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.
Adds --min-methods CLI flag (default 5). Groups that are too diverse or
too small are skipped with skip_reason in meta. Prevents noisy/meaningless
grammars from diverse packages.
Add _kore_trial() module-level worker for pickling. infer() accepts
n_workers param — >1 runs all (k x N) trials concurrently instead
of serial. Default 1 preserves existing behavior.
Thread n_workers through _run_kore() and infer_ensemble() to support
--kore flag with parallel kORE inference.
Replace serial file-read + tree-sitter parse loop with _preprocess_files()
using ProcessPoolExecutor. Module-level _preprocess_file() for pickling.
Covers all three callers: analyze_clusters, analyze_by_package, infer.
- 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
- CALL_PREFIXES: add bare "function" as last fallback — Kotlin uses
@function for both calls and definitions (no function.call capture)
- _find_arglist_node: remove template_string from arglist detection
- IMPORT_PATTERNS: require_relative before require (Ruby fix)
- pipeline-overview.txt: remove .gitignore, add min_coverage=0.8 + core/outlier
- DEFAULT_COVERAGE=0.8, frequency_filter at fixed 0.2
- frequency_filter(min_coverage=0.2) strips rare symbols before clustering/inference
- DEFAULT_COVERAGE=0.8 passed to infer_ensemble for sequence-level core/outlier detection
- Both filters active: symbol-level (0.2) then BEX sequence-level (0.8)
- Fix seq_of_file tracking broken by filter creating new list objects
- _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
- Ensemble inference (infer_ensemble) runs both CRX and iDRegEx, picks best by MDL
- CRX: CRX algorithm for wide coverage (accepts all sequences, large vocabulary)
- iDRegEx: iDRegEx for minimal core grammar (tightest common pattern)
- MDL scoring: fixed model_cost to count alphabet symbol occurrences, fixed dispatch order in _count_words_fast
- Fixed _match_tokens: rewritten as _match_possible with proper backtracking
- Fixed _parse_parts disjunction: children use _parse_flat_symbol to avoid dot-splitting
- MCP server: infer_best_grammar and infer_grammar tools
- Added prefer parameter (crx/idregex) to skip ensemble
- 28 passing tests
- SHOWCASE.md with Geerlingguy Galaxy demonstration
- blog_post.md with full technical deep-dive
