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Add bounded exhaustive gap-block top-K and threshold counts - #3
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Co-Authored-By: Codex <noreply@openai.com>
Co-Authored-By: Codex <noreply@openai.com>
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Exhaustive gap-block ranking currently requires a dense query-by-reference matrix, while trie top-hit search first collects the whole edit ball. Add native batched top-K heaps and cumulative threshold counts over the existing gap-block scorer, including generic linked two-view rows and a batched reference accessor. Ranking retains stable score/reference-ID ties; exact exclusion happens before selection.
Verification: 173 focused Python tests covering exhaustive matrix/prior oracles, thread equality, empty/invalid inputs, score bounds and paired exclusion; Sphinx zero warnings. A bounded synthetic probe produces identical outputs with one/four threads and stays below 40 MB process-tree RSS. Candidate version 1.0.2 is prepared; no tag or publication.