Skip to content

Conversation

@codeflash-ai
Copy link
Contributor

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

⚡️ This pull request contains optimizations for PR #687

If you approve this dependent PR, these changes will be merged into the original PR branch granular-async-instrumentation.

This PR will be automatically closed if the original PR is merged.


📄 37% (0.37x) speedup for compare_test_results in codeflash/verification/equivalence.py

⏱️ Runtime : 742 microseconds 540 microseconds (best of 5 runs)

📝 Explanation and details

The optimized code achieves a 37% speedup through several key micro-optimizations in the comparator function, which is the performance bottleneck (consuming 80% of runtime):

Primary Optimization - Identity Check: Added if orig is new: return True at the start of comparator. This short-circuits expensive recursive comparisons when objects are identical in memory, which happens frequently when comparing the same data structures.

Loop Optimizations: Replaced all() generator expressions with explicit for loops in multiple places:

  • List/tuple comparisons: Changed from all(comparator(elem1, elem2, superset_obj) for elem1, elem2 in zip(orig, new)) to a loop with early return on first mismatch
  • Dictionary comparisons: Converted all(k in new and comparator(v, new[k], superset_obj) for k, v in orig.items()) to explicit iteration
  • Similar changes for numpy arrays and class object comparisons

This eliminates the overhead of generator creation and the all() function call, while enabling faster short-circuit evaluation.

Why This Works: The all() function with generators creates additional Python objects and function call overhead. Direct loops with early returns are more efficient, especially when mismatches occur early in the comparison (which triggers the short-circuit behavior).

Test Case Performance: The optimizations are particularly effective for test cases with:

  • Identical objects (benefits from identity check)
  • Large nested data structures where early mismatches occur
  • Complex recursive comparisons where avoiding generator overhead accumulates significant savings

The optimizations maintain identical behavior while reducing function call overhead and memory allocations during the comparison process.

Correctness verification report:

Test Status
⚙️ Existing Unit Tests 34 Passed
🌀 Generated Regression Tests 🔘 None Found
⏪ Replay Tests 🔘 None Found
🔎 Concolic Coverage Tests 🔘 None Found
📊 Tests Coverage 72.9%
⚙️ Existing Unit Tests and Runtime
Test File::Test Function Original ⏱️ Optimized ⏱️ Speedup
test_codeflash_capture.py::test_codeflash_capture_basic 43.7μs 41.2μs 5.90%✅
test_codeflash_capture.py::test_codeflash_capture_multiple_helpers 51.1μs 43.5μs 17.6%✅
test_codeflash_capture.py::test_codeflash_capture_recursive 44.2μs 36.8μs 20.1%✅
test_codeflash_capture.py::test_codeflash_capture_super_init 45.4μs 41.6μs 9.30%✅
test_codeflash_capture.py::test_instrument_codeflash_capture_and_run_tests 55.9μs 47.6μs 17.5%✅
test_comparator.py::test_compare_results_fn 60.6μs 57.8μs 4.87%✅
test_instrument_all_and_run.py::test_bubble_sort_behavior_results 44.3μs 39.7μs 11.6%✅
test_instrument_all_and_run.py::test_class_method_full_instrumentation 57.2μs 28.5μs 100%✅
test_instrumentation_run_results_aiservice.py::test_class_method_full_instrumentation 44.6μs 36.5μs 22.2%✅
test_instrumentation_run_results_aiservice.py::test_class_method_test_instrumentation_only 36.1μs 29.1μs 24.1%✅
test_pickle_patcher.py::test_run_and_parse_picklepatch 259μs 138μs 87.4%✅

To edit these changes git checkout codeflash/optimize-pr687-2025-09-13T01.22.10 and push.

Codeflash

The optimized code achieves a **37% speedup** through several key micro-optimizations in the `comparator` function, which is the performance bottleneck (consuming 80% of runtime):

**Primary Optimization - Identity Check**: Added `if orig is new: return True` at the start of `comparator`. This short-circuits expensive recursive comparisons when objects are identical in memory, which happens frequently when comparing the same data structures.

**Loop Optimizations**: Replaced `all()` generator expressions with explicit `for` loops in multiple places:
- List/tuple comparisons: Changed from `all(comparator(elem1, elem2, superset_obj) for elem1, elem2 in zip(orig, new))` to a loop with early return on first mismatch
- Dictionary comparisons: Converted `all(k in new and comparator(v, new[k], superset_obj) for k, v in orig.items())` to explicit iteration
- Similar changes for numpy arrays and class object comparisons

This eliminates the overhead of generator creation and the `all()` function call, while enabling faster short-circuit evaluation.

**Why This Works**: The `all()` function with generators creates additional Python objects and function call overhead. Direct loops with early returns are more efficient, especially when mismatches occur early in the comparison (which triggers the short-circuit behavior).

**Test Case Performance**: The optimizations are particularly effective for test cases with:
- Identical objects (benefits from identity check)
- Large nested data structures where early mismatches occur
- Complex recursive comparisons where avoiding generator overhead accumulates significant savings

The optimizations maintain identical behavior while reducing function call overhead and memory allocations during the comparison process.
@codeflash-ai codeflash-ai bot added the ⚡️ codeflash Optimization PR opened by Codeflash AI label Sep 13, 2025
@misrasaurabh1
Copy link
Contributor

wow, this is an important function to optimize!

@KRRT7 KRRT7 changed the base branch from granular-async-instrumentation to main September 13, 2025 01:30
@KRRT7 KRRT7 changed the base branch from main to granular-async-instrumentation September 13, 2025 01:31
@KRRT7 KRRT7 merged commit 324f607 into granular-async-instrumentation Sep 13, 2025
17 of 20 checks passed
@codeflash-ai codeflash-ai bot deleted the codeflash/optimize-pr687-2025-09-13T01.22.10 branch September 13, 2025 01:31
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