pith:YF5ULMXE
Debug Like a Human: Scaling LLM-based Fault Localization to Processor Design via Block-Level Instruction-Oriented Slicing
BluesFL triples top-1 bug localization in large processor designs using block-level instruction slicing.
arxiv:2605.17290 v1 · 2026-05-17 · cs.SE
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\pithnumber{YF5ULMXEZC4G3OSM2Q7T2AYWYM}
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Record completeness
Claims
BluesFL correctly localizes 24 bugs at Top-1 on a real-world RISC-V processor core comprising 19K lines of SystemVerilog code, achieving 242.9% improvement over the existing state-of-the-art (7 bugs).
The dataflow-based blockization and Block-Level Instruction-Oriented Slicing (Blues) algorithm are assumed to provide the critical local context that enables LLMs to mimic human debugging reasoning effectively; this premise is invoked in the description of the approach but its validity rests on the specific implementation details and prompt engineering not visible in the abstract.
BluesFL uses block-level instruction-oriented slicing with LLMs to localize 24 bugs at Top-1 in a 19K-line RISC-V processor, a 242.9% gain over prior SOTA of 7 bugs.
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Receipt and verification
| First computed | 2026-05-20T00:03:50.216297Z |
|---|---|
| Builder | pith-number-builder-2026-05-17-v1 |
| Signature | Pith Ed25519
(pith-v1-2026-05) · public key |
| Schema | pith-number/v1.0 |
Canonical hash
c17b45b2e4c8b86dba4cd43f3d0316c333a85838110cf8a044a2d6a4b300a9d8
Aliases
· · · · ·Agent API
Verify this Pith Number yourself
curl -sH 'Accept: application/ld+json' https://pith.science/pith/YF5ULMXEZC4G3OSM2Q7T2AYWYM \
| jq -c '.canonical_record' \
| python3 -c "import sys,json,hashlib; b=json.dumps(json.loads(sys.stdin.read()), sort_keys=True, separators=(',',':'), ensure_ascii=False).encode(); print(hashlib.sha256(b).hexdigest())"
# expect: c17b45b2e4c8b86dba4cd43f3d0316c333a85838110cf8a044a2d6a4b300a9d8
Canonical record JSON
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