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Coverage is collected through `Microsoft.Testing.Extensions.CodeCoverage`. Cobertura is the XML output format used for line and branch reporting; the test project does not reference Coverlet.
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BenchmarkDotNet performance runs are separate from TUnit correctness tests. Commands, workload profiles, profiler options, and full result tables live in [Performance Benchmarks](docs/Features/PerformanceBenchmarks.md). PR validationand the dedicated benchmark workflow both run the complete BenchmarkDotNet suite and upload the `benchmarkdotnet-results` artifact.
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BenchmarkDotNet performance runs are separate from TUnit correctness tests. Commands, workload profiles, profiler options, and full result tables live in [Performance Benchmarks](docs/Features/PerformanceBenchmarks.md). The build/test/pack validation job stays separate; PR validation, release validation, and the dedicated benchmark workflow run the complete BenchmarkDotNet suite as parallel suite jobs and upload suite-specific `benchmarkdotnet-results-*` artifacts.
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Current local headline numbers from the May 3, 2026 BenchmarkDotNet 0.15.8 run on Apple M2 Pro with .NET 10.0.5:
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Current local headline numbers from the May 4, 2026 BenchmarkDotNet 0.15.8 run on Apple M2 Pro with .NET 10.0.5:
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| Area | Current local result |
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| --- | --- |
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| Full suite | 118 BenchmarkDotNet cases using the `Default` job |
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| Graph build | `LargeCorpus` builds in 47.851 ms with 57.73 MB allocated |
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| Low-latency search | `ShortDocuments` exact ranked graph search is 1.092 ms / 2.17 MB; BM25 is 1.309 ms / 2.14 MB |
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| Typo-tolerant search | BM25 fuzzy stays opt-in; `ShortDocuments` typo fuzzy search is 1.815 ms / 2.86 MB |
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| RDF query paths | `ShortDocuments` exact schema SPARQL is 49.212 ms / 60.32 MB; local federated schema search is 41.243 ms / 62.3 MB |
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| Tiktoken search | `LongDocuments` exact token-distance search is 159.8 us / 107.27 KB; typo correction is 225.7 us / 110.68 KB |
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| Persistence | `LargeCorpus` Turtle file load is 34.787 ms / 28.10 MB; JSON-LD file load is 98.267 ms / 75.32 MB |
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| Lifecycle | Build/search/save/load/export is 45.44 ms / 53.51 MB |
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| Fuzzy edit distance | Long insertion is 368.69x faster than naive Levenshtein; long no-match is 176.19x faster, both with 0 B allocated |
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| Full suite | 118 BenchmarkDotNet cases using the `Required` job; local sequential pass completed in 5 minutes 41 seconds (`real 341.12s`) |
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| Graph build | `LargeCorpus` builds in 151.12 ms with 58.75 MB allocated |
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| Low-latency search | `ShortDocuments` exact ranked graph search is 1.143 ms / 2.15 MB; BM25 is 2.503 ms / 2.14 MB |
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| Typo-tolerant search | BM25 fuzzy stays opt-in; `ShortDocuments` typo fuzzy search is 7.366 ms / 2.77 MB |
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| RDF query paths | `ShortDocuments` exact schema SPARQL is 94.422 ms / 61.25 MB; local federated schema search is 92.469 ms / 63.24 MB |
Copy file name to clipboardExpand all lines: docs/Features/HybridGraphSearch.md
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## Intended Library Boundary
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- The library owns the graph-native candidate extraction and merge policy.
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- BM25 ranking is in-memory and uses the same candidate text as semantic indexing for the selected boundary: graph-native for graph-only callers, document-aware for build-result/facade callers. Exact BM25 keeps the allocation profile close to ranked graph search by avoiding full per-document dictionaries. Optional fuzzy token matching is implemented inside this library, does not add an external package dependency, and does not copy AGPL-licensed code from reviewed prior-art projects.
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- BM25 ranking is in-memory and uses the same candidate text as semantic indexing for the selected boundary: graph-native for graph-only callers, document-aware for build-result/facade callers. Exact BM25 keeps the allocation profile close to ranked graph search by avoiding full per-document dictionaries. Optional fuzzy token matching is implemented inside this library, does not add an external package dependency, and follows public bounded edit-distance algorithms with our own implementation.
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- The host application owns the concrete embedding provider and supplies it as `Microsoft.Extensions.AI.IEmbeddingGenerator<string, Embedding<float>>`.
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- The library does not own a vector database, gateway endpoint, or hosted ranking infrastructure.
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