⚡️ Speed up function funcA by 4,000%

[codeflash-ai]

📄 4,000% (40.00x) speedup for funcA in code_to_optimize/code_directories/simple_tracer_e2e/workload.py

⏱️ Runtime : 51.4 milliseconds → 1.25 milliseconds (best of 342 runs)

📝 Explanation and details

Here’s an optimized version of your program.

What was improved:

• Replaced explicit loops and sum(range(...)) with the arithmetic progression formula for improved constant-time performance.
• Switched from a generator expression in join to map(str, ...) for slightly better speed and lower memory usage with large numbers.

✅ Correctness verification report:

Test	Status
⚙️ Existing Unit Tests	🔘 None Found
🌀 Generated Regression Tests	✅ 48 Passed
⏪ Replay Tests	✅ 3 Passed
🔎 Concolic Coverage Tests	🔘 None Found
📊 Tests Coverage	100.0%

🌀 Generated Regression Tests and Runtime

import pytest  # used for our unit tests
from workload import funcA

# unit tests

# --------------------
# Basic Test Cases
# --------------------

def test_funcA_zero():
    # Basic: number = 0, expect empty string
    codeflash_output = funcA(0) # 2.81μs -> 2.05μs (37.0% faster)

def test_funcA_one():
    # Basic: number = 1, expect "0"
    codeflash_output = funcA(1) # 6.02μs -> 2.25μs (168% faster)

def test_funcA_small_number():
    # Basic: number = 5, expect "0 1 2 3 4"
    codeflash_output = funcA(5) # 18.6μs -> 2.71μs (587% faster)

def test_funcA_typical_number():
    # Basic: number = 10, expect "0 1 2 3 4 5 6 7 8 9"
    codeflash_output = funcA(10) # 34.2μs -> 3.11μs (1000% faster)

# --------------------
# Edge Test Cases
# --------------------

def test_funcA_negative_number():
    # Edge: negative number, range(negative) is empty, expect empty string
    codeflash_output = funcA(-5) # 2.60μs -> 1.97μs (31.5% faster)

def test_funcA_large_number_exactly_1000():
    # Edge: number = 1000, should not be capped, expect string from 0 to 999
    codeflash_output = funcA(1000); result = codeflash_output # 3.44ms -> 79.5μs (4225% faster)
    expected = " ".join(str(i) for i in range(1000))

def test_funcA_large_number_above_1000():
    # Edge: number = 1001, should be capped at 1000
    codeflash_output = funcA(1001); result = codeflash_output # 3.40ms -> 77.3μs (4295% faster)
    expected = " ".join(str(i) for i in range(1000))

def test_funcA_large_number_far_above_1000():
    # Edge: number = 5000, should be capped at 1000
    codeflash_output = funcA(5000); result = codeflash_output # 3.38ms -> 77.6μs (4257% faster)
    expected = " ".join(str(i) for i in range(1000))

def test_funcA_number_is_float():
    # Edge: number is a float, should raise TypeError
    with pytest.raises(TypeError):
        funcA(5.5)

def test_funcA_number_is_string():
    # Edge: number is a string, should raise TypeError
    with pytest.raises(TypeError):
        funcA("10")

def test_funcA_number_is_none():
    # Edge: number is None, should raise TypeError
    with pytest.raises(TypeError):
        funcA(None)

def test_funcA_number_is_bool():
    # Edge: number is boolean, True should be treated as 1, False as 0
    codeflash_output = funcA(True) # 6.52μs -> 2.85μs (129% faster)
    codeflash_output = funcA(False) # 1.69μs -> 1.47μs (14.9% faster)

def test_funcA_number_is_list():
    # Edge: number is a list, should raise TypeError
    with pytest.raises(TypeError):
        funcA([10])

def test_funcA_number_is_dict():
    # Edge: number is a dict, should raise TypeError
    with pytest.raises(TypeError):
        funcA({'a': 1})

# --------------------
# Large Scale Test Cases
# --------------------

def test_funcA_large_scale_500():
    # Large scale: number = 500, check output length and content
    codeflash_output = funcA(500); result = codeflash_output # 1.64ms -> 40.4μs (3970% faster)
    expected = " ".join(str(i) for i in range(500))

def test_funcA_large_scale_999():
    # Large scale: number = 999, check output length and content
    codeflash_output = funcA(999); result = codeflash_output # 3.39ms -> 78.5μs (4227% faster)
    expected = " ".join(str(i) for i in range(999))

def test_funcA_large_scale_1000():
    # Large scale: number = 1000, check output length and content
    codeflash_output = funcA(1000); result = codeflash_output # 3.40ms -> 77.3μs (4292% faster)
    expected = " ".join(str(i) for i in range(1000))

def test_funcA_performance_upper_bound():
    # Large scale: number = 1000, ensure function runs within reasonable time
    import time
    start = time.time()
    codeflash_output = funcA(1000); result = codeflash_output # 3.41ms -> 77.0μs (4335% faster)
    duration = time.time() - start
    # Check correctness
    expected = " ".join(str(i) for i in range(1000))

# --------------------
# Mutation-sensitive: ensure internal logic is tested
# --------------------

def test_funcA_mutation_sensitive():
    # If the range is off-by-one, the output will differ
    codeflash_output = funcA(10); result = codeflash_output # 34.9μs -> 3.18μs (998% faster)
    # Should not contain duplicate numbers
    tokens = result.split()

# --------------------
# Additional: Idempotence and Consistency
# --------------------

def test_funcA_idempotence():
    # Calling funcA twice with the same input should yield the same result
    codeflash_output = funcA(10) # 34.2μs -> 2.96μs (1056% faster)

def test_funcA_consistency_for_capped_values():
    # All numbers >= 1000 should yield the same result
    codeflash_output = funcA(1000); result_1000 = codeflash_output # 3.42ms -> 77.7μs (4299% faster)
    codeflash_output = funcA(1001); result_1001 = codeflash_output # 3.40ms -> 75.0μs (4429% faster)
    codeflash_output = funcA(5000); result_5000 = codeflash_output # 3.39ms -> 74.5μs (4458% faster)
# codeflash_output is used to check that the output of the original code is the same as that of the optimized code.

import pytest  # used for our unit tests
from workload import funcA

# unit tests

# 1. Basic Test Cases

def test_funcA_zero():
    # Test with number = 0 (should return empty string)
    codeflash_output = funcA(0) # 2.69μs -> 2.08μs (28.9% faster)

def test_funcA_one():
    # Test with number = 1 (should return "0")
    codeflash_output = funcA(1) # 6.01μs -> 2.28μs (163% faster)

def test_funcA_small_number():
    # Test with number = 5 (should return "0 1 2 3 4")
    codeflash_output = funcA(5) # 18.5μs -> 2.65μs (600% faster)

def test_funcA_typical_number():
    # Test with number = 10 (should return "0 1 2 3 4 5 6 7 8 9")
    codeflash_output = funcA(10) # 34.3μs -> 3.00μs (1046% faster)

def test_funcA_typical_number_spacing():
    # Test that output has correct spacing (no trailing space)
    codeflash_output = funcA(3); result = codeflash_output # 11.7μs -> 2.34μs (398% faster)

# 2. Edge Test Cases

def test_funcA_negative_number():
    # Test with negative number (should return empty string, as range(negative) is empty)
    codeflash_output = funcA(-5) # 2.35μs -> 1.86μs (26.3% faster)

def test_funcA_large_number_limit():
    # Test with number = 1000 (should be capped at 1000, last number is 999)
    codeflash_output = funcA(1000); result = codeflash_output # 3.42ms -> 78.3μs (4263% faster)
    expected = " ".join(str(i) for i in range(1000))

def test_funcA_above_limit():
    # Test with number > 1000 (should be capped at 1000)
    codeflash_output = funcA(1500); result = codeflash_output # 3.42ms -> 77.1μs (4338% faster)
    expected = " ".join(str(i) for i in range(1000))

def test_funcA_limit_minus_one():
    # Test with number just below the cap (999)
    codeflash_output = funcA(999); result = codeflash_output # 3.42ms -> 76.8μs (4353% faster)
    expected = " ".join(str(i) for i in range(999))

def test_funcA_non_integer_input():
    # Test with float input (should raise TypeError)
    with pytest.raises(TypeError):
        funcA(5.5)

def test_funcA_string_input():
    # Test with string input (should raise TypeError)
    with pytest.raises(TypeError):
        funcA("10")

def test_funcA_none_input():
    # Test with None input (should raise TypeError)
    with pytest.raises(TypeError):
        funcA(None)

def test_funcA_boolean_input():
    # Test with boolean input (True is 1, False is 0)
    codeflash_output = funcA(True) # 6.41μs -> 2.85μs (125% faster)
    codeflash_output = funcA(False) # 1.64μs -> 1.31μs (25.2% faster)

def test_funcA_large_negative_number():
    # Test with a large negative number (should return empty string)
    codeflash_output = funcA(-1000) # 2.42μs -> 2.21μs (9.48% faster)

# 3. Large Scale Test Cases

def test_funcA_large_scale_500():
    # Test with number = 500 (should return numbers 0 to 499)
    codeflash_output = funcA(500); result = codeflash_output # 1.65ms -> 40.0μs (4030% faster)
    expected = " ".join(str(i) for i in range(500))

def test_funcA_large_scale_999():
    # Test with number = 999 (should return numbers 0 to 998)
    codeflash_output = funcA(999); result = codeflash_output # 3.39ms -> 79.9μs (4150% faster)
    expected = " ".join(str(i) for i in range(999))

def test_funcA_performance_1000():
    # Test upper limit for performance (number = 1000)
    codeflash_output = funcA(1000); result = codeflash_output # 3.39ms -> 77.4μs (4284% faster)
    expected = " ".join(str(i) for i in range(1000))

# Additional edge: input is minimum possible integer
def test_funcA_minimum_integer():
    # For a very negative integer, should return empty string
    codeflash_output = funcA(-999999) # 2.60μs -> 2.25μs (15.6% faster)

# Additional edge: input is not provided (should raise TypeError)
def test_funcA_no_argument():
    with pytest.raises(TypeError):
        funcA()

# Additional edge: input is a list or other type (should raise TypeError)
@pytest.mark.parametrize("bad_input", [[], {}, set(), object()])
def test_funcA_bad_types(bad_input):
    with pytest.raises(TypeError):
        funcA(bad_input)
# 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-funcA-mcl2v01f and push.