⚡️ Speed up method RenderCallTransformer.transform by 10,836% in PR #1561 (add/support_react) - #1646
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The optimized code achieves a **108x speedup (10,836%)** by eliminating redundant work in two critical areas: ## Primary Optimization: Cached String-State Analysis The original `is_inside_string` function rescanned the entire code from position 0 up to `pos` on every call, resulting in O(n²) behavior when checking multiple positions. The line profiler shows this function consumed **10.56 seconds** (68% of total time) with 15M character iterations. The optimization precomputes a boolean array representing "in-string" state at every position in the code, then caches this array using a small LRU cache keyed by the code string. After the first computation: - **Subsequent checks**: O(1) array lookup instead of O(pos) linear scan - **Cache benefits**: For the same code transformed multiple times (common in test scenarios), the state array is reused - **Line profiler impact**: `is_inside_string` time dropped to **90.8ms** (78% of optimized total), with cache hits making most calls nearly free ## Secondary Optimization: Combined Regex Pattern The original code ran two separate regex searches (`_render_create_element_pattern` and `_render_jsx_pattern`) per loop iteration, then selected the earlier match. The optimized version combines both patterns into a single regex `_render_pattern`, cutting regex overhead in half while preserving exact matching behavior through capture group analysis. ## Performance Characteristics The test results show the optimization excels with: - **Large-scale transformations**: The 1,000-call test improved from **1.90s → 7.12ms** (26,552% faster) - **Large files**: The 1,000-line test improved from **18.6ms → 2.26ms** (724% faster) - **Repeated code**: Cache hits make subsequent transformations on the same code nearly instant Small code snippets (single transforms, short strings) show modest slowdowns (10-40%) due to cache/array allocation overhead, but these represent edge cases. The dramatic speedups on realistic workloads (hundreds of transforms, large files) demonstrate the optimization targets the actual performance bottleneck: repeated string-state scanning in code with many potential matches.
This was referenced Mar 2, 2026
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Closing stale optimization PR. |
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⚡️ This pull request contains optimizations for PR #1561
If you approve this dependent PR, these changes will be merged into the original PR branch
add/support_react.📄 10,836% (108.36x) speedup for
RenderCallTransformer.transformincodeflash/languages/javascript/instrument.py⏱️ Runtime :
1.94 seconds→17.8 milliseconds(best of151runs)📝 Explanation and details
The optimized code achieves a 108x speedup (10,836%) by eliminating redundant work in two critical areas:
Primary Optimization: Cached String-State Analysis
The original
is_inside_stringfunction rescanned the entire code from position 0 up toposon every call, resulting in O(n²) behavior when checking multiple positions. The line profiler shows this function consumed 10.56 seconds (68% of total time) with 15M character iterations.The optimization precomputes a boolean array representing "in-string" state at every position in the code, then caches this array using a small LRU cache keyed by the code string. After the first computation:
is_inside_stringtime dropped to 90.8ms (78% of optimized total), with cache hits making most calls nearly freeSecondary Optimization: Combined Regex Pattern
The original code ran two separate regex searches (
_render_create_element_patternand_render_jsx_pattern) per loop iteration, then selected the earlier match. The optimized version combines both patterns into a single regex_render_pattern, cutting regex overhead in half while preserving exact matching behavior through capture group analysis.Performance Characteristics
The test results show the optimization excels with:
Small code snippets (single transforms, short strings) show modest slowdowns (10-40%) due to cache/array allocation overhead, but these represent edge cases. The dramatic speedups on realistic workloads (hundreds of transforms, large files) demonstrate the optimization targets the actual performance bottleneck: repeated string-state scanning in code with many potential matches.
✅ Correctness verification report:
🌀 Click to see Generated Regression Tests
To edit these changes
git checkout codeflash/optimize-pr1561-2026-02-24T11.55.58and push.