⚡️ Speed up function _add_behavior_instrumentation by 22% in PR #1199 (omni-java)#1294
Merged
misrasaurabh1 merged 1 commit intoomni-javafrom Feb 3, 2026
Merged
Conversation
This optimization achieves a **22% runtime improvement** (4.44ms → 3.63ms) by addressing three key performance bottlenecks:
## Primary Optimization: Cached Regex Compilation (29.7% of optimized runtime)
The original code compiled the same regex pattern 202 times inside a loop (consuming 17.8% of runtime). The optimized version introduces:
```python
@lru_cache(maxsize=128)
def _get_method_call_pattern(func_name: str):
return re.compile(...)
```
This caches compiled patterns, eliminating redundant compilation. While the first call appears slower in the line profiler (9.3ms vs 8.3ms total), this is because it includes cache initialization overhead. Subsequent calls benefit from instant retrieval, making this optimization particularly valuable when:
- Instrumenting multiple test methods in sequence
- Processing classes with many `@Test` methods (e.g., the 50-method test shows 14.8% speedup)
## Secondary Optimization: Efficient Brace Counting
The original code iterated character-by-character through method bodies (23.4% of runtime):
```python
for ch in body_line:
if ch == "{": brace_depth += 1
elif ch == "}": brace_depth -= 1
```
The optimized version uses Python's built-in string methods:
```python
open_count = body_line.count('{')
close_count = body_line.count('}')
brace_depth += open_count - close_count
```
This change shows dramatic improvements in tests with deeply nested structures:
- 10-level nested braces: 66.4% faster
- Large method bodies (100+ lines): 44.0% faster
- Methods with many variables (500+): 88.9% faster
## Performance Characteristics
The optimization excels in scenarios common to Java test instrumentation:
- **Multiple test methods**: 11-15% speedup for classes with 30-100 test methods
- **Complex method bodies**: 29-44% speedup for methods with many nested structures or statements
- **Sequential processing**: Benefits accumulate when instrumenting multiple files due to regex caching
The minor slowdowns (3-9%) in trivial cases (empty methods, minimal source) are negligible compared to the substantial gains in realistic workloads, where Java test classes typically contain multiple complex test methods.
Merged
This file contains hidden or bidirectional Unicode text that may be interpreted or compiled differently than what appears below. To review, open the file in an editor that reveals hidden Unicode characters.
Learn more about bidirectional Unicode characters
Sign up for free
to join this conversation on GitHub.
Already have an account?
Sign in to comment
Add this suggestion to a batch that can be applied as a single commit.This suggestion is invalid because no changes were made to the code.Suggestions cannot be applied while the pull request is closed.Suggestions cannot be applied while viewing a subset of changes.Only one suggestion per line can be applied in a batch.Add this suggestion to a batch that can be applied as a single commit.Applying suggestions on deleted lines is not supported.You must change the existing code in this line in order to create a valid suggestion.Outdated suggestions cannot be applied.This suggestion has been applied or marked resolved.Suggestions cannot be applied from pending reviews.Suggestions cannot be applied on multi-line comments.Suggestions cannot be applied while the pull request is queued to merge.Suggestion cannot be applied right now. Please check back later.
⚡️ This pull request contains optimizations for PR #1199
If you approve this dependent PR, these changes will be merged into the original PR branch
omni-java.📄 22% (0.22x) speedup for
_add_behavior_instrumentationincodeflash/languages/java/instrumentation.py⏱️ Runtime :
4.44 milliseconds→3.63 milliseconds(best of250runs)📝 Explanation and details
This optimization achieves a 22% runtime improvement (4.44ms → 3.63ms) by addressing three key performance bottlenecks:
Primary Optimization: Cached Regex Compilation (29.7% of optimized runtime)
The original code compiled the same regex pattern 202 times inside a loop (consuming 17.8% of runtime). The optimized version introduces:
This caches compiled patterns, eliminating redundant compilation. While the first call appears slower in the line profiler (9.3ms vs 8.3ms total), this is because it includes cache initialization overhead. Subsequent calls benefit from instant retrieval, making this optimization particularly valuable when:
@Testmethods (e.g., the 50-method test shows 14.8% speedup)Secondary Optimization: Efficient Brace Counting
The original code iterated character-by-character through method bodies (23.4% of runtime):
The optimized version uses Python's built-in string methods:
This change shows dramatic improvements in tests with deeply nested structures:
Performance Characteristics
The optimization excels in scenarios common to Java test instrumentation:
The minor slowdowns (3-9%) in trivial cases (empty methods, minimal source) are negligible compared to the substantial gains in realistic workloads, where Java test classes typically contain multiple complex test methods.
✅ Correctness verification report:
🌀 Click to see Generated Regression Tests
To edit these changes
git checkout codeflash/optimize-pr1199-2026-02-03T08.18.57and push.