{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2019:4RXC6SPDWQ6L5DFR6BKACNDWQE","short_pith_number":"pith:4RXC6SPD","schema_version":"1.0","canonical_sha256":"e46e2f49e3b43cbe8cb1f054013476813a7cfde7ac99256eb2c2de6171358bda","source":{"kind":"arxiv","id":"1901.05138","version":1},"attestation_state":"computed","paper":{"title":"Predicting Variable Types in Dynamically Typed Programming Languages","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.AI"],"primary_cat":"cs.PL","authors_text":"Abhinav Jangda, Gaurav Anand","submitted_at":"2019-01-16T05:42:22Z","abstract_excerpt":"Dynamic Programming Languages are quite popular because they increase the programmer's productivity. However, the absence of types in the source code makes the program written in these languages difficult to understand and virtual machines that execute these programs cannot produced optimized code. To overcome this challenge, we develop a technique to predict types of all identifiers including variables, and function return types.\n  We propose the first implementation of $2^{nd}$ order Inside Outside Recursive Neural Networks with two variants (i) Child-Sum Tree-LSTMs and (ii) N-ary RNNs that "},"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":"1901.05138","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.PL","submitted_at":"2019-01-16T05:42:22Z","cross_cats_sorted":["cs.AI"],"title_canon_sha256":"3790978ad20a0dd62623fcd23b54a175b567971f663e9e6f852002d80740adf4","abstract_canon_sha256":"f3b3e69f5dab29f8bbac557a2ae49e2f58af29af2d91f8317e50f784be46ed83"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-17T23:56:11.774572Z","signature_b64":"N1nIF85iAPeL1OKdSbnD47HFhI27pjADtsXhJtjtWbM/BiO/unBqbYOM3xlFgXdW/fGvzGL/IwOmvqW+jawVDQ==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"e46e2f49e3b43cbe8cb1f054013476813a7cfde7ac99256eb2c2de6171358bda","last_reissued_at":"2026-05-17T23:56:11.773908Z","signature_status":"signed_v1","first_computed_at":"2026-05-17T23:56:11.773908Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"Predicting Variable Types in Dynamically Typed Programming Languages","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.AI"],"primary_cat":"cs.PL","authors_text":"Abhinav Jangda, Gaurav Anand","submitted_at":"2019-01-16T05:42:22Z","abstract_excerpt":"Dynamic Programming Languages are quite popular because they increase the programmer's productivity. However, the absence of types in the source code makes the program written in these languages difficult to understand and virtual machines that execute these programs cannot produced optimized code. To overcome this challenge, we develop a technique to predict types of all identifiers including variables, and function return types.\n  We propose the first implementation of $2^{nd}$ order Inside Outside Recursive Neural Networks with two variants (i) Child-Sum Tree-LSTMs and (ii) N-ary RNNs that "},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1901.05138","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":"1901.05138","created_at":"2026-05-17T23:56:11.774002+00:00"},{"alias_kind":"arxiv_version","alias_value":"1901.05138v1","created_at":"2026-05-17T23:56:11.774002+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1901.05138","created_at":"2026-05-17T23:56:11.774002+00:00"},{"alias_kind":"pith_short_12","alias_value":"4RXC6SPDWQ6L","created_at":"2026-05-18T12:33:10.108867+00:00"},{"alias_kind":"pith_short_16","alias_value":"4RXC6SPDWQ6L5DFR","created_at":"2026-05-18T12:33:10.108867+00:00"},{"alias_kind":"pith_short_8","alias_value":"4RXC6SPD","created_at":"2026-05-18T12:33:10.108867+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/4RXC6SPDWQ6L5DFR6BKACNDWQE","json":"https://pith.science/pith/4RXC6SPDWQ6L5DFR6BKACNDWQE.json","graph_json":"https://pith.science/api/pith-number/4RXC6SPDWQ6L5DFR6BKACNDWQE/graph.json","events_json":"https://pith.science/api/pith-number/4RXC6SPDWQ6L5DFR6BKACNDWQE/events.json","paper":"https://pith.science/paper/4RXC6SPD"},"agent_actions":{"view_html":"https://pith.science/pith/4RXC6SPDWQ6L5DFR6BKACNDWQE","download_json":"https://pith.science/pith/4RXC6SPDWQ6L5DFR6BKACNDWQE.json","view_paper":"https://pith.science/paper/4RXC6SPD","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=1901.05138&json=true","fetch_graph":"https://pith.science/api/pith-number/4RXC6SPDWQ6L5DFR6BKACNDWQE/graph.json","fetch_events":"https://pith.science/api/pith-number/4RXC6SPDWQ6L5DFR6BKACNDWQE/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/4RXC6SPDWQ6L5DFR6BKACNDWQE/action/timestamp_anchor","attest_storage":"https://pith.science/pith/4RXC6SPDWQ6L5DFR6BKACNDWQE/action/storage_attestation","attest_author":"https://pith.science/pith/4RXC6SPDWQ6L5DFR6BKACNDWQE/action/author_attestation","sign_citation":"https://pith.science/pith/4RXC6SPDWQ6L5DFR6BKACNDWQE/action/citation_signature","submit_replication":"https://pith.science/pith/4RXC6SPDWQ6L5DFR6BKACNDWQE/action/replication_record"}},"created_at":"2026-05-17T23:56:11.774002+00:00","updated_at":"2026-05-17T23:56:11.774002+00:00"}