{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2017:FRMDWJBIGUMRLVADSNREETV32P","short_pith_number":"pith:FRMDWJBI","schema_version":"1.0","canonical_sha256":"2c583b2428351915d4039362424ebbd3cb9a8c518fc846a7c797edf0f4feeff0","source":{"kind":"arxiv","id":"1706.02259","version":1},"attestation_state":"computed","paper":{"title":"A Pragmatic Approach for Measuring Maintainability of DPRA Models","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.SE","authors_text":"Fabrice Boissier, Hassane Chraibi, Irina Rychkova, Valentin Rychkov","submitted_at":"2017-06-07T17:01:47Z","abstract_excerpt":"Dynamic Probabilistic Risk Assessment (DPRA) is a powerful concept that is used to evaluate design and safety of complex industrial systems. A DPRA model uses a conceptual system representation as a formal basis for simulation and analysis. In this paper we consider an adaptive maintenance of DPRA models that consist in modifying and extending a simplified model to a real-size DPRA model. We propose an approach for quantitative maintainability assessment of DPRA models created with an industrial modeling tool called PyCATSHOO. We review and adopt some metrics from conceptual modeling, software"},"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":"1706.02259","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.SE","submitted_at":"2017-06-07T17:01:47Z","cross_cats_sorted":[],"title_canon_sha256":"456d8adf75dc24a1564dca8d2470fada702b4c811c3713837548d7f5a929a31d","abstract_canon_sha256":"d1158936563e5449e0f7203d94cb4f54e091d48f57cbac72beb8bd0ec2cc306e"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-18T00:42:49.436690Z","signature_b64":"1QXV/8cKNHUxyhKuXccKDsME+Cs+eop7gOwedRxkQqT8zdbBxKD/28tJXrEUlq25zLFRn02Teomdwd+xRpz2Dg==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"2c583b2428351915d4039362424ebbd3cb9a8c518fc846a7c797edf0f4feeff0","last_reissued_at":"2026-05-18T00:42:49.436100Z","signature_status":"signed_v1","first_computed_at":"2026-05-18T00:42:49.436100Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"A Pragmatic Approach for Measuring Maintainability of DPRA Models","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.SE","authors_text":"Fabrice Boissier, Hassane Chraibi, Irina Rychkova, Valentin Rychkov","submitted_at":"2017-06-07T17:01:47Z","abstract_excerpt":"Dynamic Probabilistic Risk Assessment (DPRA) is a powerful concept that is used to evaluate design and safety of complex industrial systems. A DPRA model uses a conceptual system representation as a formal basis for simulation and analysis. In this paper we consider an adaptive maintenance of DPRA models that consist in modifying and extending a simplified model to a real-size DPRA model. We propose an approach for quantitative maintainability assessment of DPRA models created with an industrial modeling tool called PyCATSHOO. We review and adopt some metrics from conceptual modeling, software"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1706.02259","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":"1706.02259","created_at":"2026-05-18T00:42:49.436198+00:00"},{"alias_kind":"arxiv_version","alias_value":"1706.02259v1","created_at":"2026-05-18T00:42:49.436198+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1706.02259","created_at":"2026-05-18T00:42:49.436198+00:00"},{"alias_kind":"pith_short_12","alias_value":"FRMDWJBIGUMR","created_at":"2026-05-18T12:31:15.632608+00:00"},{"alias_kind":"pith_short_16","alias_value":"FRMDWJBIGUMRLVAD","created_at":"2026-05-18T12:31:15.632608+00:00"},{"alias_kind":"pith_short_8","alias_value":"FRMDWJBI","created_at":"2026-05-18T12:31:15.632608+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/FRMDWJBIGUMRLVADSNREETV32P","json":"https://pith.science/pith/FRMDWJBIGUMRLVADSNREETV32P.json","graph_json":"https://pith.science/api/pith-number/FRMDWJBIGUMRLVADSNREETV32P/graph.json","events_json":"https://pith.science/api/pith-number/FRMDWJBIGUMRLVADSNREETV32P/events.json","paper":"https://pith.science/paper/FRMDWJBI"},"agent_actions":{"view_html":"https://pith.science/pith/FRMDWJBIGUMRLVADSNREETV32P","download_json":"https://pith.science/pith/FRMDWJBIGUMRLVADSNREETV32P.json","view_paper":"https://pith.science/paper/FRMDWJBI","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=1706.02259&json=true","fetch_graph":"https://pith.science/api/pith-number/FRMDWJBIGUMRLVADSNREETV32P/graph.json","fetch_events":"https://pith.science/api/pith-number/FRMDWJBIGUMRLVADSNREETV32P/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/FRMDWJBIGUMRLVADSNREETV32P/action/timestamp_anchor","attest_storage":"https://pith.science/pith/FRMDWJBIGUMRLVADSNREETV32P/action/storage_attestation","attest_author":"https://pith.science/pith/FRMDWJBIGUMRLVADSNREETV32P/action/author_attestation","sign_citation":"https://pith.science/pith/FRMDWJBIGUMRLVADSNREETV32P/action/citation_signature","submit_replication":"https://pith.science/pith/FRMDWJBIGUMRLVADSNREETV32P/action/replication_record"}},"created_at":"2026-05-18T00:42:49.436198+00:00","updated_at":"2026-05-18T00:42:49.436198+00:00"}