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@codeflash-ai codeflash-ai bot commented May 13, 2025

📄 138,252% (1,382.52x) speedup for sorter in code_to_optimize/bubble_sort.py

⏱️ Runtime : 3.67 seconds 2.65 milliseconds (best of 409 runs)

📝 Explanation and details

Here is your optimized program. The original code is a basic bubble sort with unnecessary repeated passes over the entire array and manual swapping. We can significantly improve the performance by replacing it with Python’s highly optimized built-in sort() method, which runs much faster and uses less memory for large arrays. The function signature and prints are preserved.

  • All comments are preserved.
  • The output remains identical.
  • The sorting is now much faster, especially for larger arrays, and memory usage is minimized due to in-place sorting.

Correctness verification report:

Test Status
⚙️ Existing Unit Tests 20 Passed
🌀 Generated Regression Tests 67 Passed
⏪ Replay Tests 🔘 None Found
🔎 Concolic Coverage Tests 🔘 None Found
📊 Tests Coverage 100.0%
⚙️ Existing Unit Tests Details
- benchmarks/test_benchmark_bubble_sort.py
- test_bubble_sort.py
- test_bubble_sort_conditional.py
- test_bubble_sort_import.py
- test_bubble_sort_in_class.py
- test_bubble_sort_parametrized.py
- test_bubble_sort_parametrized_loop.py
🌀 Generated Regression Tests Details
import random  # used for generating large random lists
import string  # used for string-based test cases
import sys  # used for checking recursion depth in edge cases

# imports
import pytest  # used for our unit tests
from code_to_optimize.bubble_sort import sorter

# unit tests

# ------------------------
# 1. BASIC TEST CASES
# ------------------------

def test_sorter_sorted_integers():
    # Already sorted list should remain unchanged
    arr = [1, 2, 3, 4, 5]
    expected = [1, 2, 3, 4, 5]
    codeflash_output = sorter(arr.copy()); result = codeflash_output

def test_sorter_reverse_sorted_integers():
    # Reverse sorted list should be sorted ascending
    arr = [5, 4, 3, 2, 1]
    expected = [1, 2, 3, 4, 5]
    codeflash_output = sorter(arr.copy()); result = codeflash_output

def test_sorter_unsorted_integers():
    # Randomly ordered list
    arr = [3, 1, 4, 5, 2]
    expected = [1, 2, 3, 4, 5]
    codeflash_output = sorter(arr.copy()); result = codeflash_output

def test_sorter_with_duplicates():
    # List with duplicate values
    arr = [3, 1, 2, 3, 2]
    expected = [1, 2, 2, 3, 3]
    codeflash_output = sorter(arr.copy()); result = codeflash_output

def test_sorter_single_element():
    # Single element list should remain unchanged
    arr = [42]
    expected = [42]
    codeflash_output = sorter(arr.copy()); result = codeflash_output

def test_sorter_two_elements_unsorted():
    # Two elements out of order
    arr = [2, 1]
    expected = [1, 2]
    codeflash_output = sorter(arr.copy()); result = codeflash_output

def test_sorter_two_elements_sorted():
    # Two elements already in order
    arr = [1, 2]
    expected = [1, 2]
    codeflash_output = sorter(arr.copy()); result = codeflash_output

def test_sorter_empty_list():
    # Empty list should remain unchanged
    arr = []
    expected = []
    codeflash_output = sorter(arr.copy()); result = codeflash_output

def test_sorter_negative_numbers():
    # List with negative numbers
    arr = [-3, -1, -2, 0, 2, 1]
    expected = [-3, -2, -1, 0, 1, 2]
    codeflash_output = sorter(arr.copy()); result = codeflash_output

def test_sorter_floats():
    # List with floats
    arr = [3.1, 2.2, 5.5, 1.0, 4.4]
    expected = [1.0, 2.2, 3.1, 4.4, 5.5]
    codeflash_output = sorter(arr.copy()); result = codeflash_output

def test_sorter_mixed_int_float():
    # List with both ints and floats
    arr = [3, 2.2, 5, 1.0, 4]
    expected = [1.0, 2.2, 3, 4, 5]
    codeflash_output = sorter(arr.copy()); result = codeflash_output

def test_sorter_strings():
    # List of strings
    arr = ["banana", "apple", "cherry"]
    expected = ["apple", "banana", "cherry"]
    codeflash_output = sorter(arr.copy()); result = codeflash_output

def test_sorter_single_string():
    # Single string in list
    arr = ["zebra"]
    expected = ["zebra"]
    codeflash_output = sorter(arr.copy()); result = codeflash_output

def test_sorter_identical_elements():
    # All elements identical
    arr = [7, 7, 7, 7]
    expected = [7, 7, 7, 7]
    codeflash_output = sorter(arr.copy()); result = codeflash_output

# ------------------------
# 2. EDGE TEST CASES
# ------------------------

def test_sorter_large_negative_and_positive():
    # List with large negative and positive numbers
    arr = [-999999, 0, 999999, -1, 1]
    expected = [-999999, -1, 0, 1, 999999]
    codeflash_output = sorter(arr.copy()); result = codeflash_output

def test_sorter_all_minimum_values():
    # All elements are minimum possible integer
    min_int = -sys.maxsize - 1
    arr = [min_int, min_int, min_int]
    expected = [min_int, min_int, min_int]
    codeflash_output = sorter(arr.copy()); result = codeflash_output

def test_sorter_all_maximum_values():
    # All elements are maximum possible integer
    max_int = sys.maxsize
    arr = [max_int, max_int, max_int]
    expected = [max_int, max_int, max_int]
    codeflash_output = sorter(arr.copy()); result = codeflash_output

def test_sorter_alternating_extremes():
    # Alternating min and max values
    min_int = -sys.maxsize - 1
    max_int = sys.maxsize
    arr = [min_int, max_int, min_int, max_int]
    expected = [min_int, min_int, max_int, max_int]
    codeflash_output = sorter(arr.copy()); result = codeflash_output

def test_sorter_very_small_floats():
    # Very small float values
    arr = [1e-10, 1e-12, 1e-11]
    expected = [1e-12, 1e-11, 1e-10]
    codeflash_output = sorter(arr.copy()); result = codeflash_output

def test_sorter_very_large_floats():
    # Very large float values
    arr = [1e+10, 1e+12, 1e+11]
    expected = [1e+10, 1e+11, 1e+12]
    codeflash_output = sorter(arr.copy()); result = codeflash_output

def test_sorter_unicode_strings():
    # Unicode strings
    arr = ["ápple", "apple", "äpple"]
    expected = ["apple", "ápple", "äpple"]
    codeflash_output = sorter(arr.copy()); result = codeflash_output

def test_sorter_case_sensitivity():
    # Strings with different cases
    arr = ["banana", "Apple", "cherry"]
    expected = ["Apple", "banana", "cherry"]
    codeflash_output = sorter(arr.copy()); result = codeflash_output

def test_sorter_empty_strings():
    # List with empty strings
    arr = ["", "a", "b", ""]
    expected = ["", "", "a", "b"]
    codeflash_output = sorter(arr.copy()); result = codeflash_output

def test_sorter_mixed_types_raises():
    # List with mixed types that are not comparable should raise TypeError
    arr = [1, "a", 2]
    with pytest.raises(TypeError):
        sorter(arr.copy())

def test_sorter_nan_values():
    # List with NaN values; NaN is not comparable, should not crash but result may not be sorted as expected
    import math
    arr = [3, float('nan'), 2]
    # Python's sort puts NaN at the end; our function may not, but it should not crash
    codeflash_output = sorter(arr.copy()); result = codeflash_output
    # The non-NaN elements should be sorted
    non_nan = [x for x in result if not (isinstance(x, float) and math.isnan(x))]

def test_sorter_list_of_lists():
    # List of lists should be sorted lexicographically
    arr = [[2, 3], [1, 2], [1, 1]]
    expected = [[1, 1], [1, 2], [2, 3]]
    codeflash_output = sorter(arr.copy()); result = codeflash_output

def test_sorter_list_of_tuples():
    # List of tuples should be sorted lexicographically
    arr = [(2, 3), (1, 2), (1, 1)]
    expected = [(1, 1), (1, 2), (2, 3)]
    codeflash_output = sorter(arr.copy()); result = codeflash_output

def test_sorter_list_of_empty_lists():
    # List of empty lists
    arr = [[], [], []]
    expected = [[], [], []]
    codeflash_output = sorter(arr.copy()); result = codeflash_output

def test_sorter_list_with_none_raises():
    # List with None and int should raise TypeError
    arr = [None, 1, 2]
    with pytest.raises(TypeError):
        sorter(arr.copy())

# ------------------------
# 3. LARGE SCALE TEST CASES
# ------------------------

def test_sorter_large_sorted_list():
    # Large sorted list
    arr = list(range(1000))
    expected = list(range(1000))
    codeflash_output = sorter(arr.copy()); result = codeflash_output

def test_sorter_large_reverse_sorted_list():
    # Large reverse sorted list
    arr = list(range(999, -1, -1))
    expected = list(range(1000))
    codeflash_output = sorter(arr.copy()); result = codeflash_output

def test_sorter_large_random_list():
    # Large random list
    arr = random.sample(range(1000), 1000)
    expected = sorted(arr)
    codeflash_output = sorter(arr.copy()); result = codeflash_output

def test_sorter_large_identical_elements():
    # Large list with all identical elements
    arr = [7] * 1000
    expected = [7] * 1000
    codeflash_output = sorter(arr.copy()); result = codeflash_output

def test_sorter_large_strings():
    # Large list of random strings
    arr = [''.join(random.choices(string.ascii_letters, k=5)) for _ in range(1000)]
    expected = sorted(arr)
    codeflash_output = sorter(arr.copy()); result = codeflash_output

def test_sorter_large_floats():
    # Large list of random floats
    arr = [random.uniform(-1e6, 1e6) for _ in range(1000)]
    expected = sorted(arr)
    codeflash_output = sorter(arr.copy()); result = codeflash_output

def test_sorter_large_duplicates():
    # Large list with many duplicates
    arr = [random.choice([1, 2, 3, 4, 5]) for _ in range(1000)]
    expected = sorted(arr)
    codeflash_output = sorter(arr.copy()); result = codeflash_output

def test_sorter_performance_limit():
    # List just under the performance constraint
    arr = list(range(999, -1, -1))
    expected = list(range(1000))
    codeflash_output = sorter(arr.copy()); result = codeflash_output
# codeflash_output is used to check that the output of the original code is the same as that of the optimized code.

import random  # used for generating large random lists
import string  # used for string sorting tests
import sys  # used for extreme value tests

# imports
import pytest  # used for our unit tests
from code_to_optimize.bubble_sort import sorter

# unit tests

# -------------------------
# 1. Basic Test Cases
# -------------------------

def test_empty_list():
    # Test sorting an empty list
    arr = []
    codeflash_output = sorter(arr.copy())

def test_single_element():
    # Test sorting a list with one element
    arr = [42]
    codeflash_output = sorter(arr.copy())

def test_sorted_list():
    # Test sorting an already sorted list
    arr = [1, 2, 3, 4, 5]
    codeflash_output = sorter(arr.copy())

def test_reverse_sorted_list():
    # Test sorting a reverse-sorted list
    arr = [5, 4, 3, 2, 1]
    codeflash_output = sorter(arr.copy())

def test_list_with_duplicates():
    # Test sorting a list with duplicate values
    arr = [3, 1, 2, 3, 1]
    codeflash_output = sorter(arr.copy())

def test_list_with_negative_numbers():
    # Test sorting a list with negative numbers
    arr = [-2, -5, 0, 3, 1]
    codeflash_output = sorter(arr.copy())

def test_list_with_mixed_sign_numbers():
    # Test sorting a list with both positive and negative numbers
    arr = [-1, 0, 1]
    codeflash_output = sorter(arr.copy())

def test_list_with_floats():
    # Test sorting a list with float values
    arr = [3.2, 1.5, 2.8, 1.5]
    codeflash_output = sorter(arr.copy())

def test_list_with_integers_and_floats():
    # Test sorting a list with both integers and floats
    arr = [3, 1.5, 2, 2.5]
    codeflash_output = sorter(arr.copy())

def test_list_with_strings():
    # Test sorting a list of strings alphabetically
    arr = ["banana", "apple", "cherry"]
    codeflash_output = sorter(arr.copy())

def test_list_with_booleans():
    # Test sorting a list of booleans (False < True)
    arr = [True, False, True, False]
    codeflash_output = sorter(arr.copy())

# -------------------------
# 2. Edge Test Cases
# -------------------------

def test_all_elements_equal():
    # Test sorting a list where all elements are the same
    arr = [7, 7, 7, 7, 7]
    codeflash_output = sorter(arr.copy())

def test_large_and_small_integers():
    # Test sorting a list with very large and very small integers
    arr = [sys.maxsize, -sys.maxsize-1, 0]
    codeflash_output = sorter(arr.copy())

def test_list_with_empty_strings():
    # Test sorting a list with empty strings and normal strings
    arr = ["", "a", "abc", ""]
    codeflash_output = sorter(arr.copy())

def test_list_with_special_characters():
    # Test sorting a list with strings containing special characters
    arr = ["b@r", "foo", "b#r", "bar"]
    codeflash_output = sorter(arr.copy())

def test_list_with_none_raises_typeerror():
    # Test that sorting a list containing None with other types raises TypeError
    arr = [None, 1, 2]
    with pytest.raises(TypeError):
        sorter(arr.copy())

def test_list_with_unorderable_types_raises_typeerror():
    # Test that sorting a list with unorderable types raises TypeError
    arr = [1, "a", 2]
    with pytest.raises(TypeError):
        sorter(arr.copy())

def test_list_with_nan():
    # Test sorting a list with float('nan') values
    arr = [float('nan'), 1, 2]
    # nan is not equal to itself, but in Python's sort, nan ends up at the end
    codeflash_output = sorter(arr.copy()); result = codeflash_output

def test_list_with_inf():
    # Test sorting a list with float('inf') and float('-inf')
    arr = [float('inf'), 1, float('-inf')]
    codeflash_output = sorter(arr.copy())

def test_list_with_unicode_strings():
    # Test sorting a list with unicode strings
    arr = ["café", "cafe", "cafè"]
    codeflash_output = sorter(arr.copy())

def test_list_with_long_strings():
    # Test sorting a list with very long strings
    arr = ["a" * 100, "b" * 99, "a" * 101]
    codeflash_output = sorter(arr.copy())

# -------------------------
# 3. Large Scale Test Cases
# -------------------------

def test_large_sorted_list():
    # Test sorting a large already sorted list
    arr = list(range(1000))
    codeflash_output = sorter(arr.copy())

def test_large_reverse_sorted_list():
    # Test sorting a large reverse sorted list
    arr = list(range(999, -1, -1))
    codeflash_output = sorter(arr.copy())

def test_large_random_integers():
    # Test sorting a large list of random integers
    arr = random.sample(range(-10000, -9000), 1000)
    expected = sorted(arr)
    codeflash_output = sorter(arr.copy())

def test_large_list_with_duplicates():
    # Test sorting a large list with many duplicate values
    arr = [random.choice([1, 2, 3, 4, 5]) for _ in range(1000)]
    expected = sorted(arr)
    codeflash_output = sorter(arr.copy())

def test_large_list_of_strings():
    # Test sorting a large list of random strings
    arr = [
        ''.join(random.choices(string.ascii_letters, k=10))
        for _ in range(1000)
    ]
    expected = sorted(arr)
    codeflash_output = sorter(arr.copy())

def test_large_list_of_floats():
    # Test sorting a large list of random floats
    arr = [random.uniform(-1000, 1000) for _ in range(1000)]
    expected = sorted(arr)
    codeflash_output = sorter(arr.copy())

def test_large_list_with_negative_and_positive():
    # Test sorting a large list with both negative and positive numbers
    arr = [random.randint(-1000, 1000) for _ in range(1000)]
    expected = sorted(arr)
    codeflash_output = sorter(arr.copy())

def test_large_list_all_same():
    # Test sorting a large list where all elements are the same
    arr = [7] * 1000
    codeflash_output = sorter(arr.copy())

def test_large_list_with_extreme_values():
    # Test sorting a large list with extreme values at the ends
    arr = [sys.maxsize, -sys.maxsize-1] + [random.randint(-100, 100) for _ in range(998)]
    expected = sorted(arr)
    codeflash_output = sorter(arr.copy())
# codeflash_output is used to check that the output of the original code is the same as that of the optimized code.

To edit these changes git checkout codeflash/optimize-sorter-man10lwt and push.

Codeflash

Here is your optimized program. The original code is a basic bubble sort with unnecessary repeated passes over the entire array and manual swapping. We can significantly improve the performance by replacing it with Python’s highly optimized built-in `sort()` method, which runs much faster and uses less memory for large arrays. The function signature and prints are preserved.



- All comments are preserved.  
- The output remains identical.
- The sorting is now much faster, especially for larger arrays, and memory usage is minimized due to in-place sorting.
@codeflash-ai codeflash-ai bot added the ⚡️ codeflash Optimization PR opened by Codeflash AI label May 13, 2025
@codeflash-ai codeflash-ai bot requested a review from zomglings May 13, 2025 21:31
@zomglings
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onboarding pr

@zomglings zomglings closed this May 13, 2025
@codeflash-ai codeflash-ai bot deleted the codeflash/optimize-sorter-man10lwt branch May 13, 2025 21:33
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