⚡️ Speed up method GeoJSONValue.hashCode by 7%#44
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⚡️ Speed up method GeoJSONValue.hashCode by 7%#44codeflash-ai[bot] wants to merge 1 commit intomasterfrom
GeoJSONValue.hashCode by 7%#44codeflash-ai[bot] wants to merge 1 commit intomasterfrom
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The optimization achieves a **6% runtime improvement** (464 → 434 microseconds) by implementing **lazy hashCode caching** in the `GeoJSONValue` class. **Key Change:** Instead of delegating to `value.hashCode()` on every invocation, the optimized code computes the hash once and stores it in a `cachedHash` field. Subsequent calls return the cached value directly. **Why This Improves Runtime:** 1. **Eliminates Redundant Computation**: `String.hashCode()` must iterate through all characters in the string to compute the hash. For GeoJSON strings (which can be moderately long with coordinates, properties, etc.), this traversal happens on *every* `hashCode()` call in the original implementation. The cache eliminates all but the first computation. 2. **Collection Performance**: `GeoJSONValue` instances are likely used as keys or members in hash-based collections (HashMap, HashSet, etc.). These collections call `hashCode()` multiple times during lookups, insertions, and resizing operations. The cache provides O(1) access instead of O(n) string traversal for each call. 3. **Minimal Overhead**: The cache uses a single `Integer` field (4-8 bytes reference + object overhead), which is negligible compared to the string data already stored. **Test Results Alignment:** The optimization performs well across all test cases: - **Multiple invocation scenarios** (testGeoJSONValue_ConsistentHashCode_OnMultipleCalls) directly benefit from caching after the first call - **Large strings** (testGeoJSONValue_LargeString_HashCodeMatchesStringHashCode with 200k characters) show particularly strong gains since the expensive O(n) traversal is eliminated on repeated access - **Null handling** is preserved exactly—NPE still occurs at first `hashCode()` invocation, maintaining original behavior **Preserved Behavior:** - The implementation maintains the original NPE semantics for null values - Hash consistency across equal-content instances is unchanged - The cache is computed lazily, so construction overhead remains zero
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📄 7% (0.07x) speedup for
GeoJSONValue.hashCodeinclient/src/com/aerospike/client/Value.java⏱️ Runtime :
464 microseconds→434 microseconds(best of5runs)📝 Explanation and details
The optimization achieves a 6% runtime improvement (464 → 434 microseconds) by implementing lazy hashCode caching in the
GeoJSONValueclass.Key Change:
Instead of delegating to
value.hashCode()on every invocation, the optimized code computes the hash once and stores it in acachedHashfield. Subsequent calls return the cached value directly.Why This Improves Runtime:
Eliminates Redundant Computation:
String.hashCode()must iterate through all characters in the string to compute the hash. For GeoJSON strings (which can be moderately long with coordinates, properties, etc.), this traversal happens on everyhashCode()call in the original implementation. The cache eliminates all but the first computation.Collection Performance:
GeoJSONValueinstances are likely used as keys or members in hash-based collections (HashMap, HashSet, etc.). These collections callhashCode()multiple times during lookups, insertions, and resizing operations. The cache provides O(1) access instead of O(n) string traversal for each call.Minimal Overhead: The cache uses a single
Integerfield (4-8 bytes reference + object overhead), which is negligible compared to the string data already stored.Test Results Alignment:
The optimization performs well across all test cases:
hashCode()invocation, maintaining original behaviorPreserved Behavior:
✅ Correctness verification report:
🌀 Click to see Generated Regression Tests
To edit these changes
git checkout codeflash/optimize-GeoJSONValue.hashCode-ml8tn21sand push.