{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2026:JBF5DZMPWIABKN6TZ3GICTLUJW","short_pith_number":"pith:JBF5DZMP","schema_version":"1.0","canonical_sha256":"484bd1e58fb2001537d3cecc814d744da82c5d52d85937af02cd37b9df425ebc","source":{"kind":"arxiv","id":"2607.21911","version":1},"attestation_state":"computed","paper":{"title":"Leveraging Resolved Incident History for LLM-Assisted Software Bug Diagnosis","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":["cs.DL"],"primary_cat":"cs.SE","authors_text":"Boyuan Guan, Hailu Xu, Jamie Rogers","submitted_at":"2026-07-24T02:33:14Z","abstract_excerpt":"Effective software bug diagnosis requires two ingredients: the right knowledge source (operational failure history, not just system documentation) and the right retrieval structure (structured records, not unstructured chunks). Current retrieval-augmented generation (RAG) approaches fall short on one or both dimensions. We propose Operational Memory RAG (OM-RAG), which indexes resolved issues as structured symptom-root cause-resolution triples and retrieves the most similar historical precedent via single-hop embedding. OM-RAG powers a purpose-built large language model (LLM) administrator tha"},"verification_status":{"content_addressed":true,"pith_receipt":true,"author_attested":false,"weak_author_claims":0,"strong_author_claims":0,"externally_anchored":false,"storage_verified":false,"citation_signatures":0,"replication_records":0,"graph_snapshot":true,"references_resolved":false,"formal_links_present":false},"canonical_record":{"source":{"id":"2607.21911","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.SE","submitted_at":"2026-07-24T02:33:14Z","cross_cats_sorted":["cs.DL"],"title_canon_sha256":"7772fa1674b3daa92972d04a7eb0721c8ee09e7c8fc306965eb67625b6713c45","abstract_canon_sha256":"e0e1c6a2d2944173389d1e2e990a2af743b92f058629865339b40bc1e31d08a6"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-27T00:20:27.527210Z","signature_b64":"7TQGfk+nJawZBi76JjDZ9/G2lKyffoxDlB/4evidEv3k9jtIBmCJNxT92aA1udy9Btsd+5YVCnYs5LBEosvsBQ==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"484bd1e58fb2001537d3cecc814d744da82c5d52d85937af02cd37b9df425ebc","last_reissued_at":"2026-07-27T00:20:27.526426Z","signature_status":"signed_v1","first_computed_at":"2026-07-27T00:20:27.526426Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"Leveraging Resolved Incident History for LLM-Assisted Software Bug Diagnosis","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":["cs.DL"],"primary_cat":"cs.SE","authors_text":"Boyuan Guan, Hailu Xu, Jamie Rogers","submitted_at":"2026-07-24T02:33:14Z","abstract_excerpt":"Effective software bug diagnosis requires two ingredients: the right knowledge source (operational failure history, not just system documentation) and the right retrieval structure (structured records, not unstructured chunks). Current retrieval-augmented generation (RAG) approaches fall short on one or both dimensions. We propose Operational Memory RAG (OM-RAG), which indexes resolved issues as structured symptom-root cause-resolution triples and retrieves the most similar historical precedent via single-hop embedding. OM-RAG powers a purpose-built large language model (LLM) administrator tha"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2607.21911","kind":"arxiv","version":1},"verdict":{"id":null,"model_set":{},"created_at":null,"strongest_claim":"","one_line_summary":"","pipeline_version":null,"weakest_assumption":"","pith_extraction_headline":""},"integrity":{"clean":true,"summary":{"advisory":0,"critical":0,"by_detector":{},"informational":0},"endpoint":"/pith/2607.21911/integrity.json","findings":[],"available":true,"detectors_run":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938"},"references":{"count":0,"sample":[],"resolved_work":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57","internal_anchors":0},"formal_canon":{"evidence_count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"author_claims":{"count":0,"strong_count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"builder_version":"pith-number-builder-2026-05-17-v1"},"aliases":[{"alias_kind":"arxiv","alias_value":"2607.21911","created_at":"2026-07-27T00:20:27.526834+00:00"},{"alias_kind":"arxiv_version","alias_value":"2607.21911v1","created_at":"2026-07-27T00:20:27.526834+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2607.21911","created_at":"2026-07-27T00:20:27.526834+00:00"},{"alias_kind":"pith_short_12","alias_value":"JBF5DZMPWIAB","created_at":"2026-07-27T00:20:27.526834+00:00"},{"alias_kind":"pith_short_16","alias_value":"JBF5DZMPWIABKN6T","created_at":"2026-07-27T00:20:27.526834+00:00"},{"alias_kind":"pith_short_8","alias_value":"JBF5DZMP","created_at":"2026-07-27T00:20:27.526834+00:00"}],"events":[],"event_summary":{},"paper_claims":[],"inbound_citations":{"count":0,"internal_anchor_count":0,"sample":[]},"formal_canon":{"evidence_count":0,"sample":[],"anchors":[]},"links":{"html":"https://pith.science/pith/JBF5DZMPWIABKN6TZ3GICTLUJW","json":"https://pith.science/pith/JBF5DZMPWIABKN6TZ3GICTLUJW.json","graph_json":"https://pith.science/api/pith-number/JBF5DZMPWIABKN6TZ3GICTLUJW/graph.json","events_json":"https://pith.science/api/pith-number/JBF5DZMPWIABKN6TZ3GICTLUJW/events.json","paper":"https://pith.science/paper/JBF5DZMP"},"agent_actions":{"view_html":"https://pith.science/pith/JBF5DZMPWIABKN6TZ3GICTLUJW","download_json":"https://pith.science/pith/JBF5DZMPWIABKN6TZ3GICTLUJW.json","view_paper":"https://pith.science/paper/JBF5DZMP","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=2607.21911&json=true","fetch_graph":"https://pith.science/api/pith-number/JBF5DZMPWIABKN6TZ3GICTLUJW/graph.json","fetch_events":"https://pith.science/api/pith-number/JBF5DZMPWIABKN6TZ3GICTLUJW/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/JBF5DZMPWIABKN6TZ3GICTLUJW/action/timestamp_anchor","attest_storage":"https://pith.science/pith/JBF5DZMPWIABKN6TZ3GICTLUJW/action/storage_attestation","attest_author":"https://pith.science/pith/JBF5DZMPWIABKN6TZ3GICTLUJW/action/author_attestation","sign_citation":"https://pith.science/pith/JBF5DZMPWIABKN6TZ3GICTLUJW/action/citation_signature","submit_replication":"https://pith.science/pith/JBF5DZMPWIABKN6TZ3GICTLUJW/action/replication_record"}},"created_at":"2026-07-27T00:20:27.526834+00:00","updated_at":"2026-07-27T00:20:27.526834+00:00"}