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.
- 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
