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codebase-comprehension-algorithms

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Mapping an unfamiliar codebase into feature/business domains — answering "what is this about", "which files implement feature X", "where is the architectural spine", or reviewing a refactor that crosses module boundaries. 47 algorithms across 9 categories — graph construction (omnipresent filter, multilayer, SCC), lexical preprocessing (Samurai, TF-IDF), community detection (Leiden, Infomap, SBM, MCL, Walktrap, spectral, HDBSCAN), architecture recovery (Bunch+MQ, ACDC, Limbo, Reflexion, DSM), topic modelling (LDA, LSI, NMF, HDP), evolutionary coupling (Gall, ROSE), information-theoretic (NCD, MI, MDL, naturalness), centrality (PageRank, HITS, betweenness, TextRank), validation (MoJoFM, ARI/NMI, resolution limit, consensus, co-change prediction, ablation). Trigger without explicit "clustering" mention — codebase grokking, dependency mapping, domain extraction, architecture-recovery validation all apply.

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# Community Codebase Comprehension And Domain Mapping Algorithms Best Practices

A practitioner-oriented reference of the **algorithms that work for mapping a codebase into understandable feature/business domains**. Most of these techniques live in the Software Architecture Recovery and Mining Software Repositories literatures and are invisible to working engineers — yet they're the right tools for the job a coding agent is asked to do every day: *"what does this codebase do, and where?"*

The 47 rules are organized by **execution-lifecycle impact**: a wrong decision early in the pipeline (which graph to build, which identifiers to keep) propagates through everything downstream. The three CRITICAL categories (`graph-`, `clust-`, `valid-`) are the ones a wrong call cannot be recovered from later. Read them first.

**Scope**: proven algorithms with peer-reviewed citations or canonical books — Newman *Networks*, Leskovec-Rajaraman-Ullman *Mining of Massive Datasets*, Ganter-Wille *Formal Concept Analysis*, plus 40+ ICSE / FSE / TSE / PNAS / JMLR papers. No tutorial sites, no Stack Overflow, no marketing posts. Deliberately deferred to a future version: GNN/CodeBERT/code2vec (not "proven over decades" yet) and refactoring-recipe stuff (covered by sibling skills like `react-refactor` and `typescript-refactor`).

## When to Apply

Use these rules when:

- Onboarding an agent into an unfamiliar codebase: "explain what this codebase does, by domain"
- Producing an architecture map: "what are the main subsystems and how do they connect?"
- Locating a feature: "which files implement payments / authentication / search?"