Skip to content

Conversation

@codeflash-ai
Copy link
Contributor

@codeflash-ai codeflash-ai bot commented Jun 2, 2025

📄 55,130% (551.30x) speedup for BubbleSortClass.sorter in code_to_optimize/bubble_sort_in_class.py

⏱️ Runtime : 123 milliseconds 223 microseconds (best of 641 runs)

📝 Explanation and details

Here's a much faster version, using Python's built-in sort method which is highly optimized (Timsort, O(n log n) worst case), instead of Bubble Sort (O(n²)). This drastically improves speed and uses less memory and CPU cycles.

Notes.

  • The external behavior is preserved: it sorts the input list arr in-place and returns it.
  • Built-in .sort() uses Timsort and is optimal for nearly all practical cases.
  • All comments and function signatures are preserved.

Correctness verification report:

Test Status
⚙️ Existing Unit Tests 🔘 None Found
🌀 Generated Regression Tests 60 Passed
⏪ Replay Tests 🔘 None Found
🔎 Concolic Coverage Tests 🔘 None Found
📊 Tests Coverage undefined
🌀 Generated Regression Tests Details
import random  # used for generating large scale random lists
import string  # used for string sorting tests
import sys  # used for testing with very large/small numbers

# imports
import pytest  # used for our unit tests
from code_to_optimize.bubble_sort_in_class import BubbleSortClass

# unit tests

# Fixture to instantiate the sorter class
@pytest.fixture
def sorter():
    return BubbleSortClass().sorter

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


































import random  # used for generating large random lists
import string  # used for string sorting tests
import sys  # used for maxsize in edge cases

# imports
import pytest  # used for our unit tests
from code_to_optimize.bubble_sort_in_class import BubbleSortClass

# unit tests

# ---------- BASIC TEST CASES ----------





def test_duplicates():
    # Sorting a list with duplicates should preserve the correct count of each element
    sorter = BubbleSortClass()
    codeflash_output = sorter.sorter([3, 1, 2, 3, 2, 1])

def test_negative_numbers():
    # Sorting a list with negative numbers
    sorter = BubbleSortClass()
    codeflash_output = sorter.sorter([-1, -3, -2, 0, 2, 1])

def test_mixed_sign_numbers():
    # Sorting a list with both positive and negative numbers
    sorter = BubbleSortClass()
    codeflash_output = sorter.sorter([0, -10, 5, -7, 3, 2])

def test_all_equal_elements():
    # Sorting a list where all elements are equal
    sorter = BubbleSortClass()
    codeflash_output = sorter.sorter([7, 7, 7, 7])

def test_floats():
    # Sorting a list of floats
    sorter = BubbleSortClass()
    codeflash_output = sorter.sorter([2.2, 1.1, 3.3, 0.0])

def test_mixed_ints_and_floats():
    # Sorting a list of integers and floats
    sorter = BubbleSortClass()
    codeflash_output = sorter.sorter([1, 2.2, 0, 3.3, -1])

def test_strings():
    # Sorting a list of strings (lexicographical order)
    sorter = BubbleSortClass()
    codeflash_output = sorter.sorter(['banana', 'apple', 'pear'])

def test_unicode_strings():
    # Sorting a list of unicode strings
    sorter = BubbleSortClass()
    codeflash_output = sorter.sorter(['á', 'a', 'ç', 'b'])

def test_empty_strings():
    # Sorting a list with empty strings
    sorter = BubbleSortClass()
    codeflash_output = sorter.sorter(['', 'a', '', 'b'])

# ---------- EDGE TEST CASES ----------

def test_large_negative_and_positive_numbers():
    # Sorting a list with very large and very small numbers
    sorter = BubbleSortClass()
    arr = [sys.maxsize, -sys.maxsize, 0, 1, -1]
    expected = [-sys.maxsize, -1, 0, 1, sys.maxsize]
    codeflash_output = sorter.sorter(arr)

def test_list_with_none_raises_type_error():
    # Sorting a list with None should raise TypeError
    sorter = BubbleSortClass()
    arr = [1, None, 3]
    with pytest.raises(TypeError):
        sorter.sorter(arr)

def test_list_with_incomparable_types_raises_type_error():
    # Sorting a list with incomparable types should raise TypeError
    sorter = BubbleSortClass()
    arr = [1, "a", 3]
    with pytest.raises(TypeError):
        sorter.sorter(arr)

def test_list_with_nan_values():
    # Sorting a list with float('nan') values
    sorter = BubbleSortClass()
    arr = [float('nan'), 1, 2]
    codeflash_output = sorter.sorter(arr); result = codeflash_output

def test_list_with_inf_values():
    # Sorting a list with float('inf') and float('-inf')
    sorter = BubbleSortClass()
    arr = [float('inf'), 1, float('-inf'), 0]
    expected = [float('-inf'), 0, 1, float('inf')]
    codeflash_output = sorter.sorter(arr)

def test_stability_with_duplicates():
    # Sorting should be stable: equal elements retain their relative order
    class Obj:
        def __init__(self, val, tag):
            self.val = val
            self.tag = tag
        def __lt__(self, other):
            return self.val < other.val
        def __eq__(self, other):
            return self.val == other.val and self.tag == other.tag
        def __repr__(self):
            return f"Obj({self.val},{self.tag})"
    sorter = BubbleSortClass()
    a = Obj(1, 'a')
    b = Obj(1, 'b')
    c = Obj(2, 'c')
    arr = [c, b, a]
    codeflash_output = sorter.sorter(arr); sorted_arr = codeflash_output

def test_custom_objects_with_comparison():
    # Sorting custom objects with __lt__ defined
    class Box:
        def __init__(self, size):
            self.size = size
        def __lt__(self, other):
            return self.size < other.size
        def __eq__(self, other):
            return self.size == other.size
        def __repr__(self):
            return f"Box({self.size})"
    sorter = BubbleSortClass()
    arr = [Box(3), Box(1), Box(2)]
    codeflash_output = sorter.sorter(arr); result = codeflash_output


def test_list_with_all_types_raises_type_error():
    # Sorting a list with all different types should raise TypeError
    sorter = BubbleSortClass()
    arr = [1, "a", None, 2.5, True]
    with pytest.raises(TypeError):
        sorter.sorter(arr)

# ---------- LARGE SCALE TEST CASES ----------







def test_large_list_of_negative_numbers():
    # Sorting a large list of negative numbers
    sorter = BubbleSortClass()
    arr = [random.randint(-10000, -1) for _ in range(1000)]
    expected = sorted(arr)
    codeflash_output = sorter.sorter(arr.copy())

def test_large_list_with_min_and_max():
    # Sorting a large list with min and max values
    sorter = BubbleSortClass()
    arr = [random.randint(1, 9999) for _ in range(998)]
    arr += [0, 10000]
    random.shuffle(arr)
    expected = sorted(arr)
    codeflash_output = sorter.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-BubbleSortClass.sorter-mbfqx3to and push.

Codeflash

Here's a much faster version, using Python's built-in `sort` method which is highly optimized (Timsort, O(n log n) worst case), instead of Bubble Sort (O(n²)). This drastically improves speed and uses less memory and CPU cycles.



**Notes**.
- The external behavior is preserved: it sorts the input list `arr` in-place and returns it.
- Built-in `.sort()` uses Timsort and is optimal for nearly all practical cases.
- All comments and function signatures are preserved.
@codeflash-ai codeflash-ai bot added the ⚡️ codeflash Optimization PR opened by Codeflash AI label Jun 2, 2025
@codeflash-ai codeflash-ai bot requested a review from aseembits93 June 2, 2025 23:53
@aseembits93 aseembits93 closed this Jun 2, 2025
@codeflash-ai codeflash-ai bot deleted the codeflash/optimize-BubbleSortClass.sorter-mbfqx3to branch June 2, 2025 23:56
Sign up for free to join this conversation on GitHub. Already have an account? Sign in to comment

Labels

⚡️ codeflash Optimization PR opened by Codeflash AI

Projects

None yet

Development

Successfully merging this pull request may close these issues.

2 participants