{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2018:USB2JYEU6KI2VZ4CXYYILZGM4J","short_pith_number":"pith:USB2JYEU","schema_version":"1.0","canonical_sha256":"a483a4e094f291aae782be3085e4cce275283d946a5006a07370ff951a44300e","source":{"kind":"arxiv","id":"1812.11470","version":1},"attestation_state":"computed","paper":{"title":"A Systematic Literature Review of Automated Techniques for Functional GUI Testing of Mobile Applications","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.SE","authors_text":"Lipo Wang, Yauhen Leanidavich Arnatovich","submitted_at":"2018-12-30T04:50:20Z","abstract_excerpt":"Context. Multiple automated techniques have been proposed and developed for mobile application GUI testing aiming to improve effectiveness, efficiency, and practicality. The effectiveness, efficiency, and practicality are 3 fundamental characteristics which testing techniques are built upon, and need to be continuously improved to deliver useful solutions for researchers and practitioners, and community as a whole.\n  Objective. In this systematic review, we attempt to provide a broad picture of existing mobile testing tools by collating and analysing their conceptual, and also performance char"},"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":"1812.11470","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.SE","submitted_at":"2018-12-30T04:50:20Z","cross_cats_sorted":[],"title_canon_sha256":"0eb21978239edcd6f270a549b0d70528f770cc3ba35162451df54df9d41b0956","abstract_canon_sha256":"6dd70ca14de03ac804c04b6a970f049e625cb63216b18823fe615caad1383b8a"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-17T23:57:11.862526Z","signature_b64":"eKTvRlVuA/tJZ1tzQ524NPjekML/8DP9M5yt/1G4jbd1bJs2NgNWZNEZIbxJT3gXrWVcM7LfchTrp8jQRnzHDQ==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"a483a4e094f291aae782be3085e4cce275283d946a5006a07370ff951a44300e","last_reissued_at":"2026-05-17T23:57:11.862077Z","signature_status":"signed_v1","first_computed_at":"2026-05-17T23:57:11.862077Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"A Systematic Literature Review of Automated Techniques for Functional GUI Testing of Mobile Applications","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.SE","authors_text":"Lipo Wang, Yauhen Leanidavich Arnatovich","submitted_at":"2018-12-30T04:50:20Z","abstract_excerpt":"Context. Multiple automated techniques have been proposed and developed for mobile application GUI testing aiming to improve effectiveness, efficiency, and practicality. The effectiveness, efficiency, and practicality are 3 fundamental characteristics which testing techniques are built upon, and need to be continuously improved to deliver useful solutions for researchers and practitioners, and community as a whole.\n  Objective. In this systematic review, we attempt to provide a broad picture of existing mobile testing tools by collating and analysing their conceptual, and also performance char"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1812.11470","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":"1812.11470","created_at":"2026-05-17T23:57:11.862149+00:00"},{"alias_kind":"arxiv_version","alias_value":"1812.11470v1","created_at":"2026-05-17T23:57:11.862149+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1812.11470","created_at":"2026-05-17T23:57:11.862149+00:00"},{"alias_kind":"pith_short_12","alias_value":"USB2JYEU6KI2","created_at":"2026-05-18T12:32:56.356000+00:00"},{"alias_kind":"pith_short_16","alias_value":"USB2JYEU6KI2VZ4C","created_at":"2026-05-18T12:32:56.356000+00:00"},{"alias_kind":"pith_short_8","alias_value":"USB2JYEU","created_at":"2026-05-18T12:32:56.356000+00:00"}],"events":[],"event_summary":{},"paper_claims":[],"inbound_citations":{"count":1,"internal_anchor_count":1,"sample":[{"citing_arxiv_id":"2411.18279","citing_title":"Large Language Model-Brained GUI Agents: A Survey","ref_index":29,"is_internal_anchor":true}]},"formal_canon":{"evidence_count":0,"sample":[],"anchors":[]},"links":{"html":"https://pith.science/pith/USB2JYEU6KI2VZ4CXYYILZGM4J","json":"https://pith.science/pith/USB2JYEU6KI2VZ4CXYYILZGM4J.json","graph_json":"https://pith.science/api/pith-number/USB2JYEU6KI2VZ4CXYYILZGM4J/graph.json","events_json":"https://pith.science/api/pith-number/USB2JYEU6KI2VZ4CXYYILZGM4J/events.json","paper":"https://pith.science/paper/USB2JYEU"},"agent_actions":{"view_html":"https://pith.science/pith/USB2JYEU6KI2VZ4CXYYILZGM4J","download_json":"https://pith.science/pith/USB2JYEU6KI2VZ4CXYYILZGM4J.json","view_paper":"https://pith.science/paper/USB2JYEU","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=1812.11470&json=true","fetch_graph":"https://pith.science/api/pith-number/USB2JYEU6KI2VZ4CXYYILZGM4J/graph.json","fetch_events":"https://pith.science/api/pith-number/USB2JYEU6KI2VZ4CXYYILZGM4J/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/USB2JYEU6KI2VZ4CXYYILZGM4J/action/timestamp_anchor","attest_storage":"https://pith.science/pith/USB2JYEU6KI2VZ4CXYYILZGM4J/action/storage_attestation","attest_author":"https://pith.science/pith/USB2JYEU6KI2VZ4CXYYILZGM4J/action/author_attestation","sign_citation":"https://pith.science/pith/USB2JYEU6KI2VZ4CXYYILZGM4J/action/citation_signature","submit_replication":"https://pith.science/pith/USB2JYEU6KI2VZ4CXYYILZGM4J/action/replication_record"}},"created_at":"2026-05-17T23:57:11.862149+00:00","updated_at":"2026-05-17T23:57:11.862149+00:00"}