{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2019:MCEIYLXSCR4Z6NGOKPIVCF67JS","short_pith_number":"pith:MCEIYLXS","schema_version":"1.0","canonical_sha256":"60888c2ef214799f34ce53d15117df4ca4f0640ee21aeb63b9f6a93d376ed241","source":{"kind":"arxiv","id":"1907.05045","version":1},"attestation_state":"computed","paper":{"title":"Provenance for Large-scale Datalog","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.LO"],"primary_cat":"cs.PL","authors_text":"Bernhard Scholz, David Zhao, Pavle Subotic","submitted_at":"2019-07-11T08:33:13Z","abstract_excerpt":"Logic programming languages such as Datalog have become popular as Domain Specific Languages (DSLs) for solving large-scale, real-world problems, in particular, static program analysis and network analysis. The logic specifications which model analysis problems, process millions of tuples of data and contain hundreds of highly recursive rules. As a result, they are notoriously difficult to debug. While the database community has proposed several data-provenance techniques that address the Declarative Debugging Challenge for Databases, in the cases of analysis problems, these state-of-the-art t"},"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":"1907.05045","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.PL","submitted_at":"2019-07-11T08:33:13Z","cross_cats_sorted":["cs.LO"],"title_canon_sha256":"147f202fed98722cfd68bcd7979e2abb3838e836fec08ce2240dc9dd67385571","abstract_canon_sha256":"9ef023e11f58dcc28f74e997ce838670f223f5f2ee1cb69dcb0f550667ec67b7"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-17T23:40:29.603757Z","signature_b64":"gmv5b8aF9V8mUQdv5jCo02S+RZsMKE3fyRNjQUCtOPlowQgetum7r+UrJYVunv8NuBAvTrdwaG7zapJom3eKCA==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"60888c2ef214799f34ce53d15117df4ca4f0640ee21aeb63b9f6a93d376ed241","last_reissued_at":"2026-05-17T23:40:29.603120Z","signature_status":"signed_v1","first_computed_at":"2026-05-17T23:40:29.603120Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"Provenance for Large-scale Datalog","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.LO"],"primary_cat":"cs.PL","authors_text":"Bernhard Scholz, David Zhao, Pavle Subotic","submitted_at":"2019-07-11T08:33:13Z","abstract_excerpt":"Logic programming languages such as Datalog have become popular as Domain Specific Languages (DSLs) for solving large-scale, real-world problems, in particular, static program analysis and network analysis. The logic specifications which model analysis problems, process millions of tuples of data and contain hundreds of highly recursive rules. As a result, they are notoriously difficult to debug. While the database community has proposed several data-provenance techniques that address the Declarative Debugging Challenge for Databases, in the cases of analysis problems, these state-of-the-art t"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1907.05045","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":""},"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":"1907.05045","created_at":"2026-05-17T23:40:29.603193+00:00"},{"alias_kind":"arxiv_version","alias_value":"1907.05045v1","created_at":"2026-05-17T23:40:29.603193+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1907.05045","created_at":"2026-05-17T23:40:29.603193+00:00"},{"alias_kind":"pith_short_12","alias_value":"MCEIYLXSCR4Z","created_at":"2026-05-18T12:33:21.387695+00:00"},{"alias_kind":"pith_short_16","alias_value":"MCEIYLXSCR4Z6NGO","created_at":"2026-05-18T12:33:21.387695+00:00"},{"alias_kind":"pith_short_8","alias_value":"MCEIYLXS","created_at":"2026-05-18T12:33:21.387695+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/MCEIYLXSCR4Z6NGOKPIVCF67JS","json":"https://pith.science/pith/MCEIYLXSCR4Z6NGOKPIVCF67JS.json","graph_json":"https://pith.science/api/pith-number/MCEIYLXSCR4Z6NGOKPIVCF67JS/graph.json","events_json":"https://pith.science/api/pith-number/MCEIYLXSCR4Z6NGOKPIVCF67JS/events.json","paper":"https://pith.science/paper/MCEIYLXS"},"agent_actions":{"view_html":"https://pith.science/pith/MCEIYLXSCR4Z6NGOKPIVCF67JS","download_json":"https://pith.science/pith/MCEIYLXSCR4Z6NGOKPIVCF67JS.json","view_paper":"https://pith.science/paper/MCEIYLXS","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=1907.05045&json=true","fetch_graph":"https://pith.science/api/pith-number/MCEIYLXSCR4Z6NGOKPIVCF67JS/graph.json","fetch_events":"https://pith.science/api/pith-number/MCEIYLXSCR4Z6NGOKPIVCF67JS/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/MCEIYLXSCR4Z6NGOKPIVCF67JS/action/timestamp_anchor","attest_storage":"https://pith.science/pith/MCEIYLXSCR4Z6NGOKPIVCF67JS/action/storage_attestation","attest_author":"https://pith.science/pith/MCEIYLXSCR4Z6NGOKPIVCF67JS/action/author_attestation","sign_citation":"https://pith.science/pith/MCEIYLXSCR4Z6NGOKPIVCF67JS/action/citation_signature","submit_replication":"https://pith.science/pith/MCEIYLXSCR4Z6NGOKPIVCF67JS/action/replication_record"}},"created_at":"2026-05-17T23:40:29.603193+00:00","updated_at":"2026-05-17T23:40:29.603193+00:00"}