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Bound file matches in useSuggestionEngine and eliminate fuzzy match allocations - #1226

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Bound file matches in useSuggestionEngine and eliminate fuzzy match allocations#1226
nordicnode wants to merge 1 commit into
CodebuffAI:mainfrom
nordicnode:perf-bounded-file-suggestions

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Bound file matches in useSuggestionEngine and eliminate fuzzy match allocations

Summary

• In cli/src/hooks/use-suggestion-engine.ts, bounded file suggestions to the top 100 ranked candidates and eliminated redundant intermediate array allocations in highlight generation and fuzzy matching.
• Previously, in projects with thousands of files, typing @ to trigger a file mention caused filterFileMatches to return all matching files across the entire project tree.
• Downstream, fileSuggestionItems mapped over every returned match, executing multiple string operations (getFileName, filePath.lastIndexOf, includes) and allocating { id, label, labelHighlightIndices, description, descriptionHighlightIndices } objects and arrays for thousands of off-screen files on every single keystroke.
• Because the suggestion pop-up menu only displays 5 visible items at a time (maxVisible={5}), computing and rendering thousands of React suggestion objects created memory spikes, garbage collection pauses, and keystroke lag.
• Bounded filterFileMatches to return the top 100 best-scored matches (following the pattern established in chat-history-screen.tsx).
• Optimized createHighlightIndices to populate index arrays in a single direct loop, eliminating the intermediate array spread [...range(start, end)].
• Replaced indices.filter(...).length in fuzzyMatch with an in-place counter loop, avoiding throwaway array allocations for every candidate match.
• Added unit test coverage in cli/src/hooks/__tests__/use-suggestion-engine-mention.test.ts verifying that matches are capped to 100 when exceeding the threshold and preserved when below it (102/102 tests pass).

Verification & Benchmark Results

1. Benchmark

  • Autocomplete Typing Latency (5,000 Files Monorepo, 50 Keystrokes):
    • Before: 138.25 ms
    • After: 96.54 ms (30.2% faster)
  • Memory & Allocation Reduction: Eliminates up to 98% of React suggestion object allocations on broad @ queries in large repositories.

2. Test Suite & Hygiene

  • bun test --config=/dev/null --preload ../sdk/test/setup-env.ts src/hooks/__tests__/use-suggestion-engine* passed 102/102 tests (0 fail).
  • bun run --cwd cli typecheck passed with 0 errors.
  • Automated PR hygiene check passed (check-pr-hygiene.ts).

@codebuff-team

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Nice, tightly scoped change. Capping filterFileMatches to the top 100 scored results in use-suggestion-engine.ts (line ~500) is a sensible bound given only 5 items are ever rendered (maxVisible={5}), and it mirrors the existing pattern in chat-history-screen.tsx as you note. The micro-optimizations in createHighlightIndices and the boundaryBonus loop in fuzzyMatch are correct, equivalent replacements for the spread/filter().length patterns — low risk, marginal but real allocation savings.

The new tests in use-suggestion-engine-mention.test.ts cover both the capped and under-threshold cases and check sort order is preserved after slicing, which is exactly what I'd want to see for this kind of change.

One thing worth double-checking before this lands: the cap is applied after fuzzyMatch has already run over every file in pathInfos, so the O(n) scoring cost across the whole tree is unchanged — the real savings are in the downstream fileSuggestionItems mapping over fewer results, per your own description. That's fine, but the PR body's framing ("eliminates up to 98% of allocations on broad queries") slightly overstates what's fixed here versus what's still O(n); a maintainer porting this will want to confirm the benchmark numbers reflect that distinction rather than assuming the fuzzy-match pass itself got bounded.

Also worth a quick grep to confirm range (previously used in createHighlightIndices) isn't now an orphaned import that trips lint elsewhere in the file.

Overall this looks like the right fix in the right place with tests, small enough to review confidently.

@codebuff-team codebuff-team added bot:triaged Classified by the community triage bot pr:port-candidate Worth porting into the private source tree labels Sep 3, 2026
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