'regressions' 검색 결과

Classify failures in CI, automated checks run during development, to distinguish code regressions, temporary infrastructure problems, security test failures, and inconsistent results. Record each failure's category, suggested next action, and attempt count in a structured report.

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• Sort failed CI checks by likely cause
• Identify small regressions that may qualify for automatic fixes
• Refer infrastructure and security failures to a human

Investigate failing macOS tests in Xcode or SwiftPM by running a focused test scope, classifying errors, and separating setup issues from code regressions. Get a concise explanation of likely causes and the next verification step.

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• Narrowing down failing macOS tests
• Distinguishing setup issues from code regressions
• Investigating assertions and crashes

Save a baseline of a site's SEO state, then compare later runs to find changes in rankings, indexed pages, titles, and search directives. Use it to spot regressions after redesigns, migrations, or redeployments.

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• Saving an SEO baseline before site changes
• Checking SEO changes after a migration or redeployment
• Comparing current SEO with a previous snapshot

Checks whether a new version of a repository preserves the behavior observed by tests on the old version. Use this skill when comparing two versions of code to detect regressions, verify refactoring safety, validate bug fixes don't break existing functionality, or ensure backward compatibility. Detects differences in function outputs, exceptions, observable states, and performance between versions. Generates reports highlighting potential regressions (critical, high, medium, low severity), improvements, and areas requiring verification. Triggers when users ask to check for regressions between versions, compare test behavior across versions, verify behavior preservation, or validate that changes don't break existing tests.

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웹 페이지 표시와 조작, API 응답, 빌드와 테스트의 소요 시간을 측정합니다. 변경 전후 결과를 비교하고 Git으로 공유하는 기준값을 바탕으로 성능 저하를 확인합니다.

• 코드 변경 전후 성능을 비교합니다
• 페이지가 느리다는 보고를 조사합니다
• 출시 전 성능 목표를 확인합니다

원인 불명의 버그, 간헐적 이상, 성능 저하를 코드 변경 전에 조사합니다. 관찰한 증상과 추측을 구분하고 증거로 가설을 좁혀 원인과 근거를 보고합니다.

• 원인 불명의 버그 조사
• 간헐적으로 발생하는 이상 원인 조사
• 성능 저하의 원인 파악

claude-flow v3의 시작 시간, 검색 속도와 메모리 사용량을 측정해 개선 목표 달성 여부를 검증합니다. 지속적인 성능 감시와 저하 감지, 최적화 방안 검토도 지원합니다.

• v3 최적화 전후의 성능을 비교합니다
• 검색 속도와 메모리 사용량을 평가합니다
• 지속적으로 성능 저하를 감지합니다

Measure code performance and run benchmarks to investigate slow operations, regressions, or memory pressure. Establish a baseline, compare results under matching conditions, report variability, and rerun correctness tests after optimization.

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• Investigate slow operations
• Compare performance before and after a change
• Measure performance when memory pressure occurs

Check a codebase for known dependency vulnerabilities, hard-coded secrets, and risky code patterns using Ruflo security tools. Choose a scan depth, inspect matching lines, and report verified concerns with a clear account of what was checked.

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• Checking pull requests for security regressions
• Inspecting authentication and input-handling code for risky patterns
• Running security checks before production deployment

Track documented code fixes across releases with a signed manifest, a list of fixes and their identifying text. Verify that markers remain in source files, inspect file changes, and use recorded history to identify commits associated with regressions.

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• Check that documented fixes remain before a release
• Trace a regression through release history
• Verify signed fix records in CI

Measure and optimize claude-flow v3 startup, search, attention processing, and memory use. Compare benchmarks against performance targets, track changes over time, and identify regressions to guide further optimization.

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• Compare performance before and after v3 optimization
• Evaluate vector search speed and memory use
• Track performance regressions over time

Investigate SGLang serving failures by collecting server state, preserving failing requests, and replaying them on a clean target. Summarize evidence and likely causes, then choose the next debugging tool for crashes, stalls, or performance regressions.

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• Investigate failed health checks and growing queues
• Reproduce request-specific timeouts or crashes
• Investigate output changes after deployment

Fix defects in Composio SDK through focused reproduction, root-cause analysis, regression tests that check for recurrence, and targeted verification. Use it for reported bugs, failing tests, CI regressions, runtime errors, or incorrect SDK behavior.

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• Reproducing and fixing reported SDK bugs
• Investigating failing tests
• Fixing regressions in automated CI checks

Re-review a pull request after new commits arrive. Check every previous finding, inspect the new changes for regressions, and review the full current change. Run relevant verification and publish a test report and review verdict within Factory.

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• Checking whether previous review findings were addressed
• Finding regressions introduced by follow-up commits
• Re-running tests against the current PR head

Trace failing cmux Swift package tests to the commits that introduced them by running older revisions in CI, the automated testing environment. It helps distinguish outdated expectations, code regressions, and intermittent failures, then guides focused fixes and verification.

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• Investigating a package suite failing on main
• Finding the PR that first broke a test
• Distinguishing outdated tests from code regressions

Design evaluation systems that measure agent results across accuracy, completeness, citations, and tool efficiency. Build repeatable tests, compare changes against a baseline, and define quality checks that catch regressions before deployment and monitor production performance.

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• Compare agent configurations against a baseline
• Catch quality regressions before deployment
• Measure the effects of context strategies

Triage incorrect MNN outputs and regressions by matching symptoms to focused debugging guides. Use backend comparisons, minimal reproductions, and controlled experiments to investigate memory issues, quantization, concurrency, numeric limits, caches, and inconsistent results across runs.

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• Investigating garbled or degraded MNN output
• Comparing results across execution backends
• Tracking regressions after optimization changes

Review a branch, pull request, or uncommitted changes for interface problems involving accessibility, layout, text, typography, and color. The report distinguishes newly introduced issues, regressions, and existing problems, including effects on screens that use changed components.

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• Review interface changes in a pull request
• Check whether shared component changes affect other screens
• Find accessibility regressions before merging

Compares code relationships before and after a branch, pull request, or release change using Trailmark. Flags structural security regressions, such as removed authorization checks or newly reachable sensitive operations, and provides evidence for reviewers.

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• Checking structural security changes before merging a PR
• Reviewing call paths after a security fix
• Assessing attack surface changes in a release

Validate security patches by comparing vulnerable and patched code against exploit tests, related attack variants, and normal behavior. Produce reproducible logs showing remaining flaws, regressions, newly introduced security failures, and gaps that still need testing.

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• Validate an AI-generated security patch before review
• Check related attack variants for incomplete fixes
• Check whether a fix breaks normal behavior

Improve code through repeated changes, checks, and decisions to keep or discard each result. Start with a goal or measurable target, limit iteration counts, and review logs for progress, stalled improvements, or regressions.

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• Improve code against a measurable target
• Investigate and fix recurring errors
• Check whether changes introduce regressions

Diagnose difficult bugs and performance regressions by first building a repeatable check for the exact symptom. Minimize the reproduction, test ranked hypotheses, apply a fix, and verify the original scenario with regression tests where suitable.

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• Investigating persistent errors or incorrect output
• Increasing reproduction rates for intermittent bugs
• Measuring and diagnosing performance regressions

Analyze datasets in R or Python, from exploring distributions and missing values to fitting regressions. Produce tables and figures for publication, save scripts and model results, and review the analysis for common problems.

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• Explore distributions, missing values, and relationships
• Run regressions on cross-sectional or panel data
• Export publication-ready regression tables and figures

Improve R code used in empirical economics by finding slow operations, reducing memory use, and optimizing data processing and regressions. It covers large panel datasets and repeated calculations, with checks that optimized code preserves the original results.

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• Optimizing imports and summaries for large survey datasets
• Speeding up fixed-effects regressions on panel data
• Parallelizing Bootstrap and Monte Carlo calculations