{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2025:25Y2LWMXWT462HMASO63K43K7B","short_pith_number":"pith:25Y2LWMX","schema_version":"1.0","canonical_sha256":"d771a5d997b4f9ed1d8093bdb5736af87451e50ea1f7e5e4a0e9034527da32cc","source":{"kind":"arxiv","id":"2503.03893","version":2},"attestation_state":"computed","paper":{"title":"Parser Knows Best: Testing DBMS with Coverage-Guided Grammar-Rule Traversal","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.DB"],"primary_cat":"cs.CR","authors_text":"Hong Hu, Yu Liang","submitted_at":"2025-03-05T20:50:41Z","abstract_excerpt":"Database Management System (DBMS) is the key component for data-intensive applications. Recently, researchers propose many tools to comprehensively test DBMS systems for finding various bugs. However, these tools only cover a small subset of diverse syntax elements defined in DBMS-specific SQL dialects, leaving a large number of features unexplored. In this paper, we propose ParserFuzz, a novel fuzzing framework that automatically extracts grammar rules from DBMSs' built-in syntax definition files for SQL query generation. Without any input corpus, ParserFuzz can generate diverse query stateme"},"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":"2503.03893","kind":"arxiv","version":2},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CR","submitted_at":"2025-03-05T20:50:41Z","cross_cats_sorted":["cs.DB"],"title_canon_sha256":"ba7968e9fbc48103671e216d9608c847577bfa4a42d63c37c9f2104dcb9a485f","abstract_canon_sha256":"34ab3240cba39fe377ec93ef7e218e9a592616a75abcb499aef96e795db43af4"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T10:26:44.575772Z","signature_b64":"VQLsbhfmJ9K86KeUnN/zgR39uze0NnOWNOWwDdmIgT3rmeDuBcM7zHcXbI4hCpEo50LlEsEcRzbLw5Biq7I4Bg==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"d771a5d997b4f9ed1d8093bdb5736af87451e50ea1f7e5e4a0e9034527da32cc","last_reissued_at":"2026-07-05T10:26:44.575307Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T10:26:44.575307Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"Parser Knows Best: Testing DBMS with Coverage-Guided Grammar-Rule Traversal","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.DB"],"primary_cat":"cs.CR","authors_text":"Hong Hu, Yu Liang","submitted_at":"2025-03-05T20:50:41Z","abstract_excerpt":"Database Management System (DBMS) is the key component for data-intensive applications. Recently, researchers propose many tools to comprehensively test DBMS systems for finding various bugs. However, these tools only cover a small subset of diverse syntax elements defined in DBMS-specific SQL dialects, leaving a large number of features unexplored. In this paper, we propose ParserFuzz, a novel fuzzing framework that automatically extracts grammar rules from DBMSs' built-in syntax definition files for SQL query generation. Without any input corpus, ParserFuzz can generate diverse query stateme"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2503.03893","kind":"arxiv","version":2},"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/2503.03893/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":"2503.03893","created_at":"2026-07-05T10:26:44.575374+00:00"},{"alias_kind":"arxiv_version","alias_value":"2503.03893v2","created_at":"2026-07-05T10:26:44.575374+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2503.03893","created_at":"2026-07-05T10:26:44.575374+00:00"},{"alias_kind":"pith_short_12","alias_value":"25Y2LWMXWT46","created_at":"2026-07-05T10:26:44.575374+00:00"},{"alias_kind":"pith_short_16","alias_value":"25Y2LWMXWT462HMA","created_at":"2026-07-05T10:26:44.575374+00:00"},{"alias_kind":"pith_short_8","alias_value":"25Y2LWMX","created_at":"2026-07-05T10:26:44.575374+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/25Y2LWMXWT462HMASO63K43K7B","json":"https://pith.science/pith/25Y2LWMXWT462HMASO63K43K7B.json","graph_json":"https://pith.science/api/pith-number/25Y2LWMXWT462HMASO63K43K7B/graph.json","events_json":"https://pith.science/api/pith-number/25Y2LWMXWT462HMASO63K43K7B/events.json","paper":"https://pith.science/paper/25Y2LWMX"},"agent_actions":{"view_html":"https://pith.science/pith/25Y2LWMXWT462HMASO63K43K7B","download_json":"https://pith.science/pith/25Y2LWMXWT462HMASO63K43K7B.json","view_paper":"https://pith.science/paper/25Y2LWMX","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=2503.03893&json=true","fetch_graph":"https://pith.science/api/pith-number/25Y2LWMXWT462HMASO63K43K7B/graph.json","fetch_events":"https://pith.science/api/pith-number/25Y2LWMXWT462HMASO63K43K7B/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/25Y2LWMXWT462HMASO63K43K7B/action/timestamp_anchor","attest_storage":"https://pith.science/pith/25Y2LWMXWT462HMASO63K43K7B/action/storage_attestation","attest_author":"https://pith.science/pith/25Y2LWMXWT462HMASO63K43K7B/action/author_attestation","sign_citation":"https://pith.science/pith/25Y2LWMXWT462HMASO63K43K7B/action/citation_signature","submit_replication":"https://pith.science/pith/25Y2LWMXWT462HMASO63K43K7B/action/replication_record"}},"created_at":"2026-07-05T10:26:44.575374+00:00","updated_at":"2026-07-05T10:26:44.575374+00:00"}