{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,7,25]],"date-time":"2026-07-25T18:53:03Z","timestamp":1785005583726,"version":"3.55.0"},"publisher-location":"New York, NY, USA","reference-count":13,"publisher":"ACM","license":[{"start":{"date-parts":[[2022,10,10]],"date-time":"2022-10-10T00:00:00Z","timestamp":1665360000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.acm.org\/publications\/policies\/copyright_policy#Background"}],"content-domain":{"domain":["dl.acm.org"],"crossmark-restriction":true},"short-container-title":[],"published-print":{"date-parts":[[2022,10,10]]},"DOI":"10.1145\/3551349.3559505","type":"proceedings-article","created":{"date-parts":[[2023,1,5]],"date-time":"2023-01-05T20:43:54Z","timestamp":1672951434000},"page":"1-5","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":50,"title":["Fastbot2: Reusable Automated Model-based GUI Testing for Android Enhanced by Reinforcement Learning"],"prefix":"10.1145","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-2843-0689","authenticated-orcid":false,"given":"Zhengwei","family":"Lv","sequence":"first","affiliation":[{"name":"ByteDance, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Chao","family":"Peng","sequence":"additional","affiliation":[{"name":"ByteDance, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-1628-9796","authenticated-orcid":false,"given":"Zhao","family":"Zhang","sequence":"additional","affiliation":[{"name":"ByteDance, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Ting","family":"Su","sequence":"additional","affiliation":[{"name":"East China Normal University, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Kai","family":"Liu","sequence":"additional","affiliation":[{"name":"Bytedance, China and East China Normal University, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Ping","family":"Yang","sequence":"additional","affiliation":[{"name":"ByteDance, China"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"320","published-online":{"date-parts":[[2023,1,5]]},"reference":[{"key":"e_1_3_2_1_1_1","unstructured":"AppBrain. 2022.. Retrieved June 3 2022 from https:\/\/www.appbrain.com\/stats\/number-of-android-apps"},{"key":"e_1_3_2_1_2_1","volume-title":"Automated test input generation for android: Are we there yet?","author":"Choudhary Shauvik\u00a0Roy","unstructured":"Shauvik\u00a0Roy Choudhary, Alessandra Gorla, and Alessandro Orso. 2015. Automated test input generation for android: Are we there yet?. In ASE. IEEE, 429\u2013440."},{"key":"e_1_3_2_1_3_1","doi-asserted-by":"crossref","unstructured":"Kristopher De\u00a0Asis J Hernandez-Garcia G Holland and Richard Sutton. 2018. Multi-step reinforcement learning: A unifying algorithm. In AAAI Vol.\u00a032.","DOI":"10.1609\/aaai.v32i1.11631"},{"key":"e_1_3_2_1_4_1","unstructured":"Google. 2021. UI\/Application Exerciser Monkey. Retrieved March 3 2021 from https:\/\/developer.android.com\/studio\/test\/monkey"},{"key":"e_1_3_2_1_5_1","volume-title":"Practical GUI testing of Android applications via model abstraction and refinement","author":"Gu Tianxiao","unstructured":"Tianxiao Gu, Chengnian Sun, Xiaoxing Ma, Chun Cao, Chang Xu, Yuan Yao, Qirun Zhang, Jian Lu, and Zhendong Su. 2019. Practical GUI testing of Android applications via model abstraction and refinement. In ICSE. IEEE, 269\u2013280."},{"key":"e_1_3_2_1_6_1","volume-title":"Sapienz: Multi-objective automated testing for android applications. In ISSTA. 94\u2013105.","author":"Mao Ke","year":"2016","unstructured":"Ke Mao, Mark Harman, and Yue Jia. 2016. Sapienz: Multi-objective automated testing for android applications. In ISSTA. 94\u2013105."},{"key":"e_1_3_2_1_7_1","volume-title":"Crowd intelligence enhances automated mobile testing","author":"Mao Ke","unstructured":"Ke Mao, Mark Harman, and Yue Jia. 2017. Crowd intelligence enhances automated mobile testing. In ASE. IEEE, 16\u201326."},{"key":"e_1_3_2_1_8_1","doi-asserted-by":"crossref","unstructured":"Minxue Pan An Huang Guoxin Wang Tian Zhang and Xuandong Li. 2020. Reinforcement learning based curiosity-driven testing of Android applications. In ISSTA. 153\u2013164.","DOI":"10.1145\/3395363.3397354"},{"key":"e_1_3_2_1_9_1","doi-asserted-by":"crossref","unstructured":"Ting Su Guozhu Meng Yuting Chen Ke Wu Weiming Yang Yao Yao Geguang Pu Yang Liu and Zhendong Su. 2017. Guided stochastic model-based GUI testing of Android apps. In ESEC\/FSE. 245\u2013256.","DOI":"10.1145\/3106237.3106298"},{"key":"e_1_3_2_1_10_1","unstructured":"Ting Su Jue Wang and Zhendong Su. 2021. Benchmarking Automated GUI Testing for Android against Real-World Bugs. In ESEC\/FSE. to appear."},{"key":"e_1_3_2_1_11_1","volume-title":"An empirical study of android test generation tools in industrial cases","author":"Wang Wenyu","unstructured":"Wenyu Wang, Dengfeng Li, Wei Yang, Yurui Cao, Zhenwen Zhang, Yuetang Deng, and Tao Xie. 2018. An empirical study of android test generation tools in industrial cases. In ASE. IEEE, 738\u2013748."},{"key":"e_1_3_2_1_12_1","doi-asserted-by":"crossref","unstructured":"Xia Zeng Dengfeng Li Wujie Zheng Fan Xia Yuetang Deng Wing Lam Wei Yang and Tao Xie. 2016. Automated test input generation for android: Are we really there yet in an industrial case?. In ESEC\/FSE. 987\u2013992.","DOI":"10.1145\/2950290.2983958"},{"key":"e_1_3_2_1_13_1","volume-title":"Automated test input generation for android: Towards getting there in an industrial case","author":"Zheng Haibing","unstructured":"Haibing Zheng, Dengfeng Li, Beihai Liang, Xia Zeng, Wujie Zheng, Yuetang Deng, Wing Lam, Wei Yang, and Tao Xie. 2017. Automated test input generation for android: Towards getting there in an industrial case. In ICSE-SEIP. IEEE, 253\u2013262."}],"event":{"name":"ASE '22: 37th IEEE\/ACM International Conference on Automated Software Engineering","location":"Rochester MI USA","acronym":"ASE '22"},"container-title":["Proceedings of the 37th IEEE\/ACM International Conference on Automated Software Engineering"],"original-title":[],"link":[{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3551349.3559505","content-type":"unspecified","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/dl.acm.org\/doi\/pdf\/10.1145\/3551349.3559505","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,8,22]],"date-time":"2025-08-22T08:37:33Z","timestamp":1755851853000},"score":1,"resource":{"primary":{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3551349.3559505"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2022,10,10]]},"references-count":13,"alternative-id":["10.1145\/3551349.3559505","10.1145\/3551349"],"URL":"https:\/\/doi.org\/10.1145\/3551349.3559505","relation":{},"subject":[],"published":{"date-parts":[[2022,10,10]]},"assertion":[{"value":"2023-01-05","order":3,"name":"published","label":"Published","group":{"name":"publication_history","label":"Publication History"}}]}}