⚡ Bolt: computeTaskMetrics 루프 최적화 - #613
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📝 Info: Int32Array cache is behaviorally equivalent
Both loops iterate state.tasks in the same order over the unchanged array, so index alignment holds. calculateDurationDays returns non-negative integers within Int32 range given the 4-digit year cap, so no truncation. The index-based cache is more robust to duplicate task ids than the old id-keyed Map.
(Refers to this code)
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Closing this lane as semantically superseded by #508, not as a merge-readiness judgment. Fresh comparison against the same protected base #508 at exact head Current #613 review state also remains non-authorizing: CodeRabbit is rate-limited, Devin’s only current thread is informational semantic-equivalence evidence, and all six current-head workflow runs are queued. Those waits do not justify keeping a duplicate production lane open when the stronger owning lane already exists. Therefore #508 remains the single owning performance/evidence lane for this optimization. |
Understood. Acknowledging that this work is now obsolete and superseded by #508, and stopping work on this task. |
💡 무엇을
app.js의computeTaskMetrics함수 내에서 사용하던Map캐싱 로직을 제거하고, 대신 Task 개수만큼 미리 할당된 Typed Array(Int32Array)를 사용하도록 변경했습니다.reduce와forEach같은 고차 함수(Higher-Order Functions)를 이용한 순회를 성능이 더 우수한 기본for루프로 교체했습니다.🎯 왜
computeTaskMetrics는 화면 렌더링 사이클 등에서 매우 빈번하게 호출되는 핵심 병목(Hot-path) 함수입니다.Map은 삽입(set) 및 탐색(get) 시 해시 룩업(Hash-lookup) 비용이 발생합니다.reduce및forEach배열 메서드는 JS 엔진 수준에서 매 순회마다 콜백 함수를 호출해야 하므로 할당 및 실행(Execution) 오버헤드, 가비지 컬렉션(GC) 압박을 유발합니다.for루프를 사용하면 이 두 가지 병목 요소를 완전히 제거하여 O(N) 순회의 성능을 극대화할 수 있습니다.📊 영향
Map대신 고정 길이 타입 기반 배열(Int32Array)을 사용하여 메모리 힙 단편화와 가비지 컬렉터 부하를 완화했습니다. (큰 프로젝트에서 속도 개선 폭이 더 커짐)🔬 측정
computeTaskMetrics함수의 Scripting Time이 눈에 띄게 감소함을 확인할 수 있습니다.PR created automatically by Jules for task 8282498630000302187 started by @seonghobae