{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2025:ZH7FNUK3HESOL4FJHI5FKJY4YN","short_pith_number":"pith:ZH7FNUK3","canonical_record":{"source":{"id":"2504.19237","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.SE","submitted_at":"2025-04-27T13:42:30Z","cross_cats_sorted":[],"title_canon_sha256":"21965deb08b8eb8398dbf5132659382141b2f81b10ed7e55c27d2c0e7e2c0ba1","abstract_canon_sha256":"d7696e42ae6724b15bb863494fc3afc03785407195975f6d194e105a19069cea"},"schema_version":"1.0"},"canonical_sha256":"c9fe56d15b3924e5f0a93a3a55271cc356e06d944785b7bae4e7a7c95ef97496","source":{"kind":"arxiv","id":"2504.19237","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2504.19237","created_at":"2026-07-05T10:54:54Z"},{"alias_kind":"arxiv_version","alias_value":"2504.19237v1","created_at":"2026-07-05T10:54:54Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2504.19237","created_at":"2026-07-05T10:54:54Z"},{"alias_kind":"pith_short_12","alias_value":"ZH7FNUK3HESO","created_at":"2026-07-05T10:54:54Z"},{"alias_kind":"pith_short_16","alias_value":"ZH7FNUK3HESOL4FJ","created_at":"2026-07-05T10:54:54Z"},{"alias_kind":"pith_short_8","alias_value":"ZH7FNUK3","created_at":"2026-07-05T10:54:54Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2025:ZH7FNUK3HESOL4FJHI5FKJY4YN","target":"record","payload":{"canonical_record":{"source":{"id":"2504.19237","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.SE","submitted_at":"2025-04-27T13:42:30Z","cross_cats_sorted":[],"title_canon_sha256":"21965deb08b8eb8398dbf5132659382141b2f81b10ed7e55c27d2c0e7e2c0ba1","abstract_canon_sha256":"d7696e42ae6724b15bb863494fc3afc03785407195975f6d194e105a19069cea"},"schema_version":"1.0"},"canonical_sha256":"c9fe56d15b3924e5f0a93a3a55271cc356e06d944785b7bae4e7a7c95ef97496","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T10:54:54.233628Z","signature_b64":"wFQ0oimRzqK3VDTyloQXziGHrwAe8Kqd30t4U+ArT4l4suZEtp8oFM4wJvJY/IRrsMqErhxfiKFJ4zz3vi+kBQ==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"c9fe56d15b3924e5f0a93a3a55271cc356e06d944785b7bae4e7a7c95ef97496","last_reissued_at":"2026-07-05T10:54:54.233145Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T10:54:54.233145Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2504.19237","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":"2026-07-05T10:54:54Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"78BWKtC9pRVRQ4Un2rc1+rs4jlrNCKhCIt83kWbFfWYdfUrC5MjewBHLkl3qbp3HcWIXL+DkPczGJANQ/NBDAA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-07-25T01:37:48.562341Z"},"content_sha256":"561540b717ae195effc0193f693d4e0331b0c703a23f714ec7ffcd4a9f2403cf","schema_version":"1.0","event_id":"sha256:561540b717ae195effc0193f693d4e0331b0c703a23f714ec7ffcd4a9f2403cf"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2025:ZH7FNUK3HESOL4FJHI5FKJY4YN","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Deep Reinforcement Learning for Automated Web GUI Testing","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.SE","authors_text":"Chenxi Yang, Chenxu Liu, Guoquan Wu, Jun Wei, Wei Chen, Yifei Zhang, Zheheng Liang, Zhiyu Gu","submitted_at":"2025-04-27T13:42:30Z","abstract_excerpt":"Automated GUI testing of web applications has always been considered a challenging task considering their large state space and complex interaction logic. Deep Reinforcement Learning (DRL) is a recent extension of Reinforcement Learning (RL), which takes advantage of the powerful learning capabilities of neural networks, making it suitable for complex exploration space. In this paper, leveraging the capability of deep reinforcement learning, we propose WebRLED, an effective approach for automated GUI testing of complex web applications. WebRLED has the following characteristics: (1) a grid-bas"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2504.19237","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/2504.19237/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":"2026-07-05T10:54:54Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"Kyhb9ACmviAQt7yS624Fo18kVLz6piy9z6a6n0xVShROYPTF94MhWpOJOqqeKno9MMPbGbxLkPgfUd+ycjwzCg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-07-25T01:37:48.562717Z"},"content_sha256":"e5e118d11a39e6ccff690a3b22e9dcfed378dd3a5a5896e476c90a4d58dc616d","schema_version":"1.0","event_id":"sha256:e5e118d11a39e6ccff690a3b22e9dcfed378dd3a5a5896e476c90a4d58dc616d"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/ZH7FNUK3HESOL4FJHI5FKJY4YN/bundle.json","state_url":"https://pith.science/pith/ZH7FNUK3HESOL4FJHI5FKJY4YN/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/ZH7FNUK3HESOL4FJHI5FKJY4YN/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":"2026-07-25T01:37:48Z","links":{"resolver":"https://pith.science/pith/ZH7FNUK3HESOL4FJHI5FKJY4YN","bundle":"https://pith.science/pith/ZH7FNUK3HESOL4FJHI5FKJY4YN/bundle.json","state":"https://pith.science/pith/ZH7FNUK3HESOL4FJHI5FKJY4YN/state.json","well_known_bundle":"https://pith.science/.well-known/pith/ZH7FNUK3HESOL4FJHI5FKJY4YN/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2025:ZH7FNUK3HESOL4FJHI5FKJY4YN","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":"d7696e42ae6724b15bb863494fc3afc03785407195975f6d194e105a19069cea","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.SE","submitted_at":"2025-04-27T13:42:30Z","title_canon_sha256":"21965deb08b8eb8398dbf5132659382141b2f81b10ed7e55c27d2c0e7e2c0ba1"},"schema_version":"1.0","source":{"id":"2504.19237","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2504.19237","created_at":"2026-07-05T10:54:54Z"},{"alias_kind":"arxiv_version","alias_value":"2504.19237v1","created_at":"2026-07-05T10:54:54Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2504.19237","created_at":"2026-07-05T10:54:54Z"},{"alias_kind":"pith_short_12","alias_value":"ZH7FNUK3HESO","created_at":"2026-07-05T10:54:54Z"},{"alias_kind":"pith_short_16","alias_value":"ZH7FNUK3HESOL4FJ","created_at":"2026-07-05T10:54:54Z"},{"alias_kind":"pith_short_8","alias_value":"ZH7FNUK3","created_at":"2026-07-05T10:54:54Z"}],"graph_snapshots":[{"event_id":"sha256:e5e118d11a39e6ccff690a3b22e9dcfed378dd3a5a5896e476c90a4d58dc616d","target":"graph","created_at":"2026-07-05T10:54:54Z","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/2504.19237/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Automated GUI testing of web applications has always been considered a challenging task considering their large state space and complex interaction logic. Deep Reinforcement Learning (DRL) is a recent extension of Reinforcement Learning (RL), which takes advantage of the powerful learning capabilities of neural networks, making it suitable for complex exploration space. In this paper, leveraging the capability of deep reinforcement learning, we propose WebRLED, an effective approach for automated GUI testing of complex web applications. WebRLED has the following characteristics: (1) a grid-bas","authors_text":"Chenxi Yang, Chenxu Liu, Guoquan Wu, Jun Wei, Wei Chen, Yifei Zhang, Zheheng Liang, Zhiyu Gu","cross_cats":[],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.SE","submitted_at":"2025-04-27T13:42:30Z","title":"Deep Reinforcement Learning for Automated Web GUI Testing"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2504.19237","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":"sha256:561540b717ae195effc0193f693d4e0331b0c703a23f714ec7ffcd4a9f2403cf","target":"record","created_at":"2026-07-05T10:54:54Z","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":"d7696e42ae6724b15bb863494fc3afc03785407195975f6d194e105a19069cea","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.SE","submitted_at":"2025-04-27T13:42:30Z","title_canon_sha256":"21965deb08b8eb8398dbf5132659382141b2f81b10ed7e55c27d2c0e7e2c0ba1"},"schema_version":"1.0","source":{"id":"2504.19237","kind":"arxiv","version":1}},"canonical_sha256":"c9fe56d15b3924e5f0a93a3a55271cc356e06d944785b7bae4e7a7c95ef97496","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"c9fe56d15b3924e5f0a93a3a55271cc356e06d944785b7bae4e7a7c95ef97496","first_computed_at":"2026-07-05T10:54:54.233145Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T10:54:54.233145Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"wFQ0oimRzqK3VDTyloQXziGHrwAe8Kqd30t4U+ArT4l4suZEtp8oFM4wJvJY/IRrsMqErhxfiKFJ4zz3vi+kBQ==","signature_status":"signed_v1","signed_at":"2026-07-05T10:54:54.233628Z","signed_message":"canonical_sha256_bytes"},"source_id":"2504.19237","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:561540b717ae195effc0193f693d4e0331b0c703a23f714ec7ffcd4a9f2403cf","sha256:e5e118d11a39e6ccff690a3b22e9dcfed378dd3a5a5896e476c90a4d58dc616d"],"state_sha256":"c61c028bf5cf05baee22c9fa97d7c53e076ceefa68a5095d2d6ab38e6895af64"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"tkPDbMCWuIoHQcNmoF5omnikbqJwXZFr9EqoT8Il68R+GEw078VexRxU1nmHCVsW7OmhEc3A129xg0eFTBOYBw==","signed_message":"bundle_sha256_bytes","signed_at":"2026-07-25T01:37:48.565226Z","bundle_sha256":"d7c288db2376e36528c72e4e5a72f1805a65a4636d58a18630b106052bb63404"}}