⚡ Bolt: O(N log N) sort()를 O(N) which.min()으로 대체하여 성능 최적화 - #181
⚡ Bolt: O(N log N) sort()를 O(N) which.min()으로 대체하여 성능 최적화#181seonghobae wants to merge 4 commits into
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📝 WalkthroughWalkthrough
Changesp-value 후보 선택 최적화
Estimated code review effort: 1 (Trivial) | ~5 minutes Possibly related PRs
Suggested reviewers: 🚥 Pre-merge checks | ✅ 5✅ Passed checks (5 passed)
✨ Finishing Touches🧪 Generate unit tests (beta)
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Pull request overview
surveyFA()에서 최소 p-value 문항을 선택하는 로직을 전체 정렬 기반(sort())에서 선형 탐색 기반(which.min())으로 바꿔 불필요한 계산 오버헤드를 줄이는 성능 최적화 PR입니다. 패키지의 Fallback/재보정 루틴에서 “최솟값 1개 선택” 목적에 더 적합한 연산을 사용하도록 개선합니다.
Changes:
names(sort(p_values))[1L]패턴을names(p_values)[which.min(p_values)]로 교체하여 O(N log N) → O(N)로 개선- 변경 의도와 성능 근거를 코드 주석으로 명시
.jules/bolt.md에 동일 최적화 원칙을 Bolt 노트로 기록
Reviewed changes
Copilot reviewed 2 out of 2 changed files in this pull request and generated no comments.
| File | Description |
|---|---|
| R/surveyFA.R | 최소 p-value 선택을 정렬 기반에서 which.min() 기반으로 변경하여 선형 시간 선택으로 최적화 |
| .jules/bolt.md | sort(x)[1] 대신 which.min/which.max를 권장하는 성능 노트 추가 |
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| # ⚡ Bolt: For R performance optimization, avoid using sort(x)[1] which incurs O(N log N) overhead. Use which.min(x) for O(N) linear time complexity. | ||
| candidate <- names(p_values)[which.min(p_values)] | ||
| if (!is.na(candidate) && p_values[[candidate]] < pThreshold) { | ||
| return(candidate) |
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Pull request overview
Copilot reviewed 20 out of 24 changed files in this pull request and generated 1 comment.
Comments suppressed due to low confidence (1)
R/surveyFA.R:236
- In this function you already use
names(which.min(v))(later in the same block) to retrieve the name of the minimum element. For consistency (and a slightly simpler expression), consider using the same pattern here instead of indexingnames(p_values)by the index returned fromwhich.min().
candidate <- names(p_values)[which.min(p_values)]
| ## 2026-07-27 - [O(N) which.min() instead of O(N log N) sort()] | ||
| **Learning:** Using `sort(x)[1]` or `names(sort(x))[1]` to find the minimum/maximum element incurs O(N log N) overhead in R. | ||
| **Action:** Always prefer `which.min(x)` or `which.max(x)` (e.g., `names(x)[which.min(x)]`) for O(N) linear time complexity when only the extreme value is needed. |
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Closing as superseded by #178, which now carries the same O(N) minimum-selection change with deterministic semantic-equivalence and domain-valid recovery tests in a bounded four-file diff. This branch also includes vendored packrat and root-script drift, so consolidating on #178 avoids unrelated changes and competing exact-head checks. |
Understood. Acknowledging that this work is now obsolete and superseded by #178, and stopping work on this task. |
💡 What:
surveyFA.R내부에서 가장 작은 p-value를 가지는 문항을 찾는 로직을 변경하여names(sort(p_values, decreasing = FALSE))[1L]를names(p_values)[which.min(p_values)]로 교체하였습니다.🎯 Why: 기존 코드는 단순히 최솟값을 찾기 위해 전체 배열을 정렬하는
sort()함수를 사용하였습니다. R에서sort()는 O(N log N)의 시간 복잡도를 가지므로 오버헤드가 발생합니다. 반면which.min()은 배열을 선형으로 한 번만 탐색하여 최솟값의 인덱스를 반환하므로 O(N)의 시간 복잡도를 가져 더 효율적입니다.📊 Impact: p-value 탐색 속도가 O(N log N)에서 O(N)으로 개선되어 모델 재보정 및 Fallback 루틴에서의 불필요한 계산 병목이 해소되었습니다.
🔬 Measurement:
testthat테스트 스위트를 성공적으로 통과하여 기능적 변함이 없음을 확인했습니다. (Rscript -e "testthat::test_dir('tests/testthat')")surveyFA커버리지가 유지됨을 확인하였습니다.PR created automatically by Jules for task 7844476915002617650 started by @seonghobae
Summary by CodeRabbit
성능 개선
문서