{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2023:C4R7MFKQZTBZGHG6UN5X4J2TWM","short_pith_number":"pith:C4R7MFKQ","canonical_record":{"source":{"id":"2312.10622","kind":"arxiv","version":2},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.SE","submitted_at":"2023-12-17T06:38:11Z","cross_cats_sorted":["cs.AI"],"title_canon_sha256":"b20f37f5b4f23022256cbf53ac9ba03e84c21e37b8363a3c0e9262a819310e58","abstract_canon_sha256":"806e2204d2259d44c85f5a46359662e509c4c725a62ab104e4c15a73d2029e9d"},"schema_version":"1.0"},"canonical_sha256":"1723f61550ccc3931cdea37b7e2753b326e1b60180173383c66234c45ac22dc8","source":{"kind":"arxiv","id":"2312.10622","version":2},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2312.10622","created_at":"2026-07-05T07:44:45Z"},{"alias_kind":"arxiv_version","alias_value":"2312.10622v2","created_at":"2026-07-05T07:44:45Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2312.10622","created_at":"2026-07-05T07:44:45Z"},{"alias_kind":"pith_short_12","alias_value":"C4R7MFKQZTBZ","created_at":"2026-07-05T07:44:45Z"},{"alias_kind":"pith_short_16","alias_value":"C4R7MFKQZTBZGHG6","created_at":"2026-07-05T07:44:45Z"},{"alias_kind":"pith_short_8","alias_value":"C4R7MFKQ","created_at":"2026-07-05T07:44:45Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2023:C4R7MFKQZTBZGHG6UN5X4J2TWM","target":"record","payload":{"canonical_record":{"source":{"id":"2312.10622","kind":"arxiv","version":2},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.SE","submitted_at":"2023-12-17T06:38:11Z","cross_cats_sorted":["cs.AI"],"title_canon_sha256":"b20f37f5b4f23022256cbf53ac9ba03e84c21e37b8363a3c0e9262a819310e58","abstract_canon_sha256":"806e2204d2259d44c85f5a46359662e509c4c725a62ab104e4c15a73d2029e9d"},"schema_version":"1.0"},"canonical_sha256":"1723f61550ccc3931cdea37b7e2753b326e1b60180173383c66234c45ac22dc8","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T07:44:45.655135Z","signature_b64":"pOevhxPHHdFZGl+ycLUtPYHpHqEhGpNF8mfVdV8YGrMjrCpkC1vxDW2ySviUpXWzd3dW53BYxC3sjMpfbsSdBg==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"1723f61550ccc3931cdea37b7e2753b326e1b60180173383c66234c45ac22dc8","last_reissued_at":"2026-07-05T07:44:45.654692Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T07:44:45.654692Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2312.10622","source_version":2,"attestation_state":"computed"},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-07-05T07:44:45Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"LNgskPoC0STkDInoPbGWU1spqJjQyDzaCXw0aFCOgtQ31GjKYuiQoqavmM6WO6aWEOwcKJgfqrMifkW4DMXMCg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-19T16:49:57.433393Z"},"content_sha256":"d08f89416278cb60fa2ed799eb54a536bd8ae00e8aa4ff7e8e88c4c8ed4ba7d2","schema_version":"1.0","event_id":"sha256:d08f89416278cb60fa2ed799eb54a536bd8ae00e8aa4ff7e8e88c4c8ed4ba7d2"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2023:C4R7MFKQZTBZGHG6UN5X4J2TWM","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Unit Test Generation using Generative AI : A Comparative Performance Analysis of Autogeneration Tools","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.AI"],"primary_cat":"cs.SE","authors_text":"Dhruv Kumar, Pankaj Jalote, Shreya Bhatia, Tarushi Gandhi","submitted_at":"2023-12-17T06:38:11Z","abstract_excerpt":"Generating unit tests is a crucial task in software development, demanding substantial time and effort from programmers. The advent of Large Language Models (LLMs) introduces a novel avenue for unit test script generation. This research aims to experimentally investigate the effectiveness of LLMs, specifically exemplified by ChatGPT, for generating unit test scripts for Python programs, and how the generated test cases compare with those generated by an existing unit test generator (Pynguin). For experiments, we consider three types of code units: 1) Procedural scripts, 2) Function-based modul"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2312.10622","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/2312.10622/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"},"verdict_id":null},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-07-05T07:44:45Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"S4xOTFF6lvHd9IukpKDmHrccxEQhfhOp/Q7yPLmDezeCHuNrJ/u40CSFirN8DdZ/ooUKVYIaQYvN5yOLd6VqBg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-19T16:49:57.433772Z"},"content_sha256":"fd351d3f578500b702d124371289c874726ade604ee80b34cd20896fc3d70bf7","schema_version":"1.0","event_id":"sha256:fd351d3f578500b702d124371289c874726ade604ee80b34cd20896fc3d70bf7"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/C4R7MFKQZTBZGHG6UN5X4J2TWM/bundle.json","state_url":"https://pith.science/pith/C4R7MFKQZTBZGHG6UN5X4J2TWM/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/C4R7MFKQZTBZGHG6UN5X4J2TWM/bundle.json","status":"primary"}],"public_keys":[{"key_id":"pith-v1-2026-05","algorithm":"ed25519","format":"raw","public_key_b64":"stVStoiQhXFxp4s2pdzPNoqVNBMojDU/fJ2db5S3CbM=","public_key_hex":"b2d552b68890857171a78b36a5dccf368a953413288c353f7c9d9d6f94b709b3","fingerprint_sha256_b32_first128bits":"RVFV5Z2OI2J3ZUO7ERDEBCYNKS","fingerprint_sha256_hex":"8d4b5ee74e4693bcd1df2446408b0d54","rotates_at":null,"url":"https://pith.science/pith-signing-key.json","notes":"Pith uses this Ed25519 key to sign canonical record SHA-256 digests. Verify with: ed25519_verify(public_key, message=canonical_sha256_bytes, signature=base64decode(signature_b64))."}],"merge_version":"pith-open-graph-merge-v1","built_at":"2026-08-19T16:49:57Z","links":{"resolver":"https://pith.science/pith/C4R7MFKQZTBZGHG6UN5X4J2TWM","bundle":"https://pith.science/pith/C4R7MFKQZTBZGHG6UN5X4J2TWM/bundle.json","state":"https://pith.science/pith/C4R7MFKQZTBZGHG6UN5X4J2TWM/state.json","well_known_bundle":"https://pith.science/.well-known/pith/C4R7MFKQZTBZGHG6UN5X4J2TWM/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2023:C4R7MFKQZTBZGHG6UN5X4J2TWM","merge_version":"pith-open-graph-merge-v1","event_count":2,"valid_event_count":2,"invalid_event_count":0,"equivocation_count":0,"current":{"canonical_record":{"metadata":{"abstract_canon_sha256":"806e2204d2259d44c85f5a46359662e509c4c725a62ab104e4c15a73d2029e9d","cross_cats_sorted":["cs.AI"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.SE","submitted_at":"2023-12-17T06:38:11Z","title_canon_sha256":"b20f37f5b4f23022256cbf53ac9ba03e84c21e37b8363a3c0e9262a819310e58"},"schema_version":"1.0","source":{"id":"2312.10622","kind":"arxiv","version":2}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2312.10622","created_at":"2026-07-05T07:44:45Z"},{"alias_kind":"arxiv_version","alias_value":"2312.10622v2","created_at":"2026-07-05T07:44:45Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2312.10622","created_at":"2026-07-05T07:44:45Z"},{"alias_kind":"pith_short_12","alias_value":"C4R7MFKQZTBZ","created_at":"2026-07-05T07:44:45Z"},{"alias_kind":"pith_short_16","alias_value":"C4R7MFKQZTBZGHG6","created_at":"2026-07-05T07:44:45Z"},{"alias_kind":"pith_short_8","alias_value":"C4R7MFKQ","created_at":"2026-07-05T07:44:45Z"}],"graph_snapshots":[{"event_id":"sha256:fd351d3f578500b702d124371289c874726ade604ee80b34cd20896fc3d70bf7","target":"graph","created_at":"2026-07-05T07:44:45Z","signer":{"key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signer_id":"pith.science","signer_type":"pith_registry"},"payload":{"graph_snapshot":{"author_claims":{"count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57","strong_count":0},"builder_version":"pith-number-builder-2026-05-17-v1","claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"formal_canon":{"evidence_count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"integrity":{"available":true,"clean":true,"detectors_run":[],"endpoint":"/pith/2312.10622/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Generating unit tests is a crucial task in software development, demanding substantial time and effort from programmers. The advent of Large Language Models (LLMs) introduces a novel avenue for unit test script generation. This research aims to experimentally investigate the effectiveness of LLMs, specifically exemplified by ChatGPT, for generating unit test scripts for Python programs, and how the generated test cases compare with those generated by an existing unit test generator (Pynguin). For experiments, we consider three types of code units: 1) Procedural scripts, 2) Function-based modul","authors_text":"Dhruv Kumar, Pankaj Jalote, Shreya Bhatia, Tarushi Gandhi","cross_cats":["cs.AI"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.SE","submitted_at":"2023-12-17T06:38:11Z","title":"Unit Test Generation using Generative AI : A Comparative Performance Analysis of Autogeneration Tools"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2312.10622","kind":"arxiv","version":2},"verdict":{"created_at":null,"id":null,"model_set":{},"one_line_summary":"","pipeline_version":null,"pith_extraction_headline":"","strongest_claim":"","weakest_assumption":""}},"verdict_id":null}}],"author_attestations":[],"timestamp_anchors":[],"storage_attestations":[],"citation_signatures":[],"replication_records":[],"corrections":[],"mirror_hints":[],"record_created":{"event_id":"sha256:d08f89416278cb60fa2ed799eb54a536bd8ae00e8aa4ff7e8e88c4c8ed4ba7d2","target":"record","created_at":"2026-07-05T07:44:45Z","signer":{"key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signer_id":"pith.science","signer_type":"pith_registry"},"payload":{"attestation_state":"computed","canonical_record":{"metadata":{"abstract_canon_sha256":"806e2204d2259d44c85f5a46359662e509c4c725a62ab104e4c15a73d2029e9d","cross_cats_sorted":["cs.AI"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.SE","submitted_at":"2023-12-17T06:38:11Z","title_canon_sha256":"b20f37f5b4f23022256cbf53ac9ba03e84c21e37b8363a3c0e9262a819310e58"},"schema_version":"1.0","source":{"id":"2312.10622","kind":"arxiv","version":2}},"canonical_sha256":"1723f61550ccc3931cdea37b7e2753b326e1b60180173383c66234c45ac22dc8","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"1723f61550ccc3931cdea37b7e2753b326e1b60180173383c66234c45ac22dc8","first_computed_at":"2026-07-05T07:44:45.654692Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T07:44:45.654692Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"pOevhxPHHdFZGl+ycLUtPYHpHqEhGpNF8mfVdV8YGrMjrCpkC1vxDW2ySviUpXWzd3dW53BYxC3sjMpfbsSdBg==","signature_status":"signed_v1","signed_at":"2026-07-05T07:44:45.655135Z","signed_message":"canonical_sha256_bytes"},"source_id":"2312.10622","source_kind":"arxiv","source_version":2}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:d08f89416278cb60fa2ed799eb54a536bd8ae00e8aa4ff7e8e88c4c8ed4ba7d2","sha256:fd351d3f578500b702d124371289c874726ade604ee80b34cd20896fc3d70bf7"],"state_sha256":"2d344e7df53bfb44d417dae8add74c8f050689d63661885d83a8c8ba039d4cec"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"QTObUf58JQx4fgJd8waxHEUF8V/wDaI+ObVDyqTzsnLoTUxlssu5NWMrG1ySGe1t+YWAQ/PUc0I4q7DH2vRdBA==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-19T16:49:57.436132Z","bundle_sha256":"465013e2e5b8804d271dc21c3af9dcce1039c279bca97c6e0abe91cc5cad777d"}}