Standard CRX over-approximates when Hasse diagram is non-linear (24% of
RAGSAK packages). Cluster-then-infer groups sequences by (first, last,
length), infers per-cluster, picks largest cluster's grammar.
Results on RAGSAK:
Avg max disjunction: 2.8 → 1.7 (39% tighter)
Packages improved: 6/10
Tradeoff: cluster granularity (too coarse = over-approximation,
too fine = no generalization). Current: (first, last, length_bucket).
Exports crx_refined() and crx_with_confidence() from bex package.
20 new tests. All 199 tests pass.
- Remove kORE from top-level imports, _ALGORITHMS, and infer_ensemble body
- Add include_kore=False parameter, runs kORE only when opted in
- Add --kore CLI flag threaded through all pipeline layers
- Remove koreinference from --prefer choices
- Keep kore.py module in repo for reference/future use
- Update tests: remove test_prefer_koreinference, update algorithm assertions
- _extract_call_tokens filters to call-like captures only
- cluster_methods groups sequences by shared 3-gram call patterns
- analyze_clusters runs per-cluster CRX/iDRegEx/kORE inference
- Lists 17 convention clusters for RAGSAK test code
- iDRegEx and kOREInference now produce ordered grammars per cluster
- (other) cluster captures diverse conventions as CRX vocabulary
- min-cluster-size (default 3) and ngram-size (default 3) CLI flags
- _find_method_bodies uses tree-sitter's universal body field (9/10 grammars)
- Kotlin fallback: scan children for body-like types
- preprocess_by_method groups highlight captures by enclosing method body
- Returns per-method sequences for k-ORE ordering analysis
- analyze.py infer() now uses preprocess_by_method
- Document findings in ANALYSIS.md
- 97 tests pass
