{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2022:VRL4IPEKZRUWVLONKY5BYAYMKN","short_pith_number":"pith:VRL4IPEK","schema_version":"1.0","canonical_sha256":"ac57c43c8acc696aadcd563a1c030c5376e6461205c9911ed341ade68561d121","source":{"kind":"arxiv","id":"2201.08810","version":2},"attestation_state":"computed","paper":{"title":"GAP-Gen: Guided Automatic Python Code Generation","license":"http://creativecommons.org/licenses/by-sa/4.0/","headline":"","cross_cats":["cs.CL","cs.LG","cs.SE"],"primary_cat":"cs.PL","authors_text":"Ian G. Harris, Junchen Zhao, Junlin Wang, Yurun Song","submitted_at":"2022-01-19T06:32:47Z","abstract_excerpt":"Automatic code generation from natural language descriptions can be highly beneficial during the process of software development. In this work, we propose GAP-Gen, a Guided Automatic Python Code Generation method based on Python syntactic constraints and semantic constraints. We first introduce Python syntactic constraints in the form of Syntax-Flow, which is a simplified version of Abstract Syntax Tree (AST) reducing the size and high complexity of Abstract Syntax Tree but maintaining crucial syntactic information of Python code. In addition to Syntax-Flow, we introduce Variable-Flow which ab"},"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":"2201.08810","kind":"arxiv","version":2},"metadata":{"license":"http://creativecommons.org/licenses/by-sa/4.0/","primary_cat":"cs.PL","submitted_at":"2022-01-19T06:32:47Z","cross_cats_sorted":["cs.CL","cs.LG","cs.SE"],"title_canon_sha256":"5384c37ff1d08cddaee10b2477da9b71f39445ccd5e756b5ad593949e7fd93b9","abstract_canon_sha256":"3b467e3cb54b909981941173d4c40f34d132404c4a9417513041fe83ac937b2f"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T06:08:50.946863Z","signature_b64":"7ZVCfhB6TrlPWmrLDCvPy8MpyErBoNpy6olsUd9Ip8LduR5wXOCmsdyWphc1ifa7NzgrutwRC6aFQLK1hVa+BQ==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"ac57c43c8acc696aadcd563a1c030c5376e6461205c9911ed341ade68561d121","last_reissued_at":"2026-07-05T06:08:50.946466Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T06:08:50.946466Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"GAP-Gen: Guided Automatic Python Code Generation","license":"http://creativecommons.org/licenses/by-sa/4.0/","headline":"","cross_cats":["cs.CL","cs.LG","cs.SE"],"primary_cat":"cs.PL","authors_text":"Ian G. Harris, Junchen Zhao, Junlin Wang, Yurun Song","submitted_at":"2022-01-19T06:32:47Z","abstract_excerpt":"Automatic code generation from natural language descriptions can be highly beneficial during the process of software development. In this work, we propose GAP-Gen, a Guided Automatic Python Code Generation method based on Python syntactic constraints and semantic constraints. We first introduce Python syntactic constraints in the form of Syntax-Flow, which is a simplified version of Abstract Syntax Tree (AST) reducing the size and high complexity of Abstract Syntax Tree but maintaining crucial syntactic information of Python code. In addition to Syntax-Flow, we introduce Variable-Flow which ab"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2201.08810","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/2201.08810/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":"2201.08810","created_at":"2026-07-05T06:08:50.946530+00:00"},{"alias_kind":"arxiv_version","alias_value":"2201.08810v2","created_at":"2026-07-05T06:08:50.946530+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2201.08810","created_at":"2026-07-05T06:08:50.946530+00:00"},{"alias_kind":"pith_short_12","alias_value":"VRL4IPEKZRUW","created_at":"2026-07-05T06:08:50.946530+00:00"},{"alias_kind":"pith_short_16","alias_value":"VRL4IPEKZRUWVLON","created_at":"2026-07-05T06:08:50.946530+00:00"},{"alias_kind":"pith_short_8","alias_value":"VRL4IPEK","created_at":"2026-07-05T06:08:50.946530+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/VRL4IPEKZRUWVLONKY5BYAYMKN","json":"https://pith.science/pith/VRL4IPEKZRUWVLONKY5BYAYMKN.json","graph_json":"https://pith.science/api/pith-number/VRL4IPEKZRUWVLONKY5BYAYMKN/graph.json","events_json":"https://pith.science/api/pith-number/VRL4IPEKZRUWVLONKY5BYAYMKN/events.json","paper":"https://pith.science/paper/VRL4IPEK"},"agent_actions":{"view_html":"https://pith.science/pith/VRL4IPEKZRUWVLONKY5BYAYMKN","download_json":"https://pith.science/pith/VRL4IPEKZRUWVLONKY5BYAYMKN.json","view_paper":"https://pith.science/paper/VRL4IPEK","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=2201.08810&json=true","fetch_graph":"https://pith.science/api/pith-number/VRL4IPEKZRUWVLONKY5BYAYMKN/graph.json","fetch_events":"https://pith.science/api/pith-number/VRL4IPEKZRUWVLONKY5BYAYMKN/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/VRL4IPEKZRUWVLONKY5BYAYMKN/action/timestamp_anchor","attest_storage":"https://pith.science/pith/VRL4IPEKZRUWVLONKY5BYAYMKN/action/storage_attestation","attest_author":"https://pith.science/pith/VRL4IPEKZRUWVLONKY5BYAYMKN/action/author_attestation","sign_citation":"https://pith.science/pith/VRL4IPEKZRUWVLONKY5BYAYMKN/action/citation_signature","submit_replication":"https://pith.science/pith/VRL4IPEKZRUWVLONKY5BYAYMKN/action/replication_record"}},"created_at":"2026-07-05T06:08:50.946530+00:00","updated_at":"2026-07-05T06:08:50.946530+00:00"}