ramsterr / rootrank
spectrum-based root cause analysis for any graph with pass/fail traces. Ranks which node is the most likely failure source using Ochiai SBFL + propagation. Use cases: microservice incidents, CI , supply-chain failure analysis. Pure Python, pip-installable.
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Read more about ramsterr/rootrank
- OverviewFiles, symbols, languages, packages, git intelligence
- ArchitectureDependency graph, layered architecture, symbol index, and third-party dependencies
- Code healthPer-file health scores, hotspots, test coverage, dead code, and refactoring targets
- AI docsProModule-by-module documentation generated from source
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[](https://repowise.dev/repo/ramsterr/rootrank)How ramsterr/rootrank works
spectrum-based root cause analysis for any graph with pass/fail traces. Ranks which node is the most likely failure source using Ochiai SBFL + propagation. Use cases: microservice incidents, CI , supply-chain failure analysis. Pure Python, pip-installable. This page is an auto-generated, always-fresh map of the ramsterr/rootrank repository, written primarily in Python. Repowise indexes the source, parses every symbol, computes a dependency graph, scores per-file code health from complexity, duplication, test coverage and churn, mines git history for hotspots and ownership, and lifts the resulting architectural decisions into a wiki you can read or query through MCP.
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