{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2018:OVXFDJ7ILIIPKHHRDPWODOKJWO","short_pith_number":"pith:OVXFDJ7I","canonical_record":{"source":{"id":"1812.02257","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.SE","submitted_at":"2018-12-05T22:30:42Z","cross_cats_sorted":[],"title_canon_sha256":"cf29dfce34943e7122cb25d091fad59e5631bf773654cb7c24a10b3de4073c2d","abstract_canon_sha256":"2af98b0363a622408a5df4420cfaf9962e8d0cbde9080682b95955e2e8cdaf3f"},"schema_version":"1.0"},"canonical_sha256":"756e51a7e85a10f51cf11bece1b949b39691926db2564f910327d570d5945b1b","source":{"kind":"arxiv","id":"1812.02257","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1812.02257","created_at":"2026-05-17T23:58:56Z"},{"alias_kind":"arxiv_version","alias_value":"1812.02257v1","created_at":"2026-05-17T23:58:56Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1812.02257","created_at":"2026-05-17T23:58:56Z"},{"alias_kind":"pith_short_12","alias_value":"OVXFDJ7ILIIP","created_at":"2026-05-18T12:32:43Z"},{"alias_kind":"pith_short_16","alias_value":"OVXFDJ7ILIIPKHHR","created_at":"2026-05-18T12:32:43Z"},{"alias_kind":"pith_short_8","alias_value":"OVXFDJ7I","created_at":"2026-05-18T12:32:43Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2018:OVXFDJ7ILIIPKHHRDPWODOKJWO","target":"record","payload":{"canonical_record":{"source":{"id":"1812.02257","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.SE","submitted_at":"2018-12-05T22:30:42Z","cross_cats_sorted":[],"title_canon_sha256":"cf29dfce34943e7122cb25d091fad59e5631bf773654cb7c24a10b3de4073c2d","abstract_canon_sha256":"2af98b0363a622408a5df4420cfaf9962e8d0cbde9080682b95955e2e8cdaf3f"},"schema_version":"1.0"},"canonical_sha256":"756e51a7e85a10f51cf11bece1b949b39691926db2564f910327d570d5945b1b","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-17T23:58:56.748232Z","signature_b64":"9Kt8Rr9Ckldik3JznhtZe2Wej9p+YO7G3lThBwBzS5jWODd20BUQZIBGhJXUsBfTPtA/pQijcKHMyATjtoMCAQ==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"756e51a7e85a10f51cf11bece1b949b39691926db2564f910327d570d5945b1b","last_reissued_at":"2026-05-17T23:58:56.747795Z","signature_status":"signed_v1","first_computed_at":"2026-05-17T23:58:56.747795Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"1812.02257","source_version":1,"attestation_state":"computed"},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-05-17T23:58:56Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"iHI9VI2MxDWrkA3fm0a+V8Z/Lghi1ALK4HrmVtDbCearfMmRbSCgcrP49UXOahyZZPQ7TPV31l3tc0oHINX6Cg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-07-04T15:11:14.472199Z"},"content_sha256":"b610633cacf84ae19d3743dbeebe9980484ed241e47976862b81036e9076990f","schema_version":"1.0","event_id":"sha256:b610633cacf84ae19d3743dbeebe9980484ed241e47976862b81036e9076990f"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2018:OVXFDJ7ILIIPKHHRDPWODOKJWO","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"On Testing Machine Learning Programs","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.SE","authors_text":"Foutse Khomh, Houssem Ben Braiek","submitted_at":"2018-12-05T22:30:42Z","abstract_excerpt":"Nowadays, we are witnessing a wide adoption of Machine learning (ML) models in many safety-critical systems, thanks to recent breakthroughs in deep learning and reinforcement learning. Many people are now interacting with systems based on ML every day, e.g., voice recognition systems used by virtual personal assistants like Amazon Alexa or Google Home. As the field of ML continues to grow, we are likely to witness transformative advances in a wide range of areas, from finance, energy, to health and transportation. Given this growing importance of ML-based systems in our daily life, it is becom"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1812.02257","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"},"verdict_id":null},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-05-17T23:58:56Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"4tq0rBJeSzrHrk4ylzYgStMT0Yp2+BnlNlx1do1VaBdng6nYPa2Oy0Aeo/q+/+mFjkUwMfIP1rRAGBqCopeyAg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-07-04T15:11:14.472560Z"},"content_sha256":"2a43d015ca8e44b6b7b01cde32b977fc9e65399c0c58a8c71f57dec8e9cfc1ed","schema_version":"1.0","event_id":"sha256:2a43d015ca8e44b6b7b01cde32b977fc9e65399c0c58a8c71f57dec8e9cfc1ed"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/OVXFDJ7ILIIPKHHRDPWODOKJWO/bundle.json","state_url":"https://pith.science/pith/OVXFDJ7ILIIPKHHRDPWODOKJWO/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/OVXFDJ7ILIIPKHHRDPWODOKJWO/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":"2026-07-04T15:11:14Z","links":{"resolver":"https://pith.science/pith/OVXFDJ7ILIIPKHHRDPWODOKJWO","bundle":"https://pith.science/pith/OVXFDJ7ILIIPKHHRDPWODOKJWO/bundle.json","state":"https://pith.science/pith/OVXFDJ7ILIIPKHHRDPWODOKJWO/state.json","well_known_bundle":"https://pith.science/.well-known/pith/OVXFDJ7ILIIPKHHRDPWODOKJWO/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2018:OVXFDJ7ILIIPKHHRDPWODOKJWO","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":"2af98b0363a622408a5df4420cfaf9962e8d0cbde9080682b95955e2e8cdaf3f","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.SE","submitted_at":"2018-12-05T22:30:42Z","title_canon_sha256":"cf29dfce34943e7122cb25d091fad59e5631bf773654cb7c24a10b3de4073c2d"},"schema_version":"1.0","source":{"id":"1812.02257","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1812.02257","created_at":"2026-05-17T23:58:56Z"},{"alias_kind":"arxiv_version","alias_value":"1812.02257v1","created_at":"2026-05-17T23:58:56Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1812.02257","created_at":"2026-05-17T23:58:56Z"},{"alias_kind":"pith_short_12","alias_value":"OVXFDJ7ILIIP","created_at":"2026-05-18T12:32:43Z"},{"alias_kind":"pith_short_16","alias_value":"OVXFDJ7ILIIPKHHR","created_at":"2026-05-18T12:32:43Z"},{"alias_kind":"pith_short_8","alias_value":"OVXFDJ7I","created_at":"2026-05-18T12:32:43Z"}],"graph_snapshots":[{"event_id":"sha256:2a43d015ca8e44b6b7b01cde32b977fc9e65399c0c58a8c71f57dec8e9cfc1ed","target":"graph","created_at":"2026-05-17T23:58:56Z","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"},"paper":{"abstract_excerpt":"Nowadays, we are witnessing a wide adoption of Machine learning (ML) models in many safety-critical systems, thanks to recent breakthroughs in deep learning and reinforcement learning. Many people are now interacting with systems based on ML every day, e.g., voice recognition systems used by virtual personal assistants like Amazon Alexa or Google Home. As the field of ML continues to grow, we are likely to witness transformative advances in a wide range of areas, from finance, energy, to health and transportation. Given this growing importance of ML-based systems in our daily life, it is becom","authors_text":"Foutse Khomh, Houssem Ben Braiek","cross_cats":[],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.SE","submitted_at":"2018-12-05T22:30:42Z","title":"On Testing Machine Learning Programs"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1812.02257","kind":"arxiv","version":1},"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:b610633cacf84ae19d3743dbeebe9980484ed241e47976862b81036e9076990f","target":"record","created_at":"2026-05-17T23:58:56Z","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":"2af98b0363a622408a5df4420cfaf9962e8d0cbde9080682b95955e2e8cdaf3f","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.SE","submitted_at":"2018-12-05T22:30:42Z","title_canon_sha256":"cf29dfce34943e7122cb25d091fad59e5631bf773654cb7c24a10b3de4073c2d"},"schema_version":"1.0","source":{"id":"1812.02257","kind":"arxiv","version":1}},"canonical_sha256":"756e51a7e85a10f51cf11bece1b949b39691926db2564f910327d570d5945b1b","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"756e51a7e85a10f51cf11bece1b949b39691926db2564f910327d570d5945b1b","first_computed_at":"2026-05-17T23:58:56.747795Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-05-17T23:58:56.747795Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"9Kt8Rr9Ckldik3JznhtZe2Wej9p+YO7G3lThBwBzS5jWODd20BUQZIBGhJXUsBfTPtA/pQijcKHMyATjtoMCAQ==","signature_status":"signed_v1","signed_at":"2026-05-17T23:58:56.748232Z","signed_message":"canonical_sha256_bytes"},"source_id":"1812.02257","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:b610633cacf84ae19d3743dbeebe9980484ed241e47976862b81036e9076990f","sha256:2a43d015ca8e44b6b7b01cde32b977fc9e65399c0c58a8c71f57dec8e9cfc1ed"],"state_sha256":"74e599ec8d5f32fab9065ae79addb06e935726a23661df2b70258dc69603e718"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"cMJHggMUUYeYk9ZNmh2e9JgCZHAd/kQodnIHh4ixJT7AOfRROCpj+iEzDex7QV7LoxVmOkBkK1co5xSQA+MkDA==","signed_message":"bundle_sha256_bytes","signed_at":"2026-07-04T15:11:14.474440Z","bundle_sha256":"e7881f0d5b164d023ee0b88184759916eb38b149521e2b0e70565fabd74f37f7"}}