{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2023:VXOWKK4GULQAHLOJL3PHOHMT6Y","short_pith_number":"pith:VXOWKK4G","schema_version":"1.0","canonical_sha256":"addd652b86a2e003adc95ede771d93f60a9b73514fda4e13bb7db14685e3da8b","source":{"kind":"arxiv","id":"2302.04666","version":1},"attestation_state":"computed","paper":{"title":"Understand Code Style: Efficient CNN-based Compiler Optimization Recognition System","license":"http://creativecommons.org/licenses/by-nc-sa/4.0/","headline":"","cross_cats":[],"primary_cat":"cs.PL","authors_text":"Guodong Zhang, Limin Sun, Mingxuan Li, Shouguo Yang, Yuan Ma, Zhiqiang Shi","submitted_at":"2023-01-18T03:52:52Z","abstract_excerpt":"Compiler optimization level recognition can be applied to vulnerability discovery and binary analysis. Due to the exists of many different compilation optimization options, the difference in the contents of the binary file is very complicated. There are thousands of compiler optimization algorithms and multiple different processor architectures, so it is very difficult to manually analyze binary files and recognize its compiler optimization level with rules. This paper first proposes a CNN-based compiler optimization level recognition model: BinEye. The system extracts semantic and structural "},"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":"2302.04666","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by-nc-sa/4.0/","primary_cat":"cs.PL","submitted_at":"2023-01-18T03:52:52Z","cross_cats_sorted":[],"title_canon_sha256":"c69124ecd678076f28bf41153f71569ec1500a5406336fedb1be1b656f2334ce","abstract_canon_sha256":"8c88762bef55ec545484e5bf4a226025e549d27228bf5a27c7605cc31ad75e1f"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T05:40:17.088548Z","signature_b64":"odxZ/LCqCxWiSkj045Fv0dYC195hGuKOjvqg31gcruV/fQ9ygN3xbcBsID0nbAkFzzQtP6nyUfU2f2Qvis/zDA==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"addd652b86a2e003adc95ede771d93f60a9b73514fda4e13bb7db14685e3da8b","last_reissued_at":"2026-07-05T05:40:17.087926Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T05:40:17.087926Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"Understand Code Style: Efficient CNN-based Compiler Optimization Recognition System","license":"http://creativecommons.org/licenses/by-nc-sa/4.0/","headline":"","cross_cats":[],"primary_cat":"cs.PL","authors_text":"Guodong Zhang, Limin Sun, Mingxuan Li, Shouguo Yang, Yuan Ma, Zhiqiang Shi","submitted_at":"2023-01-18T03:52:52Z","abstract_excerpt":"Compiler optimization level recognition can be applied to vulnerability discovery and binary analysis. Due to the exists of many different compilation optimization options, the difference in the contents of the binary file is very complicated. There are thousands of compiler optimization algorithms and multiple different processor architectures, so it is very difficult to manually analyze binary files and recognize its compiler optimization level with rules. This paper first proposes a CNN-based compiler optimization level recognition model: BinEye. The system extracts semantic and structural "},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2302.04666","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":""},"integrity":{"clean":true,"summary":{"advisory":0,"critical":0,"by_detector":{},"informational":0},"endpoint":"/pith/2302.04666/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"},"aliases":[{"alias_kind":"arxiv","alias_value":"2302.04666","created_at":"2026-07-05T05:40:17.088005+00:00"},{"alias_kind":"arxiv_version","alias_value":"2302.04666v1","created_at":"2026-07-05T05:40:17.088005+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2302.04666","created_at":"2026-07-05T05:40:17.088005+00:00"},{"alias_kind":"pith_short_12","alias_value":"VXOWKK4GULQA","created_at":"2026-07-05T05:40:17.088005+00:00"},{"alias_kind":"pith_short_16","alias_value":"VXOWKK4GULQAHLOJ","created_at":"2026-07-05T05:40:17.088005+00:00"},{"alias_kind":"pith_short_8","alias_value":"VXOWKK4G","created_at":"2026-07-05T05:40:17.088005+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/VXOWKK4GULQAHLOJL3PHOHMT6Y","json":"https://pith.science/pith/VXOWKK4GULQAHLOJL3PHOHMT6Y.json","graph_json":"https://pith.science/api/pith-number/VXOWKK4GULQAHLOJL3PHOHMT6Y/graph.json","events_json":"https://pith.science/api/pith-number/VXOWKK4GULQAHLOJL3PHOHMT6Y/events.json","paper":"https://pith.science/paper/VXOWKK4G"},"agent_actions":{"view_html":"https://pith.science/pith/VXOWKK4GULQAHLOJL3PHOHMT6Y","download_json":"https://pith.science/pith/VXOWKK4GULQAHLOJL3PHOHMT6Y.json","view_paper":"https://pith.science/paper/VXOWKK4G","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=2302.04666&json=true","fetch_graph":"https://pith.science/api/pith-number/VXOWKK4GULQAHLOJL3PHOHMT6Y/graph.json","fetch_events":"https://pith.science/api/pith-number/VXOWKK4GULQAHLOJL3PHOHMT6Y/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/VXOWKK4GULQAHLOJL3PHOHMT6Y/action/timestamp_anchor","attest_storage":"https://pith.science/pith/VXOWKK4GULQAHLOJL3PHOHMT6Y/action/storage_attestation","attest_author":"https://pith.science/pith/VXOWKK4GULQAHLOJL3PHOHMT6Y/action/author_attestation","sign_citation":"https://pith.science/pith/VXOWKK4GULQAHLOJL3PHOHMT6Y/action/citation_signature","submit_replication":"https://pith.science/pith/VXOWKK4GULQAHLOJL3PHOHMT6Y/action/replication_record"}},"created_at":"2026-07-05T05:40:17.088005+00:00","updated_at":"2026-07-05T05:40:17.088005+00:00"}