git-forensics

分析 Git 历史，发现"逻辑耦合"（总一起改的文件）和"热点"（高频修改的复杂模块）。基于 Adam Tornhill 的《Your Code as a Crime Scene》方法论。

1.45x

Quality

56%

Does it follow best practices?

Impact

90%

1.45x

Average score across 3 eval scenarios

Securityby

Passed

No known issues

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Evaluation results

84%

35%

Finding Hidden Dependencies in an Open Source Service

Temporal coupling analysis

Criteria

Without context

With context

Script output format

30%

Noise files excluded

100%

HIGH_COUPLING label

100%

MEDIUM_COUPLING label

100%

File type classification

20%

70%

Build root annotation

100%

History completeness check

100%

Initial activity survey

100%

Actionable recommendations

100%

Architectural decay identification

50%

40%

100%

40%

Technical Debt Prioritization for an Engineering Refactoring Sprint

Hotspot detection and debt scoring

Criteria

Without context

With context

Hotspot script output fields

100%

debt_score field present

90%

100%

debt_score = churn × max_ccn

100%

max_ccn used

100%

nloc field present

100%

Sorted by debt_score descending

100%

High churn + high complexity = top priority

86%

100%

High churn + low complexity = deprioritize

91%

100%

Analysis period defined

40%

100%

Concrete file example

100%

88%

Pre-Decomposition Architectural Risk Assessment

Full forensic report with cross-root coupling

Criteria

Without context

With context

Both analyses present

100%

Cross-subsystem section

100%

Cross-subsystem pairs flagged

100%

Build root annotation

100%

Orphan files listed

100%

One-year orphan threshold

100%

Refactoring priority section

100%

Priority matrix applied

60%

100%

Coupling threshold 0.7

37%

Actionable recommendations

100%

Rename distortion awareness

Repository: Lingjie-chen/MT5
Commit: 3069d33

Evaluated: 26 days ago
Agent: Claude Code
Model: Claude Sonnet 4.6

Table of Contents

Finding Hidden Dependencies in an Open Source Service Technical Debt Prioritization for an Engineering Refactoring Sprint Pre-Decomposition Architectural Risk Assessment

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