⚡️ Speed up function _find_type_node by 18% in PR #1199 (omni-java)#1292
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codeflash-ai[bot] wants to merge 1 commit intoomni-javafrom
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⚡️ Speed up function _find_type_node by 18% in PR #1199 (omni-java)#1292codeflash-ai[bot] wants to merge 1 commit intoomni-javafrom
_find_type_node by 18% in PR #1199 (omni-java)#1292codeflash-ai[bot] wants to merge 1 commit intoomni-javafrom
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The optimized code achieves a **17% runtime improvement** by eliminating repeated dictionary creation overhead in a recursive function. **Key Optimization:** The critical change is moving the `type_declarations` dictionary from inside the function to module-level as `_TYPE_DECLARATIONS`. In the original code, this dictionary was recreated on every function call, including all recursive calls. The line profiler shows this dictionary construction consumed ~27% of the function's time (lines allocating "class_declaration", "interface_declaration", and "enum_declaration"). **Why This Improves Performance:** - **Eliminates allocation overhead**: Dictionary creation, even for small dicts, involves memory allocation and hashing operations on each call - **Critical in recursive contexts**: Since `_find_type_node` recursively traverses a tree structure, the dictionary was being recreated multiple times per search operation (25 hits in the profiler) - **Constant lookup cost**: Module-level constants are created once at import time and accessed via faster LOAD_GLOBAL bytecode operations **Test Results Analysis:** The optimization shows consistent gains across all test cases: - **Deep nesting scenarios** (19% faster): Maximum benefit when recursion depth is high, as dictionary recreation is avoided on each level - **Multiple type scenarios** (18-22% faster): When traversing multiple sibling nodes, the savings compound - **Early termination cases** (20% faster): Even when a match is found quickly, avoiding the dictionary creation overhead provides measurable gains The profiler confirms the improvement: total function time decreased from 140.23μs to 115.17μs, with the dictionary construction lines completely eliminated from the optimized version. This optimization is particularly valuable when parsing large Java ASTs with deep nesting or when this function is called frequently in a hot path, as the per-call overhead reduction scales with usage frequency.
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⚡️ 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.📄 18% (0.18x) speedup for
_find_type_nodeincodeflash/languages/java/context.py⏱️ Runtime :
25.3 microseconds→21.4 microseconds(best of34runs)📝 Explanation and details
The optimized code achieves a 17% runtime improvement by eliminating repeated dictionary creation overhead in a recursive function.
Key Optimization:
The critical change is moving the
type_declarationsdictionary from inside the function to module-level as_TYPE_DECLARATIONS. In the original code, this dictionary was recreated on every function call, including all recursive calls. The line profiler shows this dictionary construction consumed ~27% of the function's time (lines allocating "class_declaration", "interface_declaration", and "enum_declaration").Why This Improves Performance:
_find_type_noderecursively traverses a tree structure, the dictionary was being recreated multiple times per search operation (25 hits in the profiler)Test Results Analysis:
The optimization shows consistent gains across all test cases:
The profiler confirms the improvement: total function time decreased from 140.23μs to 115.17μs, with the dictionary construction lines completely eliminated from the optimized version.
This optimization is particularly valuable when parsing large Java ASTs with deep nesting or when this function is called frequently in a hot path, as the per-call overhead reduction scales with usage frequency.
✅ Correctness verification report:
🌀 Click to see Generated Regression Tests
To edit these changes
git checkout codeflash/optimize-pr1199-2026-02-03T07.19.45and push.