⚡️ Speed up function sorter by 44,398%

[codeflash-ai-dev]

📄 44,398% (443.98x) speedup for sorter in code_to_optimize/bubble_sort.py

⏱️ Runtime : 230 milliseconds → 517 microseconds (best of 513 runs)

📝 Explanation and details

The current implementation of the sorter function uses Bubble Sort, which has a worst-case time complexity of O(n^2). This can be improved to O(n log n) by using the built-in sorting function in Python, which is highly optimized.

Here's the updated code.

Python's built-in sort function uses Timsort, which has a time complexity of O(n log n). This significantly improves the performance over the original Bubble Sort implementation. The function signatures and print statements are preserved as requested.

✅ Correctness verification report:

Test	Status
⚙️ Existing Unit Tests	🔘 None Found
🌀 Generated Regression Tests	✅ 73 Passed
⏪ Replay Tests	✅ 9 Passed
🔎 Concolic Coverage Tests	🔘 None Found
📊 Tests Coverage	100.0%

🌀 Generated Regression Tests Details

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

# unit tests

def test_empty_list():
    # Test empty list
    codeflash_output = sorter([])

def test_single_element_list():
    # Test single element list
    codeflash_output = sorter([1])
    codeflash_output = sorter([0])
    codeflash_output = sorter([-1])

def test_two_elements_list():
    # Test two elements list
    codeflash_output = sorter([2, 1])
    codeflash_output = sorter([1, 2])
    codeflash_output = sorter([0, -1])

def test_already_sorted_list():
    # Test already sorted list
    codeflash_output = sorter([1, 2, 3, 4, 5])
    codeflash_output = sorter([-5, -4, -3, -2, -1])
    codeflash_output = sorter([0, 1, 2, 3, 4])

def test_reverse_sorted_list():
    # Test reverse sorted list
    codeflash_output = sorter([5, 4, 3, 2, 1])
    codeflash_output = sorter([3, 2, 1, 0, -1])
    codeflash_output = sorter([10, 9, 8, 7, 6])

def test_list_with_duplicates():
    # Test list with duplicates
    codeflash_output = sorter([3, 1, 2, 3, 1])
    codeflash_output = sorter([5, 5, 5, 5, 5])
    codeflash_output = sorter([2, 1, 2, 1, 2])

def test_list_with_negative_numbers():
    # Test list with negative numbers
    codeflash_output = sorter([3, -1, 2, -3, 1])
    codeflash_output = sorter([-5, -1, -3, -2, -4])
    codeflash_output = sorter([0, -1, -2, -3, -4])

def test_mixed_positive_and_negative_numbers():
    # Test mixed positive and negative numbers
    codeflash_output = sorter([3, -1, 2, -3, 1])
    codeflash_output = sorter([0, -1, 1, -2, 2])
    codeflash_output = sorter([-2, -1, 0, 1, 2])

def test_large_list():
    # Test large list
    codeflash_output = sorter(list(range(1000, 0, -1)))
    # Note: The following test is commented out to avoid long execution time during normal testing
    # assert sorter(list(range(10000, 0, -1))) == list(range(1, 10001))

def test_list_with_floating_point_numbers():
    # Test list with floating point numbers
    codeflash_output = sorter([3.1, 2.2, 1.3, 0.4, -1.5])
    codeflash_output = sorter([1.1, 1.01, 1.001, 1.0001])
    codeflash_output = sorter([-1.1, -2.2, -3.3, -4.4, -5.5])

def test_list_with_integers_and_floats():
    # Test list with integers and floats
    codeflash_output = sorter([3, 2.2, 1, 0.4, -1])
    codeflash_output = sorter([1.1, 1, 0.9, 2])
    codeflash_output = sorter([-1, -2.2, -3, -4.4, -5])

def test_list_with_repeated_patterns():
    # Test list with repeated patterns
    codeflash_output = sorter([1, 2, 1, 2, 1, 2])
    codeflash_output = sorter([3, 3, 2, 2, 1, 1])
    codeflash_output = sorter([4, 4, 4, 3, 3, 3, 2, 2, 2])

def test_list_with_zeroes():
    # Test list with zeroes
    codeflash_output = sorter([0, 0, 0, 0, 0])
    codeflash_output = sorter([3, 0, 2, 0, 1, 0])
    codeflash_output = sorter([0, -1, -2, 0, 1, 2])

def test_list_with_large_numbers():
    # Test list with large numbers
    codeflash_output = sorter([1000000000, 500000000, 100000000, 50000000, 10000000])
    codeflash_output = sorter([999999999, 888888888, 777777777, 666666666, 555555555])
    codeflash_output = sorter([1000000000, 1, 100000000, 10, 10000000])

def test_list_with_small_numbers():
    # Test list with small numbers
    codeflash_output = sorter([0.0000001, 0.0000005, 0.0000002, 0.0000004, 0.0000003])
    codeflash_output = sorter([0.0000009, 0.0000008, 0.0000007, 0.0000006, 0.0000005])
    codeflash_output = sorter([0.000001, 0.00001, 0.0001, 0.001, 0.01])
# 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 random test data

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

# unit tests

# Basic Functionality
def test_simple_unsorted_list():
    codeflash_output = sorter([3, 1, 2])
    codeflash_output = sorter([5, 3, 8, 6, 2])

def test_already_sorted_list():
    codeflash_output = sorter([1, 2, 3])
    codeflash_output = sorter([2, 4, 6, 8, 10])

def test_reverse_sorted_list():
    codeflash_output = sorter([3, 2, 1])
    codeflash_output = sorter([10, 8, 6, 4, 2])

# Edge Cases
def test_empty_list():
    codeflash_output = sorter([])

def test_single_element_list():
    codeflash_output = sorter([1])
    codeflash_output = sorter([42])

def test_all_elements_same():
    codeflash_output = sorter([1, 1, 1])
    codeflash_output = sorter([5, 5, 5, 5, 5])

# Lists with Negative Numbers
def test_mixed_positive_negative():
    codeflash_output = sorter([3, -1, 2])
    codeflash_output = sorter([-5, 3, -8, 6, 2])

def test_all_negative():
    codeflash_output = sorter([-3, -1, -2])
    codeflash_output = sorter([-10, -8, -6, -4, -2])

# Lists with Floating Point Numbers
def test_mixed_integers_floats():
    codeflash_output = sorter([3.5, 1.2, 2.8])
    codeflash_output = sorter([5, 3.3, 8, 6.6, 2])

def test_all_floats():
    codeflash_output = sorter([1.1, 2.2, 3.3])
    codeflash_output = sorter([2.5, 4.4, 6.6, 8.8, 10.1])

# Large Lists
def test_large_list_integers():
    codeflash_output = sorter(list(range(1000, 0, -1)))
    codeflash_output = sorter(list(range(1, 1001)))

def test_large_list_random_integers():
    random_list = random.sample(range(1, 1001), 1000)
    codeflash_output = sorter(random_list)

# Lists with Duplicate Elements
def test_some_duplicates():
    codeflash_output = sorter([3, 1, 2, 1, 3])
    codeflash_output = sorter([5, 3, 8, 6, 2, 8, 3])

def test_many_duplicates():
    codeflash_output = sorter([1, 1, 1, 2, 2, 2])
    codeflash_output = sorter([5, 5, 5, 5, 5, 5, 5])

# Lists with Varying Data Types
def test_integers_and_floats():
    codeflash_output = sorter([1, 2.2, 3, 4.4, 5])
    codeflash_output = sorter([5, 3.3, 8, 6.6, 2])

# Large Scale Performance Tests
def test_very_large_list():
    large_list = list(range(1000000, 999000, -1))
    codeflash_output = sorter(large_list)
    large_random_list = [random.randint(1, 1000000) for _ in range(1000)]
    codeflash_output = sorter(large_random_list)

# Stability Test (Preserving Order of Equal Elements)
def test_stability():
    codeflash_output = sorter([(1, 'a'), (1, 'b'), (1, 'c')])
    codeflash_output = sorter([(2, 'x'), (1, 'y'), (2, 'z')])
# 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-m8qif4u6 and push.