2.2.6,<3"
 pydantic = ">=2.12.4,<3"
+gest-api = ">=0.1,<0.2"
 
 
 # macOS dependencies
@@ -247,9 +243,7 @@ extend-exclude = ["*.bib", "*.xml", "docs/nitpicky"]
 # Initial, permissive mypy configuration for libensemble.
 # Allows incremental adoption. To be tightened in future releases.
 packages = ["libensemble.utils"]
-exclude = '''
-libensemble/utils/(launcher|loc_stack|runners|pydantic|output_directory)\.py
-'''
+exclude = 'libensemble/utils/(launcher|loc_stack|runners|pydantic|output_directory)\.py$|libensemble/tests/regression_tests/support\.py$|libensemble/tests/functionality_tests/.*'
 disable_error_code = ["import-not-found", "import-untyped"]
 ignore_missing_imports = true
 follow_imports = "skip"