{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2018:C4DICN33IHB7KVQ2ZX42GOWAPY","short_pith_number":"pith:C4DICN33","canonical_record":{"source":{"id":"1807.08906","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.SE","submitted_at":"2018-07-23T09:24:18Z","cross_cats_sorted":[],"title_canon_sha256":"7fa666ee95d9d37320275b399879a44f69c252cbcadb5d87f28913422b46836d","abstract_canon_sha256":"464596b2f74242d0b7b274f998db49aba64a28bb9a7875d828902ede3f7d5ba5"},"schema_version":"1.0"},"canonical_sha256":"170681377b41c3f5561acdf9a33ac07e0e29010c40b103f3e6c9261358b2096f","source":{"kind":"arxiv","id":"1807.08906","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1807.08906","created_at":"2026-05-18T00:09:57Z"},{"alias_kind":"arxiv_version","alias_value":"1807.08906v1","created_at":"2026-05-18T00:09:57Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1807.08906","created_at":"2026-05-18T00:09:57Z"},{"alias_kind":"pith_short_12","alias_value":"C4DICN33IHB7","created_at":"2026-05-18T12:32:16Z"},{"alias_kind":"pith_short_16","alias_value":"C4DICN33IHB7KVQ2","created_at":"2026-05-18T12:32:16Z"},{"alias_kind":"pith_short_8","alias_value":"C4DICN33","created_at":"2026-05-18T12:32:16Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2018:C4DICN33IHB7KVQ2ZX42GOWAPY","target":"record","payload":{"canonical_record":{"source":{"id":"1807.08906","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.SE","submitted_at":"2018-07-23T09:24:18Z","cross_cats_sorted":[],"title_canon_sha256":"7fa666ee95d9d37320275b399879a44f69c252cbcadb5d87f28913422b46836d","abstract_canon_sha256":"464596b2f74242d0b7b274f998db49aba64a28bb9a7875d828902ede3f7d5ba5"},"schema_version":"1.0"},"canonical_sha256":"170681377b41c3f5561acdf9a33ac07e0e29010c40b103f3e6c9261358b2096f","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-18T00:09:57.478591Z","signature_b64":"ngDQ6iWkWOUUpDCoe/elZcIhMkY/SmcnGiUjK3f9AbwnUwUB+dEtU/hbtIa9BLgGW+KRfpoXIXgpzqplJfO2BA==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"170681377b41c3f5561acdf9a33ac07e0e29010c40b103f3e6c9261358b2096f","last_reissued_at":"2026-05-18T00:09:57.478087Z","signature_status":"signed_v1","first_computed_at":"2026-05-18T00:09:57.478087Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"1807.08906","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":"2026-05-18T00:09:57Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"3hYIEh+5ngVbKkuU6QVtyA/HP3UqgplrUbdnt2vg27F5xxktt54tdhZAqb0dSihXee47tHQgs2hRqG++0Wv6BQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-07-16T21:52:02.026540Z"},"content_sha256":"2747cf54a096e994c28f14d732981342f7b2ab1c27709700df76ddd812470af8","schema_version":"1.0","event_id":"sha256:2747cf54a096e994c28f14d732981342f7b2ab1c27709700df76ddd812470af8"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2018:C4DICN33IHB7KVQ2ZX42GOWAPY","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Reduction of Redundant Rules in Association Rule Mining-Based Bug Assignment","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.SE","authors_text":"Abhishek Tandon, Madhu Kumari, Meera Sharma, V B Singh","submitted_at":"2018-07-23T09:24:18Z","abstract_excerpt":"Bug triaging is a process to decide what to do with newly coming bug reports. In this paper, we have mined association rules for the prediction of bug assignee of a newly reported bug using different bug attributes, namely, severity, priority, component and operating system. To deal with the problem of large data sets, we have taken subsets of data set by dividing the large data set using K-means clustering algorithm. We have used an Apriori algorithm in MATLAB to generate association rules. We have extracted the association rules for top 5 assignees in each cluster.The proposed method has bee"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1807.08906","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":"2026-05-18T00:09:57Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"ORVopqaNZjrYJyqZN6G4CMyutWMnnr7t7aJVEKNeMNCMWtJldzItC/80IjqE/kEoGi0PYaEKRbEI/Ft8Uh5PDA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-07-16T21:52:02.026901Z"},"content_sha256":"c19dbacbbdda092ead22cec5155ce4dee1e1cc6b7a2286da87d67668ebdbeb48","schema_version":"1.0","event_id":"sha256:c19dbacbbdda092ead22cec5155ce4dee1e1cc6b7a2286da87d67668ebdbeb48"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/C4DICN33IHB7KVQ2ZX42GOWAPY/bundle.json","state_url":"https://pith.science/pith/C4DICN33IHB7KVQ2ZX42GOWAPY/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/C4DICN33IHB7KVQ2ZX42GOWAPY/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":"2026-07-16T21:52:02Z","links":{"resolver":"https://pith.science/pith/C4DICN33IHB7KVQ2ZX42GOWAPY","bundle":"https://pith.science/pith/C4DICN33IHB7KVQ2ZX42GOWAPY/bundle.json","state":"https://pith.science/pith/C4DICN33IHB7KVQ2ZX42GOWAPY/state.json","well_known_bundle":"https://pith.science/.well-known/pith/C4DICN33IHB7KVQ2ZX42GOWAPY/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2018:C4DICN33IHB7KVQ2ZX42GOWAPY","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":"464596b2f74242d0b7b274f998db49aba64a28bb9a7875d828902ede3f7d5ba5","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.SE","submitted_at":"2018-07-23T09:24:18Z","title_canon_sha256":"7fa666ee95d9d37320275b399879a44f69c252cbcadb5d87f28913422b46836d"},"schema_version":"1.0","source":{"id":"1807.08906","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1807.08906","created_at":"2026-05-18T00:09:57Z"},{"alias_kind":"arxiv_version","alias_value":"1807.08906v1","created_at":"2026-05-18T00:09:57Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1807.08906","created_at":"2026-05-18T00:09:57Z"},{"alias_kind":"pith_short_12","alias_value":"C4DICN33IHB7","created_at":"2026-05-18T12:32:16Z"},{"alias_kind":"pith_short_16","alias_value":"C4DICN33IHB7KVQ2","created_at":"2026-05-18T12:32:16Z"},{"alias_kind":"pith_short_8","alias_value":"C4DICN33","created_at":"2026-05-18T12:32:16Z"}],"graph_snapshots":[{"event_id":"sha256:c19dbacbbdda092ead22cec5155ce4dee1e1cc6b7a2286da87d67668ebdbeb48","target":"graph","created_at":"2026-05-18T00:09:57Z","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":"Bug triaging is a process to decide what to do with newly coming bug reports. In this paper, we have mined association rules for the prediction of bug assignee of a newly reported bug using different bug attributes, namely, severity, priority, component and operating system. To deal with the problem of large data sets, we have taken subsets of data set by dividing the large data set using K-means clustering algorithm. We have used an Apriori algorithm in MATLAB to generate association rules. We have extracted the association rules for top 5 assignees in each cluster.The proposed method has bee","authors_text":"Abhishek Tandon, Madhu Kumari, Meera Sharma, V B Singh","cross_cats":[],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.SE","submitted_at":"2018-07-23T09:24:18Z","title":"Reduction of Redundant Rules in Association Rule Mining-Based Bug Assignment"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1807.08906","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":"sha256:2747cf54a096e994c28f14d732981342f7b2ab1c27709700df76ddd812470af8","target":"record","created_at":"2026-05-18T00:09:57Z","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":"464596b2f74242d0b7b274f998db49aba64a28bb9a7875d828902ede3f7d5ba5","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.SE","submitted_at":"2018-07-23T09:24:18Z","title_canon_sha256":"7fa666ee95d9d37320275b399879a44f69c252cbcadb5d87f28913422b46836d"},"schema_version":"1.0","source":{"id":"1807.08906","kind":"arxiv","version":1}},"canonical_sha256":"170681377b41c3f5561acdf9a33ac07e0e29010c40b103f3e6c9261358b2096f","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"170681377b41c3f5561acdf9a33ac07e0e29010c40b103f3e6c9261358b2096f","first_computed_at":"2026-05-18T00:09:57.478087Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-05-18T00:09:57.478087Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"ngDQ6iWkWOUUpDCoe/elZcIhMkY/SmcnGiUjK3f9AbwnUwUB+dEtU/hbtIa9BLgGW+KRfpoXIXgpzqplJfO2BA==","signature_status":"signed_v1","signed_at":"2026-05-18T00:09:57.478591Z","signed_message":"canonical_sha256_bytes"},"source_id":"1807.08906","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:2747cf54a096e994c28f14d732981342f7b2ab1c27709700df76ddd812470af8","sha256:c19dbacbbdda092ead22cec5155ce4dee1e1cc6b7a2286da87d67668ebdbeb48"],"state_sha256":"7154108c7f4dca81e94a39ad97afc218f8b1b0e8dd59d64c4212f7c5fc89948e"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"8MqYCYJNadGr11GsLnnaEIIrKHmX9/PVhu80DHk3JdCs3XQE4zqAcMKDBKi49lQMTqT6j97pj5c76jYTbbgWBA==","signed_message":"bundle_sha256_bytes","signed_at":"2026-07-16T21:52:02.029181Z","bundle_sha256":"89b127892a28b79bf4040726c79337dddc1766e8d5cd64e8c9fdf91e4e7d7424"}}