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Functional AssessmentVerdict: ❌ Incomplete
🧠 User Story ID: FCM-001-A — File Change Management📝 Feature CompletenessThe Requirement was.. The system must successfully incorporate 63 distinct file changes and pass initial syntax and integrity checks. This is what is built... Implemented approximately 30 Python scripts covering various algorithms and utilities, but failed to reach the required 63 file count. 📊 Implementation Status
✅ Completed Components
❌ Gaps & Issues
🎯 Conclusion & Final AssessmentImportant 🟢 Completed Features: Key completed features include the implementation of various Python utility scripts such as LCM calculation, binary conversions, sorting algorithms (Merge, Quick, Bubble), and basic data structures like Arrays. |
⚙️ DevOps and Release Automation🟢 Status: Passed🌟 Excellent work! Your code passed the DevOps review. |
🔍 Technical Quality Assessment📋 SummaryThis update adds a collection of helpful tools and mathematical calculations to our system, such as sorting data and converting numbers. While these tools are useful, several of them currently have 'bugs' that could cause the system to crash or give wrong answers if a user types in something unexpected (like a letter instead of a number). 💼 Business Impact
🎯 Purpose & Scope
📊 Change AnalysisFiles by Category:
Impact Distribution:
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| File | Status | Description | Impact | Issues Detected |
|---|---|---|---|---|
Programs/P02_VariableScope.py |
Modified ( +2/ -0) | Added a print statement inside the test function and a blank line at the end of the file. | Low – The changes are primarily for logging/debugging and do not alter the core logic of the variable scope demonstration. | 1 |
Test001/P10_LCM.py |
Added ( +19/ -0) | Added a script to calculate the Least Common Multiple (LCM) of two user-provided numbers using an iterative approach. | Medium – The script provides a functional LCM calculator but contains a logic flaw that causes a crash when one of the inputs is zero. | 1 |
Test001/P11_BinaryToDecimal.py |
Added ( +17/ -0) | Added a script to convert binary numbers to their decimal equivalents using a mathematical approach. | Low – The script provides a basic utility for binary-to-decimal conversion but lacks robust input validation for non-binary digits. | 1 |
Test001/P12_DecimalToBinary.py |
Added ( +13/ -0) | Added a recursive function to convert decimal numbers to binary and a main execution block for user input. | Low – The script provides a basic utility for decimal-to-binary conversion but lacks robust error handling for non-integer inputs. | 1 |
Test001/P13_Palindrome.py |
Added ( +14/ -0) | Added a Python script to check if a given string is a palindrome. | Low – This is a standalone utility script for string manipulation and does not affect core system functionality. | 1 |
Test001/P14_CheckGreater.py |
Added ( +15/ -0) | Added a script to check if a user-provided number is greater than all elements in a predefined list. | Low – The script provides basic comparison logic but contains a logical flaw in its feedback message. | 1 |
Test001/P15_Arguments.py |
Added ( +17/ -0) | Added a script to demonstrate command-line argument handling using the sys module. | Low – This is a standalone demonstration script with minimal impact on other system components. | 1 |
Test001/P16_CountVowels.py |
Added ( +17/ -0) | Added a script to count vowels in a user-provided string using a function and a loop. | Low – This is a standalone utility script for counting vowels and does not affect core application logic. | 1 |
Test001/P17_EvenOdd.py |
Added ( +19/ -0) | Added a script that takes space-separated numbers from user input and categorizes them into even and odd lists. | Low – This is a standalone utility script for basic number categorization. | 1 |
Test001/P18_Logging.py |
Added ( +22/ -0) | Added a script demonstrating basic logging and exception handling for parity checks on user input. | Medium – The script introduces logging and input handling, but contains logic errors in configuration and exception handling that affect reliability. | 2 |
Test001/P19_SimpleStopWatch.py |
Added ( +45/ -0) | Added a simple stopwatch script that uses keyboard interrupts to calculate elapsed time. | Medium – The script provides basic stopwatch functionality but contains a logic error regarding variable initialization that will cause a crash if interrupted prematurely. | 1 |
Test001/P20_OsModule.py |
Added ( +13/ -0) | Added a script demonstrating basic os module operations including directory creation and renaming in a loop. | Medium – The script performs file system operations (mkdir, rename) which could fail if the environment is not prepared or if run multiple times. | 2 |
Test001/P21_GuessTheNumber.py |
Added ( +24/ -0) | Added a simple 'Guess the Number' game where the user tries to guess a randomly generated number between 0 and 21. | Low – This is a standalone script for a simple game and does not affect other parts of the system. | 2 |
Test001/P22_SequentialSearch.py |
Added ( +23/ -0) | Implementation of a sequential search algorithm with iteration tracking. | Low – Adds a basic search utility; however, the use of global state for iteration tracking makes it non-thread-safe and prone to side effects. | 1 |
Test001/P23_BinarySearch.py |
Added ( +29/ -0) | Implementation of a standard binary search algorithm with an iteration counter. | Low – Adds a utility function for binary search; however, the use of a global variable for iteration counting makes it non-thread-safe and prone to side effects. | 1 |
Test001/P24_SelectionSort.py |
Added ( +21/ -0) | Added a Python implementation of the Selection Sort algorithm with a main execution block. | Low – The change adds a standalone sorting utility script. It does not affect existing application logic but provides a new functional component. | 0 |
Test001/P25_BubbleSort.py |
Added ( +24/ -0) | Added a standard implementation of the Bubble Sort algorithm in Python. | Low – This is a standalone utility script for educational purposes and does not affect core system functionality. | 1 |
Test001/P26_InsertionSort.py |
Added ( +25/ -0) | Implementation of the Insertion Sort algorithm in Python. | Medium – Adds a sorting utility function. The current implementation has a logical flaw in the inner loop that affects correctness and efficiency. | 1 |
Test001/P27_MergeSort.py |
Added ( +42/ -0) | Implementation of the Merge Sort algorithm with a helper merge function. | Medium – The implementation uses an inefficient list removal method during the merge process, which negatively impacts the time complexity of the algorithm. | 1 |
Test001/P28_QuickSort.py |
Added ( +65/ -0) | Added two implementations of the QuickSort algorithm: a standard in-place version and a more Pythonic list-comprehension based version. | Medium – Provides sorting utility functions. The in-place version is memory efficient but the 'quicksortBetter' version uses significant extra memory. | 1 |
Test001/P29_ArgumentParser.py |
Added ( +21/ -0) | Added a Python script demonstrating the use of the argparse module to handle command-line arguments. | Low – This is a standalone example script and does not affect existing application functionality. | 1 |
Test001/P30_Array.py |
Added ( +107/ -0) | Implementation of a static-sized Array class in Python with basic insertion, deletion, and search operations. | Medium – Provides a custom array implementation that mimics static arrays, but contains several logical flaws in insertion and search logic. | 4 |
Test002/P01_hello.py |
Added ( +29/ -0) | Added a new Python script that performs basic arithmetic operations based on user input. | Medium – The script introduces interactive input and arithmetic logic, but lacks error handling for non-numeric inputs which will cause runtime crashes. | 1 |
Test002/P02_VariableScope.py |
Added ( +18/ -0) | Added a Python script demonstrating variable scope rules (LEGB). | Low – This is an educational script with no impact on core application functionality. | 0 |
Test002/P03_ListsOperations.py |
Added ( +48/ -0) | Added a Python script demonstrating various list operations including slicing, appending, sorting, popping, removing, inserting, counting, extending, and reversing. | Low – This is an educational or utility script demonstrating list operations. It does not affect core application logic but contains a potential runtime error if the list state changes. | 1 |
Test002/P04_Factorial.py |
Added ( +17/ -0) | Added a recursive factorial calculation script with basic input handling. | Medium – The script provides a functional factorial calculator but contains logic flaws regarding negative numbers and recursion depth. | 2 |
Test002/P05_Pattern.py |
Added ( +112/ -0) | Added a Python script containing multiple functions to print various star patterns and a main execution block. | Low – The changes introduce basic pattern printing logic which is primarily for educational or demonstration purposes. | 3 |
Test002/P06_CharCount.py |
Added ( +18/ -0) | Added a script to calculate character frequency in a given string using a dictionary. | Low – The script provides basic character counting functionality but contains a minor inefficiency in dictionary key checking. | 1 |
Test002/P07_PrimeNumber.py |
Added ( +23/ -0) | Added a script to check if a given number is prime. | Medium – The script provides a functional prime number check but contains logical flaws for specific inputs like the number 2. | 1 |
Test002/P08_Fibonacci.py |
Added ( +24/ -0) | Added two implementations of Fibonacci series calculation: one recursive and one iterative, along with a main block for user interaction. | Medium – The changes introduce core mathematical logic for Fibonacci calculations. The recursive implementation has significant performance risks for larger inputs. | 1 |
![appmod-pr-genie[bot]](https://avatars.githubusercontent.com/u/178300120?s=60&v=4){kind=small}
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| def LCM(number1, number2): | ||
| '''This function calculates LCM of two numbers inputed by the user''' | ||
| maximum = max(number1, number2) |
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Division by Zero Risk
I noticed that if a user enters '0' as one of the numbers, the program will crash with a ZeroDivisionError during the modulo operation. We should add a check to handle zero inputs, as the LCM of any number and zero is typically defined as zero or undefined depending on the context.
| maximum = max(number1, number2) | |
| if number1 == 0 or number2 == 0: | |
| return 0 | |
| maximum = max(number1, number2) |
| while(binary != 0): | ||
| dec = binary % 10 | ||
| decimal = decimal + dec * pow(2, i) |
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Missing Validation for Non-Binary Digits
I noticed that the current implementation doesn't check if the input contains digits other than 0 or 1. If a user enters a number like '123', the logic will still process it as if it were binary, leading to mathematically incorrect results. We should add a check to ensure the input is a valid binary number before processing.
| while(binary != 0): | |
| dec = binary % 10 | |
| decimal = decimal + dec * pow(2, i) | |
| while(binary != 0): | |
| dec = binary % 10 | |
| if dec not in (0, 1): | |
| print('Invalid binary number') | |
| return | |
| decimal = decimal + dec * pow(2, i) |
| userInput = int(input('Enter the decimal number to find its binary equivalent: ')) | ||
| decimalToBinary(userInput) |
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Potential Runtime Error: Missing Input Validation
I notice we're directly casting the user input to an integer. If a user enters a non-numeric string or a float, the program will crash with a ValueError. We should wrap this in a try-except block to handle invalid inputs gracefully.
| userInput = int(input('Enter the decimal number to find its binary equivalent: ')) | |
| decimalToBinary(userInput) | |
| try: | |
| userInput = int(input('Enter the decimal number to find its binary equivalent: ')) | |
| decimalToBinary(userInput) | |
| except ValueError: | |
| print('Invalid input! Please enter a valid integer.') |
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| def palindrome(string): | ||
| '''This function checks the string for palindrome''' | ||
| revString = string[::-1] |
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Case-Sensitive Palindrome Check
I notice the current implementation performs a case-sensitive check. This means 'Level' would not be recognized as a palindrome because 'L' and 'l' are different characters. We should normalize the string to lowercase to ensure the check works as expected for all inputs.
| revString = string[::-1] | |
| string = string.lower() | |
| revString = string[::-1] |
| if number > original[-1]: | ||
| print('Yes, the entered number is greater than those in the list') | ||
| else: | ||
| print('No, entered number is less than those in the list') |
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Inaccurate Logic in Failure Message
I noticed a small logic issue in the else block. If the entered number is equal to the largest number in the list, the current message says it is 'less than', which is technically incorrect. We should update the message to accurately reflect that the number is 'less than or equal to' the list elements to avoid confusing the user.
| print('No, entered number is less than those in the list') | |
| print('No, entered number is less than or equal to those in the list') |
| if int(number) % 2 == 0: | ||
| even.append(number) | ||
| else: | ||
| odd.append(number) |
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Potential Runtime Error on Non-Numeric Input
I noticed that we're calling int(number) directly on user input without any validation. If a user accidentally enters a letter or a special character instead of a number, the program will crash with a ValueError. It would be much safer to check if the input is numeric before attempting the conversion to ensure the script doesn't fail unexpectedly.
| if int(number) % 2 == 0: | |
| even.append(number) | |
| else: | |
| odd.append(number) | |
| try: | |
| num = int(number) | |
| if num % 2 == 0: | |
| even.append(number) | |
| else: | |
| odd.append(number) | |
| except ValueError: | |
| continue |
Reasons & Gaps
Reasons
- Direct type casting of unvalidated user input causes immediate runtime crashes
- ValueError is raised when non-numeric strings are passed to the int() constructor
- Missing error handling prevents the script from processing remaining valid numbers
Gaps
- The intended use case might strictly assume valid integer inputs from a controlled source
- Adding try-except blocks might slightly change the function's return behavior for invalid data
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| def log(number): | ||
| ''' This function creates a log file if any error is reported ''' | ||
| logging.basicConfig(filename = 'P18-logfile.txt', level = logging.INFO) |
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Ineffective Logging Configuration
I notice that logging.basicConfig is called inside the log function. In Python, basicConfig only configures the logger if it hasn't been configured yet. If this function is called multiple times, subsequent calls will be ignored, which might lead to unexpected logging behavior if other parts of the app try to reconfigure it. It's generally better to configure logging at the module level or once at the start of the application.
Reasons & Gaps
Reasons
- basicConfig is a one-time configuration call that ignores subsequent invocations
- Placing configuration inside a function prevents consistent logging across the module
- Can lead to silent failures where log settings are not applied as expected
Gaps
- The script is small and likely standalone, making the impact of repeated configuration calls negligible in this specific context.
- Standard logging behavior in simple scripts often involves local configuration despite best practices.
| else: | ||
| print('Unsuccessful, this instance will be reported, check the log file') | ||
| logging.info('Invalid Entry') | ||
| except: |
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Bare Exception Clause
I see we're using a bare except: block here. This is a bit risky because it catches every possible exception, including KeyboardInterrupt or SystemExit, which can make it hard for a user to stop the program. It's safer to catch specific errors like ValueError or TypeError so we only handle the issues we actually expect.
| except: | |
| except (ValueError, TypeError): |
| try: | ||
| input() #For ENTER | ||
| starttime = time.time() | ||
| print('Started') |
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Potential UnboundLocalError on Interrupt
I notice that if a user presses Ctrl + C before the first input() is resolved, the starttime variable won't be defined. This will cause the program to crash when it tries to access starttime in the except block. We should initialize starttime before the try block or handle the case where it hasn't been set yet.
| try: | |
| input() #For ENTER | |
| starttime = time.time() | |
| print('Started') | |
| starttime = time.time() | |
| try: | |
| input() #For ENTER | |
| print('Started') |
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| print(os.getcwd()) #Prints the current working directory | ||
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| os.mkdir('newDir1') |
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Potential Crash: Directory Already Exists
I notice we're calling os.mkdir('newDir1') without checking if it already exists. If this script is run a second time, it will throw an FileExistsError and crash. We should add a check or use exist_ok=True if using os.makedirs to make this more robust.
| os.mkdir('newDir1') | |
| if not os.path.exists('newDir1'): | |
| os.mkdir('newDir1') |
| os.mkdir('newDir1') | ||
| for i in range(1,10): | ||
| print('Here i is',i) | ||
| os.rename('newDir' + str(i),'newDir' + str(i + 1)) |
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Logic Error: Renaming Non-Existent Directories
In the loop, we're trying to rename newDir1 to newDir2, then newDir2 to newDir3, and so on. However, we only created newDir1 outside the loop. On the second iteration (i=2), the script will look for newDir2 to rename it, but it won't find it because the previous iteration already moved it. This will cause a FileNotFoundError.
| os.mkdir('newDir1') | |
| for i in range(1,10): | |
| print('Here i is',i) | |
| os.rename('newDir' + str(i),'newDir' + str(i + 1)) | |
| os.mkdir('newDir1') | |
| for i in range(1, 10): | |
| print('Here i is', i) | |
| new_name = 'newDir' + str(i + 1) | |
| os.rename('newDir' + str(i), new_name) | |
| time.sleep(2) |
Reasons & Gaps
Reasons
- The loop logic assumes source directories exist for every value of i
- Only the first directory is created, leading to FileNotFoundError on i=2
- Breaks the functional flow of the program immediately after the first step
Gaps
- The intended logic might be to create a new directory in each iteration
- The current implementation suggests a chain of renames on a single entity
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| while True: | ||
| count += 1 | ||
| number = int(input('Enter the number between 0 to 20: ')) |
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Range Mismatch in User Prompt
I noticed that the random number is generated between 0 and 21 (inclusive), but the prompt tells the user to enter a number between 0 and 20. This could be confusing if the secret number happens to be 21, as the user wouldn't know to guess it. We should align the prompt with the actual range being used.
| number = int(input('Enter the number between 0 to 20: ')) | |
| number = int(input('Enter the number between 0 to 21: ')) |
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| while True: | ||
| count += 1 | ||
| number = int(input('Enter the number between 0 to 20: ')) |
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Potential Runtime Crash on Invalid Input
Right now, if a user accidentally enters something that isn't a number (like a letter or a symbol), the program will crash with a ValueError. Since this is an interactive game, it would be much better to handle that gracefully so the user can try again without the script stopping.
| number = int(input('Enter the number between 0 to 20: ')) | |
| try: | |
| number = int(input('Enter the number between 0 to 21: ')) | |
| except ValueError: | |
| print('Please enter a valid integer.') | |
| continue |
Reasons & Gaps
Reasons
- Calling int() on non-numeric string input raises a ValueError exception
- Unhandled exceptions cause the Python interpreter to terminate immediately
- Robust CLI applications should validate user input to prevent unexpected crashes
Gaps
- The fix requires a multi-line block which might slightly change the loop structure
- Error handling preferences can vary between simple scripts and production code
| while position < len(List): | ||
| iterations += 1 | ||
| if target == List[position]: | ||
| return position |
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Global State for Iteration Tracking
I notice we're using a global variable iterations to track the search progress. This can lead to unexpected behavior if the function is called multiple times in a larger system or in a multi-threaded environment, as the state is shared globally. It's generally safer to return the iteration count along with the result or encapsulate it within a class.
| return position | |
| return position, iterations |
Reasons & Gaps
Reasons
- Global variables create hidden dependencies between different parts of the code
- Shared state makes the function non-reentrant and difficult to test in isolation
- Returning multiple values is the standard Pythonic way to handle auxiliary metadata
Gaps
- The script appears to be a standalone educational example where global variables are common
- Thread safety might not be a requirement for this specific script's context
| global iterations | ||
| iterations = 0 |
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Global State for Iteration Counter
I notice we're using a global variable iterations to track the search count. This can lead to unexpected behavior if the function is called multiple times or in a multi-threaded environment, as the state is shared globally. It's generally safer to return the iteration count along with the result or use a class to encapsulate the state.
Reasons & Gaps
Reasons
- Global variables create hidden dependencies between different parts of the program
- Makes the function non-reentrant and difficult to test in isolation
- Concurrent calls to binarySearch will overwrite the shared iterations value
Gaps
- The script appears to be a standalone example where global state might be intentional for simplicity
- In a small script, thread safety is rarely a concern, but it remains a poor architectural pattern
| while len(a) != 0 and len(b) != 0: | ||
| if a[0] < b[0]: | ||
| c.append(a[0]) | ||
| a.remove(a[0]) | ||
| else: | ||
| c.append(b[0]) | ||
| b.remove(b[0]) | ||
| if len(a) == 0: | ||
| c += b | ||
| else: | ||
| c += a |
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Performance Issue: Inefficient List Removal
I notice we're using a.remove(a[0]) and b.remove(b[0]) inside the merge loop. In Python, list.remove() or pop(0) are O(n) operations because they require shifting all subsequent elements. This turns our O(n log n) merge sort into O(n² log n). We can fix this by using indices to track our position in the lists, which keeps the merge step at O(n).
| while len(a) != 0 and len(b) != 0: | |
| if a[0] < b[0]: | |
| c.append(a[0]) | |
| a.remove(a[0]) | |
| else: | |
| c.append(b[0]) | |
| b.remove(b[0]) | |
| if len(a) == 0: | |
| c += b | |
| else: | |
| c += a | |
| i = j = 0 | |
| while i < len(a) and j < len(b): | |
| if a[i] < b[j]: | |
| c.append(a[i]) | |
| i += 1 | |
| else: | |
| c.append(b[j]) | |
| j += 1 | |
| c.extend(a[i:]) | |
| c.extend(b[j:]) |
| def quicksortBetter(arr): | ||
| if len(arr) <= 1: | ||
| return arr | ||
| pivot = arr[len(arr) // 2] |
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Potential Recursion Depth Error
I notice that the quicksortBetter implementation uses a fixed pivot (the middle element). While this works for many cases, if the input list is already sorted or nearly sorted, this specific pivot selection can still lead to O(n^2) performance and potential RecursionError for very large lists. For a more robust implementation, we should consider using a random pivot or the median-of-three approach to ensure better average-case performance.
| pivot = arr[len(arr) // 2] | |
| import random | |
| pivot = random.choice(arr) |
Reasons & Gaps
Reasons
- Fixed pivot selection leads to worst-case O(n^2) complexity on specific patterns
- Deep recursion on sorted arrays can trigger a RecursionError in Python
- Random pivot selection significantly reduces the probability of hitting worst-case
Gaps
- The impact depends on the size and distribution of input data which is not visible here
- Python's default recursion limit might be sufficient for the intended use case
| if(arg.slowbros): | ||
| slowBros() | ||
| else: | ||
| print('Dude give some arguments! Type ArgumentParser -h for more details') |
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JAS - Just a suggestion
Incorrect Help Message Reference
The print statement suggests running ArgumentParser -h, but the script's filename is P29_ArgumentParser.py. This might confuse users trying to find help for the command.
| print('Dude give some arguments! Type ArgumentParser -h for more details') | |
| print('Dude give some arguments! Type python P29_ArgumentParser.py -h for more details') |
| for i in range(self.myLen(), 0, -1): | ||
| self.items[i] = self.items[i - 1] |
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Incorrect Insertion Logic in insertFirst
In the insertFirst method, the loop range range(self.myLen(), 0, -1) will correctly shift elements, but it relies on myLen() which only counts non-None elements. If the array has gaps (None values) in the middle due to deletions, myLen() will return a value smaller than the actual index of the last element, causing data corruption or overwriting existing elements during the shift.
| for i in range(self.myLen(), 0, -1): | |
| self.items[i] = self.items[i - 1] | |
| for i in range(self.size - 1, 0, -1): | |
| self.items[i] = self.items[i - 1] |
| for i in range(self.myLen(), index - 1, -1): | ||
| self.items[i] = self.items[i - 1] | ||
| self.items[index - 1] = element |
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Off-by-One Error in insertBeforeIndex
In insertBeforeIndex, the loop range(self.myLen(), index - 1, -1) and the subsequent assignment to self.items[index - 1] will fail if index is 0, as it attempts to access index -1. Furthermore, inserting 'before' an index usually implies shifting elements from that index onwards, not just the one before it.
| for i in range(self.myLen(), index - 1, -1): | |
| self.items[i] = self.items[i - 1] | |
| self.items[index - 1] = element | |
| for i in range(self.size - 1, index, -1): | |
| self.items[i] = self.items[i - 1] | |
| self.items[index] = element |
Reasons & Gaps
Reasons
- Accessing index -1 causes incorrect behavior or unexpected assignments
- Logic incorrectly shifts elements based on count rather than index position
- Does not handle the boundary case where index is 0 correctly
Gaps
- The intended behavior of 'insertBeforeIndex' is ambiguous compared to 'insertAtIndex'
- Current implementation specifically targets index-1 which is highly prone to errors
| def search(self, element): | ||
| if element in self.items: | ||
| position = 0 | ||
| for i in range(self.myLen()): |
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Incomplete Search Logic
The search method iterates up to self.myLen(). If the array contains None values (e.g., after a delete operation), myLen() will be less than the actual index of elements stored later in the array. This means the search will stop prematurely and fail to find existing elements.
| for i in range(self.myLen()): | |
| for i in range(self.size): |
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| def insertAfterIndex(self, index, element): | ||
| ''' This function adds the element to the beginning of the array ''' | ||
| if (self.myLen() < self.size): |
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Potential IndexError in insertAfterIndex
In insertAfterIndex, if index is the last valid index of the array (self.size - 1), index + 1 will be out of bounds, causing a runtime IndexError when attempting to assign the element.
| if (self.myLen() < self.size): | |
| if (self.myLen() < self.size and index < self.size - 1): |
| print("Divide value is:", divide_value) | ||
| print("Multiply value is:", multiply_value) | ||
| print("Modulus:", increment_value % base_value ) # % -> remainder | ||
| print('Addition is:', int(a) + int(b)) |
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Potential Runtime Crash: Missing Input Validation
I notice we're directly casting a and b to integers. If a user enters something that isn't a number (like a string or special character), the program will crash with a ValueError. We should wrap this in a try-except block or validate the input first to make the script more robust.
| print('Addition is:', int(a) + int(b)) | |
| try: | |
| print('Addition is:', int(a) + int(b)) | |
| except ValueError: | |
| print('Error: Please enter valid numeric values.') |
| print('Poped Element:',myList.pop()) | ||
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| #To remove a particular element from the lsit BY NAME | ||
| myList.remove(6) |
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Potential ValueError in List Removal
I noticed we're calling myList.remove(6) here. While '6' exists in the initial list, the previous myList.pop() at line 29 removes the last element. If the list were shorter or if '6' was the last element, this call would raise a ValueError. It's safer to check if the element exists before attempting to remove it by value.
| myList.remove(6) | |
| if 6 in myList: | |
| myList.remove(6) |
Reasons & Gaps
Reasons
- The remove() method raises a ValueError if the specified value is not found
- Previous operations like pop() modify the list state unpredictably
- Checking existence prevents runtime crashes during data manipulation
Gaps
- The script is a static example where the list content is predictable
- In a dynamic environment, the list state could change between operations
| if number < 0: | ||
| print('Invalid entry! Cannot find factorial of a negative number') |
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Logic Error: Negative Number Handling
I noticed that when a negative number is entered, the function prints an error message but then continues to execute the recursive logic. This will lead to a RecursionError (maximum recursion depth exceeded) because the number will keep decreasing indefinitely. We should return early or raise an exception when an invalid input is detected.
| if number < 0: | |
| print('Invalid entry! Cannot find factorial of a negative number') | |
| if number < 0: | |
| print('Invalid entry! Cannot find factorial of a negative number') | |
| return None |
| pattern5(userInput) | ||
| print() | ||
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| def pattern6(userInput): |
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Nested Function Definition and Missing Call
It looks like pattern6 is defined inside the main block but is never actually called. Additionally, defining functions inside the main block is generally less maintainable than defining them at the module level. We should move the definition outside and ensure it's called if intended.
Reasons & Gaps
Reasons
- Function is defined but never executed, resulting in dead code in the main block
- Nested definitions limit reusability and make the main execution block cluttered
- Moving it to module level follows standard Python structure for better clarity
Gaps
- The developer might have intended to keep it as a local helper function
- The lack of a call might be intentional if the code is still in progress
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| ''' | ||
| # first loop for number of lines | ||
| for i in range(level + 1): |
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Off-by-one Error in pattern5
In pattern5, the loop for printing stars range(2 * i - 1) will attempt to print -1 stars when i is 0 (the first iteration of range(level + 1)). While Python handles range(-1) gracefully by doing nothing, it results in an empty line at the start of the pattern which doesn't match the intended docstring visualization. Starting the range from 1 would fix this.
| for i in range(level + 1): | |
| for i in range(1, level + 1): |
| keys = dict.keys() | ||
| if char in keys: |
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Inefficient Dictionary Key Lookup
I noticed we're calling dict.keys() inside the loop to check for character existence. In Python, checking membership directly in the dictionary (char in dict) is more efficient and idiomatic, as it uses the hash map directly rather than creating a view object in every iteration.
| keys = dict.keys() | |
| if char in keys: | |
| if char in dict: |
| isPrime = False | ||
| if number == 2: | ||
| print(number, 'is a Prime Number') | ||
| if number > 1: | ||
| for i in range(2, number): | ||
| if number % i == 0: | ||
| print(number, 'is not a Prime Number') | ||
| isPrime = False | ||
| break | ||
| else: | ||
| isPrime = True | ||
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| if isPrime: | ||
| print(number, 'is a Prime Number') |
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Redundant and Conflicting Logic for Number 2
I noticed that when the input is 2, the code prints that it's a prime number twice. This happens because line 7 handles it explicitly, but line 9 also triggers since 2 > 1. Inside the loop at line 10, range(2, 2) is empty, so isPrime remains False (from line 6), but then line 18 doesn't execute. Wait, actually, if number is 2, the loop doesn't run, isPrime stays False, and only the first print executes. However, for other primes, isPrime becomes True. The logic is a bit tangled. Let's simplify this by handling the edge case and the loop more cleanly.
| isPrime = False | |
| if number == 2: | |
| print(number, 'is a Prime Number') | |
| if number > 1: | |
| for i in range(2, number): | |
| if number % i == 0: | |
| print(number, 'is not a Prime Number') | |
| isPrime = False | |
| break | |
| else: | |
| isPrime = True | |
| if isPrime: | |
| print(number, 'is a Prime Number') | |
| if number <= 1: | |
| print(number, 'is not a Prime Number') | |
| return | |
| for i in range(2, int(number**0.5) + 1): | |
| if number % i == 0: | |
| print(number, 'is not a Prime Number') | |
| return | |
| print(number, 'is a Prime Number') |
| if __name__ == '__main__': | ||
| userInput = int(input('Enter the number upto which you wish to calculate fibonnaci series: ')) | ||
| for i in range(userInput + 1): | ||
| print(fibonacci(i),end=' ') |
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Performance Risk: Exponential Time Complexity in Recursion
I notice we're using a simple recursive approach for the Fibonacci calculation. While it's mathematically elegant, it has O(2^n) time complexity, which will cause the application to hang or crash with a RecursionError for even moderately large inputs (e.g., n > 35). Since we already have an efficient iterative version, we should use that in the loop to ensure the program remains responsive.
| print(fibonacci(i),end=' ') | |
| print(fibonacci_without_recursion(i),end=' ') |
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Variable naming convention |
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JAS - Just a suggestion
🗂️ Test001/P11_BinaryToDecimal.py
| Coding Standard | Violations | Citation |
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Misleading Function Name |
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Variable naming convention |
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JAS - Just a suggestion
🗂️ Test001/P12_DecimalToBinary.py
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Variable naming convention |
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Variable naming convention |
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Misleading Function Name |
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JAS - Just a suggestion
🗂️ Test001/P13_Palindrome.py
| Coding Standard | Violations | Citation |
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Variable naming convention |
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Misleading Function Name |
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JAS - Just a suggestion
🗂️ Test001/P14_CheckGreater.py
| Coding Standard | Violations | Citation |
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Misleading Function Name |
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Variable naming convention |
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Variable naming convention |
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JAS - Just a suggestion
🗂️ Test001/P15_Arguments.py
| Coding Standard | Violations | Citation |
|---|---|---|
Function naming convention |
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JAS - Just a suggestion
🗂️ Test001/P16_CountVowels.py
| Coding Standard | Violations | Citation |
|---|---|---|
Function naming convention |
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Variable naming convention |
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JAS - Just a suggestion
🗂️ Test001/P17_EvenOdd.py
| Coding Standard | Violations | Citation |
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Misleading Function Name |
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Variable naming convention |
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JAS - Just a suggestion
🗂️ Test001/P18_Logging.py
| Coding Standard | Violations | Citation |
|---|---|---|
Misleading Function Name |
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Variable naming convention |
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JAS - Just a suggestion
🗂️ Test001/P19_SimpleStopWatch.py
| Coding Standard | Violations | Citation |
|---|---|---|
Variable naming convention |
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JAS - Just a suggestion
🗂️ Test001/P20_OsModule.py
| Coding Standard | Violations | Citation |
|---|---|---|
Variable naming convention |
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JAS - Just a suggestion
🗂️ Test001/P21_GuessTheNumber.py
| Coding Standard | Violations | Citation |
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Variable naming convention |
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Function naming convention |
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JAS - Just a suggestion
🗂️ Test001/P22_SequentialSearch.py
| Coding Standard | Violations | Citation |
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Variable naming convention |
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Variable naming convention |
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Misleading Function Name |
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JAS - Just a suggestion
🗂️ Test001/P23_BinarySearch.py
| Coding Standard | Violations | Citation |
|---|---|---|
Function naming convention |
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Variable naming convention |
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Variable naming convention |
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JAS - Just a suggestion
🗂️ Test001/P24_SelectionSort.py
| Coding Standard | Violations | Citation |
|---|---|---|
Function naming convention |
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Variable naming convention |
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JAS - Just a suggestion
🗂️ Test001/P25_BubbleSort.py
| Coding Standard | Violations | Citation |
|---|---|---|
Function naming convention |
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Variable naming convention |
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JAS - Just a suggestion
🗂️ Test001/P26_InsertionSort.py
| Coding Standard | Violations | Citation |
|---|---|---|
Function naming convention |
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Variable naming convention |
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JAS - Just a suggestion
🗂️ Test001/P27_MergeSort.py
| Coding Standard | Violations | Citation |
|---|---|---|
Variable naming convention |
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Function naming convention |
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JAS - Just a suggestion
🗂️ Test001/P28_QuickSort.py
| Coding Standard | Violations | Citation |
|---|---|---|
Function naming convention |
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Variable naming convention |
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JAS - Just a suggestion
🗂️ Test001/P29_ArgumentParser.py
| Coding Standard | Violations | Citation |
|---|---|---|
Function naming convention |
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Variable naming convention |
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JAS - Just a suggestion
🗂️ Test001/P30_Array.py
| Coding Standard | Violations | Citation |
|---|---|---|
Variable naming convention |
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Misleading Function Name |
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Variable naming convention |
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JAS - Just a suggestion
🗂️ Test002/P01_hello.py
| Coding Standard | Violations | Citation |
|---|---|---|
Variable naming convention |
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Function naming convention |
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JAS - Just a suggestion
🗂️ Test002/P02_VariableScope.py
| Coding Standard | Violations | Citation |
|---|---|---|
Variable naming convention |
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Function naming convention |
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JAS - Just a suggestion
🗂️ Test002/P03_ListsOperations.py
| Coding Standard | Violations | Citation |
|---|---|---|
Variable naming convention |
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JAS - Just a suggestion
🗂️ Test002/P04_Factorial.py
| Coding Standard | Violations | Citation |
|---|---|---|
Variable naming convention |
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Variable naming convention |
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JAS - Just a suggestion
🗂️ Test002/P05_Pattern.py
| Coding Standard | Violations | Citation |
|---|---|---|
Variable naming convention |
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Variable naming convention |
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JAS - Just a suggestion
🗂️ Test002/P06_CharCount.py
| Coding Standard | Violations | Citation |
|---|---|---|
Function naming convention |
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Variable naming convention |
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Variable naming convention |
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JAS - Just a suggestion
🗂️ Test002/P07_PrimeNumber.py
| Coding Standard | Violations | Citation |
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Misleading Function Name |
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Variable naming convention |
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JAS - Just a suggestion
🗂️ Test002/P08_Fibonacci.py
| Coding Standard | Violations | Citation |
|---|---|---|
Variable naming convention |
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JAS - Just a suggestion
| #Author: OMKAR PATHAK | ||
| #This program calculates the LCM of the two numbers entered by the user | ||
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| def LCM(number1, number2): |
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Function Naming Convention
The function name 'LCM' uses all uppercase letters, which violates Python's snake_case naming convention. It should be renamed to something more descriptive and idiomatic like 'calculate_lcm'.
| def LCM(number1, number2): | |
| def calculate_lcm(number1, number2): |
Reasons & Gaps
Reasons
- Python naming conventions (PEP 8) require function names to be in lowercase snake_case
- 'calculate_lcm' explicitly describes the action being performed by the function
- Improves consistency with standard Python library naming patterns
Gaps
- LCM is a well-known mathematical acronym which might be considered acceptable in some scientific contexts
- The project might not strictly enforce PEP 8 snake_case for mathematical abbreviations
| def LCM(number1, number2): | ||
| '''This function calculates LCM of two numbers inputed by the user''' | ||
| maximum = max(number1, number2) | ||
| i = maximum |
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Single-Character Variable Name
The variable name 'i' is used here as a tracking value for the LCM calculation rather than a simple loop counter. Using a more descriptive name like 'current_multiple' would improve code clarity.
| i = maximum | |
| current_multiple = maximum |
Reasons & Gaps
Reasons
- Single-letter names (except for simple loop indices) increase cognitive load for maintainers
- 'current_multiple' clearly indicates the variable's role in the LCM search logic
- Descriptive names make the algorithm's intent self-documenting without needing extra comments
Gaps
- 'i' is commonly used for integers in mathematical algorithms without causing significant confusion
- The scope of the variable is very small, making its purpose relatively easy to trace
| return lcm | ||
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| if __name__ == '__main__': | ||
| userInput1 = int(input('Enter first number: ')) |
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Variable Naming Refinement
The variable 'userInput1' uses camelCase, which is inconsistent with Python's snake_case convention. Additionally, 'first_number' would be more descriptive of the data's role.
| userInput1 = int(input('Enter first number: ')) | |
| first_number = int(input('Enter first number: ')) |
Reasons & Gaps
Reasons
- CamelCase (userInput1) deviates from the standard Python snake_case (user_input_1) convention
- 'first_number' is more semantically accurate than the generic 'userInput1'
- Consistent naming styles across the file improve professional code quality
Gaps
- The name is functional and understandable, making this a low-priority refinement
- Some developers prefer camelCase if they are coming from Java or JavaScript backgrounds
| #Author: OMKAR PATHAK | ||
| #This program converts the given binary number to its decimal equivalent | ||
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| def binaryToDecimal(binary): |
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Boolean-Returning Function Without Prefix
The function name 'binaryToDecimal' uses camelCase which is non-idiomatic in Python. Additionally, if this function were to return a boolean check, it would require a prefix like 'is_'. However, per Python standards (PEP 8), function names should be snake_case.
| def binaryToDecimal(binary): | |
| def binary_to_decimal(binary): |
Reasons & Gaps
Reasons
- Python naming conventions (PEP 8) require function names to be in snake_case
- camelCase is typically reserved for other languages like Java or JavaScript
- Consistent naming improves maintainability and follows community standards
Gaps
- The standard CS-2 focuses on boolean prefixes and vague verbs; while this is a naming convention issue, it fits the 'incorrect case' criteria
- Python functions should strictly follow snake_case per PEP 8 guidelines
| def binaryToDecimal(binary): | ||
| '''This function calculates the decimal equivalent to given binary number''' | ||
| binary1 = binary | ||
| decimal, i, n = 0, 0, 0 |
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Single-Character Variable Names
The variables 'i' and 'n' are single-character names. While 'i' is often used as a loop counter, 'n' is unused in the provided logic and both should be more descriptive to improve code clarity.
| decimal, i, n = 0, 0, 0 | |
| decimal, power_index = 0, 0 |
Reasons & Gaps
Reasons
- Single-letter variables (except in specific loop contexts) reduce code readability
- Descriptive names like 'power_index' explain the variable's role in the binary conversion
- Removing unused variables like 'n' reduces cognitive load and potential for bugs
Gaps
- 'i' is a common convention for indices, but 'power_index' is more descriptive in this mathematical context
- 'n' is initialized but never used in the visible logic
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| def palindrome(string): | ||
| '''This function checks the string for palindrome''' | ||
| revString = string[::-1] |
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Variable Naming Convention
The variable name 'revString' uses camelCase, which is not the standard naming convention for Python. Following PEP 8, variable names should use snake_case (e.g., 'reversed_string').
| revString = string[::-1] | |
| reversed_string = string[::-1] |
Reasons & Gaps
Reasons
- Python naming conventions (PEP 8) require snake_case for variable names
- Using 'rev' as a prefix is a mixed abbreviation pattern that reduces clarity
- Consistent naming styles across the module improve long-term maintainability
Gaps
- The term 'rev' is a common clipping for 'reversed' but 'reversed_string' is more expressive
- Project-specific style guides might occasionally allow camelCase in Python for consistency with other languages
| print('String is not Palindrome') | ||
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| if __name__ == '__main__': | ||
| userInput = str(input('Enter a string to check for Palindrome: ')) |
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Variable Naming Convention
The variable name 'userInput' uses camelCase. In Python, the standard convention for variables is snake_case. Consider renaming it to 'user_input'.
| userInput = str(input('Enter a string to check for Palindrome: ')) | |
| user_input = str(input('Enter a string to check for Palindrome: ')) |
Reasons & Gaps
Reasons
- PEP 8 style guide explicitly recommends snake_case for all variable names
- Maintaining language-specific conventions reduces cognitive load for Python developers
- Standardized naming prevents mixed styles within the same codebase
Gaps
- camelCase is technically functional but violates Python-specific style standards
- The name is descriptive, so the violation is purely stylistic rather than semantic
| #Author: OMKAR PATHAK | ||
| #This program checks for the palindrome | ||
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| def palindrome(string): |
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Boolean Function Naming
Functions that check a condition and imply a boolean result should typically be prefixed with 'is_', 'has_', or 'can_'. Renaming to 'is_palindrome' makes the intent clearer.
| def palindrome(string): | |
| def is_palindrome(string): |
Reasons & Gaps
Reasons
- Function names should be verbs or verb phrases describing the action
- Predicate functions are more readable when prefixed with boolean indicators
- 'palindrome' as a name is a noun, which usually represents a variable or class
Gaps
- The function currently prints the result instead of returning a boolean
- If the intent is a CLI utility, a noun-based name might be acceptable
| #Author: OMKAR PATHAK | ||
| #This prpgram checks that the given number is greater than all those numbers in th list | ||
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| def checkGreater(number): |
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Boolean-Returning Function Without Prefix
The function returns a boolean-like result (implicit check) or performs a validation but lacks a boolean prefix like 'is_' or 'has_'. In Python, 'is_greater_than_list' would be more idiomatic.
| def checkGreater(number): | |
| def is_greater_than_list(number): |
Reasons & Gaps
Reasons
- Function names should clearly indicate if they perform a check or return a boolean value
- Adding a prefix like 'is_' improves the predictability of the function's behavior
- 'checkGreater' uses camelCase which is non-idiomatic for Python function definitions
Gaps
- The function currently prints instead of returning a boolean, making the prefix rule partially applicable
- Standard naming conventions for utility functions often vary by team preference
| print('No, entered number is less than those in the list') | ||
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| if __name__ == '__main__': | ||
| userInput = int(input('Enter the number to check: ')) |
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Non-Standard Case Convention
Python variables should use snake_case instead of camelCase. 'user_input' is the preferred naming convention for local variables in Python.
| userInput = int(input('Enter the number to check: ')) | |
| user_input = int(input('Enter the number to check: ')) |
Reasons & Gaps
Reasons
- PEP 8 specifically recommends snake_case for variable and function names in Python
- Consistent casing reduces cognitive load when switching between different Python modules
- 'user_input' aligns with standard Python library and community naming patterns
Gaps
- Project-specific style guides might allow camelCase for consistency with older codebases
- The variable name itself is descriptive, only the casing style is technically incorrect
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| def checkGreater(number): | ||
| '''This function checks whether the entered number is greater than those in the list''' | ||
| original = [1,2,3,4,5] |
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Vague Variable Name
The variable name 'original' is functional but generic. A more descriptive name like 'reference_numbers' or 'comparison_list' would better reflect its purpose in this logic.
| original = [1,2,3,4,5] | |
| reference_numbers = [1,2,3,4,5] |
Reasons & Gaps
Reasons
- 'original' does not describe what the data represents, only its state relative to changes
- Descriptive names like 'reference_numbers' explain the business logic role of the variable
- Improving semantic clarity helps maintainability as the function grows in complexity
Gaps
- In a very small function, 'original' might be considered sufficiently clear by some reviewers
- The context of the list is simple enough that ambiguity is relatively low
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| import sys | ||
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| def arguments(): |
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Vague Function Name
The function name 'arguments' is a generic noun that doesn't describe the action being performed. Renaming it to something like 'print_command_line_arguments' would better reflect its purpose.
| def arguments(): | |
| def print_command_line_arguments(): |
Reasons & Gaps
Reasons
- Function names should ideally be verbs or verb phrases describing an action
- 'arguments' is a noun and doesn't communicate that the function prints them
- Descriptive names act as documentation and reduce cognitive load for maintainers
Gaps
- The function is small and its purpose is clear from the docstring
- In a script specifically about arguments, the name might be considered contextually sufficient
| #Author: OMKAR PATHAK | ||
| #This program counts the vowels present in the user input | ||
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| def countVowels(sentence): |
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Function Naming Convention (Python)
In Python, function names should follow the snake_case convention as per PEP 8. Consider renaming countVowels to count_vowels to align with standard Python practices.
| def countVowels(sentence): | |
| def count_vowels(sentence): |
Reasons & Gaps
Reasons
- Python's PEP 8 standard explicitly recommends snake_case for function names
- Consistent naming conventions improve code searchability and developer onboarding
- camelCase is non-idiomatic in Python and deviates from standard library patterns
Gaps
- The project might be using camelCase as a local convention inherited from other languages
- The impact on functionality is zero, making this a stylistic preference check
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| if __name__ == '__main__': | ||
| userInput = str(input("Enter the string to check for vowels: ")) |
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Variable Naming Convention (Python)
Variable names in Python should use snake_case. Renaming userInput to user_input follows PEP 8 guidelines and improves consistency across the Python ecosystem.
| userInput = str(input("Enter the string to check for vowels: ")) | |
| user_input = str(input("Enter the string to check for vowels: ")) |
Reasons & Gaps
Reasons
- PEP 8 specifies that variable names should be lowercase with words separated by underscores
- Using snake_case ensures the codebase remains idiomatic for Python developers
- Improves visual consistency with other standard Python variables and functions
Gaps
- camelCase is often used by developers coming from Java/JavaScript backgrounds
- The variable is local to the main block, reducing the scope of the inconsistency
| #Author: OMKAR PATHAK | ||
| #This program takes input from user and sorts the numbers in two arrays, one of even and other of odd | ||
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| def evenOdd(numbers): |
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Boolean-Returning Function Without Prefix
The function name 'evenOdd' returns a tuple of lists but its name is ambiguous. If it were intended to check a property, it would require a prefix like 'is_'. However, per standard CS-2 rule 1.2, functions returning specific logic should follow naming conventions. More importantly, it violates Python's snake_case convention.
| def evenOdd(numbers): | |
| def get_even_and_odd_numbers(numbers): |
Reasons & Gaps
Reasons
- Function name 'evenOdd' uses camelCase which violates Python snake_case conventions
- The name is vague and doesn't clearly indicate that it performs a separation/filtering action
- Descriptive names like 'get_even_and_odd_numbers' improve code maintainability and intent
Gaps
- The function returns a tuple, not a boolean, so the boolean prefix rule (1.2) is a partial match
- The primary issue is the camelCase naming in a Python context which violates rule 5
| print(os.getcwd()) #Prints the current working directory | ||
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| os.mkdir('newDir1') | ||
| for i in range(1,10): |
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Single-Character Loop Variable
While 'i' is a common convention for simple counters, using a more descriptive name like 'directory_index' or 'folder_number' improves code clarity, especially when performing file system operations.
| for i in range(1,10): | |
| for directory_index in range(1, 10): |
Reasons & Gaps
Reasons
- Single-letter variables provide no context about the data being iterated
- Descriptive names like 'directory_index' clarify the variable's role in the logic
- Improves maintainability by making the loop's purpose self-evident to other developers
Gaps
- Exemption 1.1 explicitly allows 'i' as a loop counter in range-based loops
- The standard suggests avoiding single letters but provides a specific exception for this exact context
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| def guess(): | ||
| ''' This function guesses the randomnly generated number ''' | ||
| randomNumber = random.randint(0, 21) |
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Variable Naming Convention (camelCase in Python)
In Python, variable names should follow the snake_case convention. The name randomNumber uses camelCase, which is inconsistent with PEP 8 standards.
| randomNumber = random.randint(0, 21) | |
| random_number = random.randint(0, 21) |
Reasons & Gaps
Reasons
- PEP 8 recommends snake_case for all function and variable names in Python
- Consistent naming conventions reduce cognitive load when switching between Python modules
- Standardizing on snake_case ensures the code looks idiomatic to other Python developers
Gaps
- Project-specific style guides sometimes override PEP 8 to maintain consistency with legacy code
- The variable name is descriptive, only the casing style is technically non-compliant
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| import random | ||
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| def guess(): |
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Vague Function Name
The function name guess is a generic verb that doesn't fully describe the action. A more descriptive name like play_guessing_game or start_number_guess would better reflect its purpose.
| def guess(): | |
| def play_guessing_game(): |
Reasons & Gaps
Reasons
- Function names should explicitly state the action and the object being acted upon
- 'guess' could imply a single attempt rather than the entire game logic loop
- Descriptive names act as internal documentation, making the entry point clearer
Gaps
- In very small scripts, short function names are often considered acceptable by developers
- The docstring immediately following the definition clarifies the function's purpose
| #Author: OMKAR PATHAK | ||
| #This program is an example for sequential search | ||
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| def sequentialSearch(target, List): |
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Variable Naming Violation: Forbidden Generic Name
The parameter name 'List' is a forbidden generic name and a built-in type in Python. Using it as a variable name can lead to shadowing and reduced readability.
| def sequentialSearch(target, List): | |
| def sequentialSearch(target, search_list): |
Reasons & Gaps
Reasons
- 'List' is a forbidden generic name according to the enterprise coding standards
- Using type names as variables causes confusion for developers and static analysis tools
- Descriptive names like 'search_list' clarify the variable's role in the algorithm
Gaps
- The variable is used within a small function scope which limits the impact of shadowing
- Python is case-sensitive, so 'List' (capitalized) technically avoids shadowing the built-in 'list'
| if __name__ == '__main__': | ||
| List = [1, 2, 3, 4, 5, 6, 7, 8] | ||
| target = 3 | ||
| ans = sequentialSearch(target, List) |
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Variable Naming Refinement: Non-Standard Abbreviation
The variable name 'ans' is a non-standard abbreviation for 'answer'. Expanding it to 'result' or 'position' improves semantic clarity.
| ans = sequentialSearch(target, List) | |
| result = sequentialSearch(target, List) |
Reasons & Gaps
Reasons
- 'ans' is identified as a non-standard abbreviation that should be fully expanded
- 'result' or 'search_result' provides better alignment with domain terminology
- Improving semantic clarity reduces cognitive load for future maintainers
Gaps
- 'ans' is a very common abbreviation in mathematical and algorithmic scripts
- The context of the search makes the meaning of the variable relatively clear
| #Author: OMKAR PATHAK | ||
| #This program is an example for sequential search | ||
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| def sequentialSearch(target, List): |
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Function Naming Violation: Language-Specific Case Convention
The function name 'sequentialSearch' uses camelCase, which violates the Python snake_case convention (PEP 8).
| def sequentialSearch(target, List): | |
| def sequential_search(target, List): |
Reasons & Gaps
Reasons
- Python standard PEP 8 requires function names to be in snake_case
- Consistent casing across the codebase improves overall maintainability
- camelCase is typically reserved for other languages like Java or JavaScript
Gaps
- Some legacy codebases or specific project styles may intentionally use camelCase
- The logic of the function is perfectly clear despite the casing style
| #Author: OMKAR PATHAK | ||
| #This programs give an example of binary search algorithm | ||
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| def binarySearch(target, List): |
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Function Naming Convention (Case Style)
In Python, function names should follow the snake_case naming convention. The current name binarySearch uses camelCase, which is more common in Java or JavaScript.
| def binarySearch(target, List): | |
| def binary_search(target, List): |
Reasons & Gaps
Reasons
- PEP 8 explicitly recommends snake_case for function and variable names in Python
- Consistent naming styles improve code maintainability and follow community standards
- Standardizing on snake_case ensures the codebase feels native to Python developers
Gaps
- Project-specific style guides might occasionally override PEP 8 for consistency with legacy code
- The developer's background in other languages often leads to camelCase usage in Python
| #Author: OMKAR PATHAK | ||
| #This programs give an example of binary search algorithm | ||
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| def binarySearch(target, List): |
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Forbidden Generic Variable Name
The variable name List is a forbidden generic name and shadows the built-in list type (case-insensitively). Using more descriptive names like sorted_elements or data_list is recommended.
| def binarySearch(target, List): | |
| def binarySearch(target, sorted_list): |
Reasons & Gaps
Reasons
- Shadowing built-in types or using their names can lead to confusion and potential bugs
- Descriptive names like 'sorted_list' convey the prerequisite state for binary search
- Following naming standards prevents collision with Python's reserved keywords and types
Gaps
- In small algorithmic examples, generic names like 'List' are frequently used for simplicity
- The variable is local to the function, reducing the impact of shadowing built-ins
| if __name__ == '__main__': | ||
| List = [1, 2, 3, 4, 5, 6, 7, 8, 9, 11, 12, 13, 14] | ||
| target = 2 | ||
| ans = binarySearch(target, List) |
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Vague Variable Name
The variable name ans is a common but non-standard abbreviation for 'answer'. Expanding it to result_index or target_position provides better semantic clarity.
| ans = binarySearch(target, List) | |
| result_index = binarySearch(target, List) |
Reasons & Gaps
Reasons
- Fully expressive names like 'result_index' describe exactly what the value represents
- Reducing abbreviations decreases the cognitive load required to understand the code logic
- Semantic naming helps distinguish between different types of return values in larger scripts
Gaps
- 'ans' is a widely understood abbreviation in competitive programming and math contexts
- The short scope of the script makes the purpose of 'ans' relatively clear to the reader
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| #Best O(n^2); Average O(n^2); Worst O(n^2) | ||
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| def selectionSort(List): |
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Function Naming Convention (Case Style)
In Python, function names should follow the snake_case convention. 'selectionSort' uses camelCase, which is non-standard for Python development.
| def selectionSort(List): | |
| def selection_sort(List): |
Reasons & Gaps
Reasons
- PEP 8 specifies that function names should be lowercase with words separated by underscores
- Consistent naming conventions improve code maintainability across Python projects
- Standardizing to snake_case aligns the code with the broader Python ecosystem
Gaps
- The project might be following a legacy camelCase convention not visible in this diff
- Some developers coming from Java/C++ backgrounds may intentionally use camelCase in Python
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| # Best O(n); Average O(n^2); Worst O(n^2) | ||
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| def insertionSort(List): |
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Forbidden Generic Name
The variable name 'List' is a forbidden generic name and shadows the Python built-in type. Use a more descriptive name like 'input_list' or 'elements'.
| def insertionSort(List): | |
| def insertionSort(elements): |
Reasons & Gaps
Reasons
- 'list' is a forbidden generic name according to the enterprise naming standard
- Shadowing built-in types can lead to confusion and potential runtime errors
- Descriptive names like 'elements' clarify what the collection contains
Gaps
- The variable is used as a parameter, where context is usually provided by the function name
- Python is case-sensitive, so 'List' (capitalized) technically differs from 'list'
| return List | ||
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| if __name__ == '__main__': | ||
| List = [3, 4, 2, 6, 5, 7, 1, 9] |
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Forbidden Generic Name
The variable name 'List' is a forbidden generic name and shadows the Python built-in type. Use a more descriptive name like 'unsorted_numbers'.
| List = [3, 4, 2, 6, 5, 7, 1, 9] | |
| numbers_to_sort = [3, 4, 2, 6, 5, 7, 1, 9] |
Reasons & Gaps
Reasons
- 'list' is explicitly listed as a forbidden generic name in the coding standards
- Capitalized 'List' is often used for type hinting, creating semantic ambiguity
- Descriptive names improve code clarity when the list is passed to other functions
Gaps
- In a small script, the purpose of the variable is immediately obvious from the assignment
- The variable is local to the 'if name == "main"' block
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| # Best = Average = Worst = O(nlog(n)) | ||
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| def merge(a,b): |
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Single-Character Parameter Names
The parameters 'a' and 'b' are single-character names which are non-descriptive. Using more meaningful names like 'left_half' and 'right_half' improves code readability and intent.
| def merge(a,b): | |
| def merge(left_half, right_half): |
Reasons & Gaps
Reasons
- Single-character names 'a' and 'b' do not convey the purpose of the input arrays
- Descriptive names reduce cognitive load when tracing the merge logic
- Standard naming improves maintainability for developers unfamiliar with the specific implementation
Gaps
- Single-letter variables are common in classic algorithm implementations like merge sort
- The mathematical nature of sorting algorithms often uses short variable names by convention
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| def merge(a,b): | ||
| """ Function to merge two arrays """ | ||
| c = [] |
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Single-Character Variable Name
The variable 'c' is a single-character name. A more descriptive name like 'merged_list' or 'result' would better describe its role as the container for the sorted elements.
| c = [] | |
| merged_list = [] |
Reasons & Gaps
Reasons
- The name 'c' requires the reader to look at the initialization to understand its type
- 'merged_list' explicitly states what the variable represents in the sorting context
- Avoids ambiguity and follows clean code practices for descriptive naming
Gaps
- In very short functions, single-letter variables for local accumulators are sometimes tolerated
- The context of a 'merge' function strongly implies 'c' is the result
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| # Code for merge sort | ||
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| def mergeSort(x): |
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Incorrect Function Naming Convention
In Python, function names should follow the snake_case convention. 'mergeSort' should be renamed to 'merge_sort' to align with PEP 8 standards.
| def mergeSort(x): | |
| def merge_sort(x): |
Reasons & Gaps
Reasons
- PEP 8 explicitly recommends snake_case for function and variable names in Python
- Consistent casing across a project prevents confusion and improves professional quality
- camelCase is non-idiomatic in the Python ecosystem and should be avoided
Gaps
- Some legacy codebases or developers coming from Java/C++ backgrounds use camelCase in Python
- The function name is descriptive, only the casing style is technically a violation
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| # Code for merge sort | ||
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| def mergeSort(x): |
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Single-Character Parameter Name
The parameter 'x' is non-descriptive. Renaming it to 'input_list' or 'array_to_sort' makes the function's interface clearer to the caller.
| def mergeSort(x): | |
| def mergeSort(input_list): |
Reasons & Gaps
Reasons
- 'x' provides no information about the expected data type or content of the parameter
- Descriptive parameters serve as internal documentation for the function's usage
- Using 'input_list' clarifies that the function expects a collection of items
Gaps
- 'x' is often used in mathematical or generic algorithmic contexts to represent an input
- The docstring immediately following clarifies that it is an array
| # Best = Average = O(nlog(n)); Worst = O(n^2 | ||
| import time | ||
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| def quickSort(myList, start, end): |
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Function Naming Convention (Case Style)
In Python, function names should follow the snake_case convention. Rename quickSort to quick_sort to align with PEP 8 standards and improve consistency.
| def quickSort(myList, start, end): | |
| def quick_sort(my_list, start, end): |
Reasons & Gaps
Reasons
- Python's PEP 8 style guide explicitly requires snake_case for function names
- Consistent naming conventions reduce cognitive load for Python developers
- Improves code searchability and integration with standard Python tooling
Gaps
- The project might be following a legacy camelCase convention not visible in this diff
- Some teams prefer camelCase for mathematical or algorithmic implementations
| # Best = Average = O(nlog(n)); Worst = O(n^2 | ||
| import time | ||
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| def quickSort(myList, start, end): |
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Non-Standard Abbreviation in Variable
The parameter myList uses a non-standard abbreviation and includes a type hint in the name. Renaming it to items or collection would be more expressive.
| def quickSort(myList, start, end): | |
| def quick_sort(items, start, end): |
Reasons & Gaps
Reasons
- Including the type 'List' in the variable name is a form of Hungarian notation
- 'items' is more generic and allows for future type flexibility
- Removing 'my' prefix follows professional naming standards for parameters
Gaps
- 'myList' is a very common placeholder in educational algorithm examples
- The term 'list' is technically accurate for the Python data structure used
| done= True | ||
| else: | ||
| # swap places | ||
| temp=myList[left] |
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Vague Generic Variable Name
The variable name temp is generic. While common for swaps, Python supports tuple unpacking which eliminates the need for temporary variables entirely.
| temp=myList[left] | |
| myList[left], myList[right] = myList[right], myList[left] |
Reasons & Gaps
Reasons
- Pythonic tuple unpacking is more concise and less error-prone than temp variables
- Eliminates the need for a generic 'temp' name that carries no semantic meaning
- Reduces the number of lines and improves the overall flow of the logic
Gaps
- 'temp' is the industry standard name for temporary storage during a swap
- In low-level algorithmic contexts, explicit swaps are sometimes preferred for clarity
| return quicksortBetter(left) + middle + quicksortBetter(right) | ||
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| if __name__ == '__main__': | ||
| List = [3, 4, 2, 6, 5, 7, 1, 9] |
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Vague and Capitalized Variable Name
The variable List is capitalized (usually reserved for classes) and uses a generic type name. Use a descriptive name like unsorted_numbers.
| List = [3, 4, 2, 6, 5, 7, 1, 9] | |
| numbers = [3, 4, 2, 6, 5, 7, 1, 9] |
Reasons & Gaps
Reasons
- Capitalized names in Python typically indicate classes, leading to confusion
- 'List' shadows the built-in type name (though case-different, it is poor practice)
- Descriptive names like 'numbers' clarify what the collection actually contains
Gaps
- In a simple script, generic names like 'List' are often used for brevity
- The context of a sorting algorithm makes the purpose of the list obvious
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| def delete(self, element): | ||
| if element in self.items: | ||
| Index = self.items.index(element) |
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Inconsistent Variable Casing
The variable 'Index' uses PascalCase, which is inconsistent with the snake_case convention used for other variables in this file and standard Python practices.
| Index = self.items.index(element) | |
| element_index = self.items.index(element) |
Reasons & Gaps
Reasons
- Python variables should follow snake_case to maintain codebase consistency
- PascalCase is typically reserved for Class names in Python
- 'element_index' is more descriptive than the generic 'Index'
Gaps
- The variable is functional and its purpose is clear despite the casing
- Local scope limits the impact of the naming inconsistency
| def justPrint(text): | ||
| '''This function prints the text passed as argument to this function''' | ||
| print(text) | ||
| a=input("Enter a number: ") |
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Single-Character Variable Name
The variable name 'a' is non-descriptive. Using more meaningful names like 'first_number' or 'input_value_a' improves code readability and maintainability.
| a=input("Enter a number: ") | |
| first_number = input("Enter a number: ") |
Reasons & Gaps
Reasons
- Single-letter names provide no context about the data being stored or its purpose
- Descriptive names reduce the cognitive load required to understand the logic flow
- Following PEP 8 naming conventions ensures consistency across the Python codebase
Gaps
- In very small scripts or mathematical contexts, single letters are sometimes used by convention
- The script's simple nature might make the variable's purpose obvious to the original author
| '''This function prints the text passed as argument to this function''' | ||
| print(text) | ||
| a=input("Enter a number: ") | ||
| b=input("Enter another number: ") |
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Single-Character Variable Name
The variable name 'b' is non-descriptive. A name like 'second_number' or 'input_value_b' would more clearly communicate the variable's intent.
| b=input("Enter another number: ") | |
| second_number = input("Enter another number: ") |
Reasons & Gaps
Reasons
- Non-descriptive names like 'b' make the code harder to maintain as it grows
- Meaningful names act as internal documentation for the function's operations
- Standardizing on descriptive names prevents ambiguity in complex expressions
Gaps
- Small scope of the function might lead some developers to consider 'b' acceptable
- Project-specific conventions for simple input scripts are not visible in this diff
| # Author: OMKAR PATHAK | ||
| # This program prints the entered message | ||
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| def justPrint(text): |
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Non-Standard Function Naming (CamelCase)
Python functions should use snake_case. Additionally, 'justPrint' is slightly vague; consider a name that reflects its full behavior, such as 'print_and_calculate'.
| def justPrint(text): | |
| def print_and_calculate(text): |
Reasons & Gaps
Reasons
- Python convention (PEP 8) strictly recommends snake_case for function names
- The name 'justPrint' implies a single action while the body performs multiple tasks
- Consistent naming styles across a project improve overall code professionality
Gaps
- The function name is partially descriptive but violates Python's PEP 8 style guide
- 'justPrint' is misleading as the function also performs arithmetic and input operations
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| # LEGB Rule: Local, Enclosing, Global, Built-in | ||
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| x = 80 # Global x |
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Single-Character Variable Name
The variable name 'x' is non-descriptive. Using single-letter names for global variables or business logic makes the code harder to maintain and understand. Consider a more descriptive name like 'global_count' or 'base_value'.
| x = 80 # Global x | |
| global_value = 80 # Global x |
Reasons & Gaps
Reasons
- Single-character names fail to communicate the purpose or content of the variable
- Global variables require high clarity to prevent accidental shadowing or misuse
- Descriptive naming reduces cognitive load when tracing variable scope in LEGB rules
Gaps
- Single letters like 'x' are common in mathematical contexts or quick scripts
- The comment explicitly labels it as 'Global x', providing some immediate context
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| def test(): | ||
| #global x | ||
| y = 100 # Local y |
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Single-Character Variable Name
The variable name 'y' is ambiguous. While it is a local variable, using descriptive names like 'local_offset' or 'adjustment_value' improves code clarity.
| y = 100 # Local y | |
| local_value = 100 # Local y |
Reasons & Gaps
Reasons
- 'y' provides no semantic meaning regarding what the integer 100 represents
- Meaningful names act as internal documentation for the function's logic
- Standardized naming prevents confusion in larger functions with multiple variables
Gaps
- Local scope limits the impact of poor naming compared to global variables
- In simple demonstration scripts, x and y are often used as generic placeholders
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| x = 80 # Global x | ||
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| def test(): |
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Vague Function Name
The function name 'test' is generic and does not describe the specific behavior being performed. A name like 'demonstrate_variable_scope' would be more appropriate.
| def test(): | |
| def demonstrate_scope_rules(): |
Reasons & Gaps
Reasons
- The name 'test' is a forbidden generic placeholder that lacks functional context
- It does not indicate what is being tested or the expected outcome of the call
- Descriptive names (3-5 words) are preferred to make the code self-documenting
Gaps
- 'test' is frequently used in small snippets or scratchpad code for quick execution
- The script's purpose is educational, where generic names are sometimes tolerated
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| #Syntax: list[start: end: step] | ||
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| myList = [1, 2, 3, 4, 5, 6, 7, 8, 9] |
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Non-Descriptive Variable Name
The variable name 'myList' is generic and uses a type suffix. Renaming it to something descriptive like 'numbers' or 'integer_list' improves code clarity and follows naming best practices.
| myList = [1, 2, 3, 4, 5, 6, 7, 8, 9] | |
| numbers = [1, 2, 3, 4, 5, 6, 7, 8, 9] |
Reasons & Gaps
Reasons
- Generic names like 'myList' fail to describe the actual data being stored
- Including the type 'List' in the name is redundant and discouraged in Python
- Descriptive names reduce cognitive load when the codebase grows in complexity
Gaps
- The script appears to be an educational example where generic names are common
- 'myList' is technically functional and its purpose is clear within this small scope
| return number * factorial(number - 1) | ||
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| if __name__ == '__main__': | ||
| userInput = int(input('Enter the Number to find the factorial of: ')) |
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Non-Standard Variable Naming (camelCase)
In Python, variable names should follow the snake_case convention. The variable userInput uses camelCase, which is inconsistent with PEP 8 standards.
| userInput = int(input('Enter the Number to find the factorial of: ')) | |
| user_input = int(input('Enter the Number to find the factorial of: ')) |
Reasons & Gaps
Reasons
- PEP 8 specifically recommends snake_case for variable and function names in Python
- Consistent naming conventions reduce cognitive load when switching between different files
- Improves code maintainability by adhering to community-standard stylistic patterns
Gaps
- Project-specific style guides sometimes allow camelCase if migrating from other languages
- The variable is local to the main block, reducing its impact on the overall API consistency
| #This program finds the favtorial of the specified numbers | ||
| #For example, factorial of 5 = 5*4*3*2*1 = 120 | ||
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| def factorial(number): |
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Vague Variable Name
While 'number' is functional, using a more descriptive name like 'input_number' or 'n' (in mathematical contexts) can improve clarity, especially in larger functions.
| def factorial(number): | |
| def factorial(input_number): |
Reasons & Gaps
Reasons
- Enhancing variable names to be fully expressive improves long-term code maintainability
- Avoids using generic terms that might conflict with built-in types or common utilities
- Aligns the parameter name with the domain-specific purpose of the function input
Gaps
- 'number' is a forbidden generic name in some strict standards but acceptable in simple math
- The context of a factorial function makes the purpose of 'number' relatively obvious
| #Author: OMKAR PATHAK | ||
| #This program checks for the character frequency in the given string | ||
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| def charFrequency(userInput): |
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Variable Naming Refinement
The parameter userInput uses camelCase, which is non-standard for Python variables. It should be refined to user_input to align with PEP 8 and improve consistency.
| def charFrequency(userInput): | |
| def charFrequency(user_input): |
Reasons & Gaps
Reasons
- Python convention (PEP 8) dictates snake_case for all variable and parameter names
- Standardizing naming styles across the codebase improves overall maintainability
- 'user_input' is the idiomatic way to represent this variable in Python
Gaps
- The name is already understandable, making this a stylistic refinement
- Project-specific style guides might occasionally permit camelCase for parameters
| #Author: OMKAR PATHAK | ||
| #This program checks whether the entered number is prime or not | ||
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| def checkPrime(number): |
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Boolean Function Naming Convention
Functions that return a boolean value or check a condition should typically be prefixed with is_, has_, or can_. Renaming this to is_prime improves clarity and follows Python naming conventions.
| def checkPrime(number): | |
| def is_prime(number): |
Reasons & Gaps
Reasons
- Function returns/calculates a boolean state but lacks a standard boolean prefix
- 'checkPrime' is a vague verb-noun combination compared to the idiomatic 'is_prime'
- Improves consistency with PEP 8 recommendations for predicate functions
Gaps
- The function currently prints results instead of returning a boolean, though it maintains an internal 'isPrime' state
- Refactoring to return a boolean would make the 'is_' prefix 100% appropriate
| print(number, 'is a Prime Number') | ||
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| if __name__ == '__main__': | ||
| userInput = int(input('Enter a number to check: ')) |
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Variable Naming Convention (CamelCase)
In Python, variable names should follow the snake_case convention. 'userInput' should be renamed to 'user_input' to align with standard Python style guides.
| userInput = int(input('Enter a number to check: ')) | |
| user_input = int(input('Enter a number to check: ')) |
Reasons & Gaps
Reasons
- Python naming conventions (PEP 8) require snake_case for variables and functions
- Mixed naming styles (camelCase vs snake_case) reduce codebase consistency
- Standardizing to user_input follows the widely accepted community and enterprise norms
Gaps
- CamelCase is functional in Python but violates the PEP 8 standard used in most enterprise environments
- The name itself is descriptive, only the casing style is non-compliant
| return fibonacci1 | ||
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| if __name__ == '__main__': | ||
| userInput = int(input('Enter the number upto which you wish to calculate fibonnaci series: ')) |
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Variable Naming Convention (Information)
The variable name userInput uses camelCase, which is inconsistent with Python's snake_case convention. Renaming it to user_input or max_terms would improve consistency and clarity.
| userInput = int(input('Enter the number upto which you wish to calculate fibonnaci series: ')) | |
| user_input = int(input('Enter the number upto which you wish to calculate fibonnaci series: ')) |
Reasons & Gaps
Reasons
- Python's PEP 8 style guide recommends snake_case for variable names
- Consistent naming conventions reduce cognitive load during code reviews
- Improving semantic clarity ensures the codebase remains maintainable over time
Gaps
- Project-specific naming conventions might allow camelCase for user-facing variables
- The variable is functional and its purpose is clear within the local scope
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| def fibonacci_without_recursion(number): | ||
| if number == 0: return 0 | ||
| fibonacci0, fibonacci1 = 0, 1 |
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Variable Naming Convention (Information)
The variables fibonacci0 and fibonacci1 contain numeric suffixes. Using more descriptive names like previous_term and current_term would better reflect their roles in the sequence calculation.
| fibonacci0, fibonacci1 = 0, 1 | |
| prev_term, curr_term = 0, 1 |
Reasons & Gaps
Reasons
- Avoiding numbered names prevents ambiguity in complex logic blocks
- Descriptive names like 'prev' and 'curr' explain the state of the iteration
- Enhances readability for developers unfamiliar with this specific implementation
Gaps
- Numeric suffixes are common in mathematical implementations of sequences
- The context of a Fibonacci function makes the purpose of these variables relatively clear
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