{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,7,16]],"date-time":"2026-07-16T02:40:43Z","timestamp":1784169643374,"version":"3.55.0"},"publisher-location":"New York, NY, USA","reference-count":72,"publisher":"ACM","license":[{"start":{"date-parts":[[2020,6,27]],"date-time":"2020-06-27T00:00:00Z","timestamp":1593216000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.acm.org\/publications\/policies\/copyright_policy#Background"}],"funder":[{"name":"CCF-1927679,CCF-1815186,CNS-1815336","award":["CCF-1927679,CCF-1815186,CNS-1815336"],"award-info":[{"award-number":["CCF-1927679,CCF-1815186,CNS-1815336"]}]}],"content-domain":{"domain":["dl.acm.org"],"crossmark-restriction":true},"short-container-title":[],"published-print":{"date-parts":[[2020,6,27]]},"DOI":"10.1145\/3377811.3380328","type":"proceedings-article","created":{"date-parts":[[2020,10,1]],"date-time":"2020-10-01T18:25:38Z","timestamp":1601576738000},"page":"309-321","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":61,"title":["Translating video recordings of mobile app usages into replayable scenarios"],"prefix":"10.1145","author":[{"given":"Carlos","family":"Bernal-C\u00e1rdenas","sequence":"first","affiliation":[{"name":"William &amp; Mary"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Nathan","family":"Cooper","sequence":"additional","affiliation":[{"name":"William &amp; Mary"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Kevin","family":"Moran","sequence":"additional","affiliation":[{"name":"William &amp; Mary"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Oscar","family":"Chaparro","sequence":"additional","affiliation":[{"name":"William &amp; Mary"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Andrian","family":"Marcus","sequence":"additional","affiliation":[{"name":"The University of Texas at Dallas"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Denys","family":"Poshyvanyk","sequence":"additional","affiliation":[{"name":"William &amp; Mary"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"320","published-online":{"date-parts":[[2020,10]]},"reference":[{"key":"e_1_3_2_1_1_1","unstructured":"2014. Android Fragmentation Statistics http:\/\/opensignal.com\/reports\/2014\/android-fragmentation\/."},{"key":"e_1_3_2_1_2_1","unstructured":"2019. 7-Eleven https:\/\/play.google.com\/store\/apps\/details?id=com.sei.android."},{"key":"e_1_3_2_1_3_1","unstructured":"2019. Airtest Project. Retrieved August 14 2019 from http:\/\/airtest.netease.com\/"},{"key":"e_1_3_2_1_4_1","unstructured":"2019. Android Show Touches Option https:\/\/medium.theuxblog.com\/enabling-show-touches-in-android-screen-recordings-for-user-research-cc968563fcb9."},{"key":"e_1_3_2_1_5_1","unstructured":"2019. Applause Crowdsourced Testing Service https:\/\/www.applause.com\/crowdtesting."},{"key":"e_1_3_2_1_6_1","unstructured":"2019. AppSee https:\/\/www.appsee.com."},{"key":"e_1_3_2_1_7_1","unstructured":"2019. BugClipper http:\/\/bugclipper.com."},{"key":"e_1_3_2_1_8_1","unstructured":"2019. Command line tools for recording replaying and mirroring touchscreen events for Android: appetizerio\/replaykit. https:\/\/github.com\/appetizerio\/replaykitoriginal-date:2016-10-28T01:10:09Z."},{"key":"e_1_3_2_1_9_1","unstructured":"2019. Create UI tests with Espresso Test Recorder. https:\/\/developer.android.com\/studio\/test\/espresso-test-recorder"},{"key":"e_1_3_2_1_10_1","unstructured":"2019. FFmpeg tool https:\/\/www.ffmpeg.org\/."},{"key":"e_1_3_2_1_11_1","unstructured":"2019. Google Play Screen Recording Apps https:\/\/play.google.com\/store\/search?q=screen%20recording&c=apps."},{"key":"e_1_3_2_1_12_1","unstructured":"2019. Google Search https:\/\/play.google.com\/store\/apps\/details?id=com.google.android.googlequicksearchbox."},{"key":"e_1_3_2_1_13_1","unstructured":"2019. HiroMacro Auto-Touch Macro - Apps on Google Play. https:\/\/play.google.com\/store\/apps\/details?id=com.prohiro.macro&hl=en"},{"key":"e_1_3_2_1_14_1","unstructured":"2019. Mr. Tappy Mobile Usability Testing Device https:\/\/www.mrtappy.com."},{"key":"e_1_3_2_1_15_1","unstructured":"2019. MyCrowd Crowdsourced Testing Service https:\/\/mycrowd.com."},{"key":"e_1_3_2_1_16_1","unstructured":"2019. Proximus https:\/\/www.proximus.be."},{"key":"e_1_3_2_1_17_1","unstructured":"2019. [ROOT] Bot Maker for Android - Apps on Google Play. https:\/\/play.google.com\/store\/apps\/details?id=com.frapeti.androidbotmaker&hl=en"},{"key":"e_1_3_2_1_18_1","unstructured":"2019. Stackoverflow Android Screen Record https:\/\/stackoverflow.com\/questions\/29546743\/what-is-the-frame-rate-of-screen-record\/44523688."},{"key":"e_1_3_2_1_19_1","unstructured":"2019. TensorFlow Object Detection API https:\/\/github.com\/tensorflow\/models\/tree\/master\/research\/object_detection."},{"key":"e_1_3_2_1_20_1","unstructured":"2019. TestBirds Crowdsourced Testing Service https:\/\/www.testbirds.com."},{"key":"e_1_3_2_1_21_1","unstructured":"2019. TestFairy https:\/\/testfairy.com."},{"key":"e_1_3_2_1_22_1","unstructured":"2019. WatchSend https:\/\/watchsend.com."},{"key":"e_1_3_2_1_23_1","doi-asserted-by":"publisher","DOI":"10.1109\/ICSE.2015.220"},{"key":"e_1_3_2_1_24_1","doi-asserted-by":"publisher","DOI":"10.1109\/TSE.2014.2367027"},{"key":"e_1_3_2_1_25_1","doi-asserted-by":"publisher","DOI":"10.1145\/3220134.3220135"},{"key":"e_1_3_2_1_26_1","unstructured":"Carlos Bernal-C\u00e1rdenas Nathan Cooper Kevin Moran Oscar Chaparro Andrian Marcus and Denys Poshyvanyk. 2019. V2S Online Appendix https:\/\/sites.google.com\/view\/video2sceneario\/home."},{"key":"e_1_3_2_1_27_1","doi-asserted-by":"publisher","DOI":"10.1145\/1453101.1453146"},{"key":"e_1_3_2_1_28_1","doi-asserted-by":"publisher","DOI":"10.1145\/3338906.3338947"},{"key":"e_1_3_2_1_29_1","doi-asserted-by":"publisher","DOI":"10.1145\/3180155.3180240"},{"key":"e_1_3_2_1_30_1","doi-asserted-by":"publisher","DOI":"10.1109\/SANER.2017.7884612"},{"key":"e_1_3_2_1_31_1","volume-title":"Proceedings of the 24th ACM SIGSOFT International Symposium on Foundations of Software Engineering (FSE'16)","author":"Sorbo Andrea Di","unstructured":"Andrea Di Sorbo, Sebastiano Panichella, Carol V. Alexandru, Junji Shimagaki, Corrado A. Visaggio, Gerardo Canfora, and Harald C. Gall. 2016. What Would Users Change in My App? Summarizing App Reviews for Recommending Software Changes. In Proceedings of the 24th ACM SIGSOFT International Symposium on Foundations of Software Engineering (FSE'16). Seattle, WA, USA, 499--510."},{"key":"e_1_3_2_1_32_1","volume-title":"Proceedings of the 10th IEEE International Conference on Software Testing, Verification and Validation (ICST'17)","author":"Fazzini M.","unstructured":"M. Fazzini, E. N. D. A. Freitas, S. R. Choudhary, and A. Orso. 2017. Barista: A Technique for Recording, Encoding, and Running Platform Independent Android Tests. In Proceedings of the 10th IEEE International Conference on Software Testing, Verification and Validation (ICST'17). 149--160."},{"key":"e_1_3_2_1_33_1","doi-asserted-by":"publisher","DOI":"10.1145\/2851581.2892388"},{"key":"e_1_3_2_1_34_1","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2014.81"},{"key":"e_1_3_2_1_35_1","doi-asserted-by":"publisher","DOI":"10.1109\/ICSE.2013.6606553"},{"key":"e_1_3_2_1_36_1","volume-title":"Proceedings of the IEEE International Symposium on Performance Analysis of Systems and Software (2015)","author":"Halpern M.","unstructured":"M. Halpern, Y. Zhu, R. Peri, and V. J. Reddi. 2015. Mosaic: cross-platform user-interaction record and replay for the fragmented android ecosystem. In Proceedings of the IEEE International Symposium on Performance Analysis of Systems and Software (2015) (ISPASS'15). 215--224."},{"key":"e_1_3_2_1_37_1","doi-asserted-by":"publisher","DOI":"10.1109\/WCRE.2012.18"},{"key":"e_1_3_2_1_38_1","volume-title":"Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR'16)","author":"He K.","unstructured":"K. He, X. Zhang, S. Ren, and J. Sun. 2016. Deep Residual Learning for Image Recognition. In Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR'16). 770--778."},{"key":"e_1_3_2_1_39_1","doi-asserted-by":"publisher","DOI":"10.1145\/2592798.2592813"},{"key":"e_1_3_2_1_40_1","doi-asserted-by":"publisher","DOI":"10.1145\/3236024.3236055"},{"key":"e_1_3_2_1_41_1","doi-asserted-by":"publisher","DOI":"10.1145\/2814270.2814320"},{"key":"e_1_3_2_1_42_1","volume-title":"Troyd: Integration Testing for Android.","author":"Jeon Jinseong","year":"2012","unstructured":"Jinseong Jeon and Jeffrey S Foster. 2012. Troyd: Integration Testing for Android. (2012), 7."},{"key":"e_1_3_2_1_44_1","doi-asserted-by":"publisher","DOI":"10.1145\/3229434.3229450"},{"key":"e_1_3_2_1_45_1","volume-title":"Proceedings of the 25th Neural Information Processing Systems (NeurIPS'12)","author":"Krizhevsky Alex","year":"2012","unstructured":"Alex Krizhevsky, Ilya Sutskever, and Geoffrey E Hinton. 2012. ImageNet Classification with Deep Convolutional Neural Networks. In Proceedings of the 25th Neural Information Processing Systems (NeurIPS'12). 1097--1105."},{"key":"e_1_3_2_1_46_1","doi-asserted-by":"publisher","DOI":"10.1145\/3106237.3117769"},{"key":"e_1_3_2_1_47_1","doi-asserted-by":"publisher","DOI":"10.14722\/ndss.2014.23049"},{"key":"e_1_3_2_1_48_1","doi-asserted-by":"crossref","unstructured":"Tsung Yi Lin Michael Maire Serge Belongie James Hays Pietro Perona Deva Ramanan Piotr Doll\u00e1r and C. Lawrence Zitnick. 2014. Microsoft COCO: Common objects in context. 740--755 pages.","DOI":"10.1007\/978-3-319-10602-1_48"},{"key":"e_1_3_2_1_49_1","doi-asserted-by":"publisher","DOI":"10.1145\/2491411.2491428"},{"key":"e_1_3_2_1_50_1","doi-asserted-by":"publisher","DOI":"10.1109\/ICSME.2017.47"},{"key":"e_1_3_2_1_51_1","doi-asserted-by":"publisher","DOI":"10.1109\/ICSME.2017.27"},{"key":"e_1_3_2_1_52_1","doi-asserted-by":"publisher","DOI":"10.5555\/2820518.2820534"},{"key":"e_1_3_2_1_53_1","doi-asserted-by":"publisher","DOI":"10.5555\/3155562.3155569"},{"key":"e_1_3_2_1_54_1","unstructured":"Diego Torres Milano. 2019. Android ViewServer client. Contribute to dtmilano\/AndroidViewClient development by creating an account on GitHub. https:\/\/github.com\/dtmilano\/AndroidViewClient"},{"key":"e_1_3_2_1_55_1","doi-asserted-by":"publisher","DOI":"10.1145\/3196321.3196322"},{"key":"e_1_3_2_1_56_1","doi-asserted-by":"publisher","DOI":"10.1109\/MOBILESoft.2017.36"},{"key":"e_1_3_2_1_57_1","doi-asserted-by":"publisher","DOI":"10.1145\/2786805.2786857"},{"key":"e_1_3_2_1_58_1","doi-asserted-by":"publisher","DOI":"10.1109\/ICST.2016.34"},{"key":"e_1_3_2_1_59_1","volume-title":"Machine Learning-Based Prototyping of Graphical User Interfaces for Mobile Apps","author":"Moran Kevin Patrick","year":"2018","unstructured":"Kevin Patrick Moran, Carlos Bernal-Cardenas, Michael Curcio, Richard Bonett, and Denys Poshyvanyk. 2018. Machine Learning-Based Prototyping of Graphical User Interfaces for Mobile Apps. IEEE Transactions on Software Engineering (2018)."},{"key":"e_1_3_2_1_60_1","doi-asserted-by":"publisher","DOI":"10.1109\/ASE.2015.32"},{"key":"e_1_3_2_1_61_1","doi-asserted-by":"publisher","DOI":"10.1145\/3092703.3098231"},{"key":"e_1_3_2_1_62_1","volume-title":"Proceedings of the IEEE International Conference on Software Maintenance and Evolution (ICSME'15)","author":"Palomba F.","unstructured":"F. Palomba, M. Linares-Vasquez, G. Bavota, R. Oliveto,M.Di Penta, D. Poshyvanyk, and A. De Lucia. 2015. User reviews matter! Tracking crowdsourced reviews to support evolution of successful apps. In Proceedings of the IEEE International Conference on Software Maintenance and Evolution (ICSME'15). 291--300."},{"key":"e_1_3_2_1_63_1","volume-title":"Denys Poshyvanyk, and Andrea De Lucia.","author":"Palomba Fabio","year":"2018","unstructured":"Fabio Palomba, Mario Linares-V\u00e1squez, Gabriele Bavota, Rocco Oliveto, Massimiliano Di Penta, Denys Poshyvanyk, and Andrea De Lucia. 2018. Crowdsourcing user reviews to support the evolution of mobile apps. Journal of Systems and Software (2018), 143--162."},{"key":"e_1_3_2_1_64_1","doi-asserted-by":"publisher","DOI":"10.1109\/ICSE.2017.18"},{"key":"e_1_3_2_1_65_1","doi-asserted-by":"publisher","DOI":"10.1145\/2884781.2884854"},{"key":"e_1_3_2_1_66_1","volume-title":"Proceedings of the 28th International Conference on Neural Information Processing Systems (NeurIPS'15)","author":"Ren Shaoqing","year":"2015","unstructured":"Shaoqing Ren, Kaiming He, Ross Girshick, and Jian Sun. 2015. Faster R-CNN: Towards Real-time Object Detection with Region Proposal Networks. In Proceedings of the 28th International Conference on Neural Information Processing Systems (NeurIPS'15). Cambridge, MA, USA, 91--99."},{"key":"e_1_3_2_1_67_1","doi-asserted-by":"publisher","DOI":"10.1109\/TPAMI.2016.2577031"},{"key":"e_1_3_2_1_68_1","doi-asserted-by":"publisher","DOI":"10.1145\/1240866.1240908"},{"key":"e_1_3_2_1_69_1","volume-title":"Proceedings of the International Conference on Learning Representations (ICLR'14)","volume":"1409","author":"Simonyan Karen","year":"2014","unstructured":"Karen Simonyan and Andrew Zisserman. 2014. Very Deep Convolutional Networks for Large-Scale Image Recognition. In Proceedings of the International Conference on Learning Representations (ICLR'14), Vol. abs\/1409.1556."},{"key":"e_1_3_2_1_70_1","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2015.7298594"},{"key":"e_1_3_2_1_71_1","doi-asserted-by":"publisher","DOI":"10.1007\/s11263-013-0620-5"},{"key":"e_1_3_2_1_72_1","volume-title":"Proceedings of the 31st IEEE\/ACM International Conference on Automated Software Engineering (ASE'16)","author":"Wei L.","unstructured":"L. Wei, Y. Liu, and S. C. Cheung. 2016. Taming Android Fragmentation: Characterizing and Detecting Compatibility Issues for Android Apps. In Proceedings of the 31st IEEE\/ACM International Conference on Automated Software Engineering (ASE'16). 226--237."},{"key":"e_1_3_2_1_73_1","volume-title":"Proceedings of the 13th European Conference on Computer Vision (ECCV'14)","author":"Matthew","unstructured":"Matthew D. Zeiler and Rob Fergus. 2014. Visualizing and Understanding Convolutional Networks. In Proceedings of the 13th European Conference on Computer Vision (ECCV'14). Cham, 818--833."}],"event":{"name":"ICSE '20: 42nd International Conference on Software Engineering","location":"Seoul South Korea","acronym":"ICSE '20","sponsor":["SIGSOFT ACM Special Interest Group on Software Engineering","KIISE Korean Institute of Information Scientists and Engineers","IEEE CS"]},"container-title":["Proceedings of the ACM\/IEEE 42nd International Conference on Software Engineering"],"original-title":[],"link":[{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3377811.3380328","content-type":"unspecified","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/dl.acm.org\/doi\/pdf\/10.1145\/3377811.3380328","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,6,17]],"date-time":"2025-06-17T23:23:56Z","timestamp":1750202636000},"score":1,"resource":{"primary":{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3377811.3380328"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2020,6,27]]},"references-count":72,"alternative-id":["10.1145\/3377811.3380328","10.1145\/3377811"],"URL":"https:\/\/doi.org\/10.1145\/3377811.3380328","relation":{},"subject":[],"published":{"date-parts":[[2020,6,27]]},"assertion":[{"value":"2020-10-01","order":2,"name":"published","label":"Published","group":{"name":"publication_history","label":"Publication History"}}]}}