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These advances have led to widespread adoption and deployment of DL in security- and safety-critical systems, such as selfdriving cars, malware detection, and aircraft collision avoidance systems.<\/jats:p>","DOI":"10.1145\/3308755.3308767","type":"journal-article","created":{"date-parts":[[2019,1,17]],"date-time":"2019-01-17T17:15:15Z","timestamp":1547745315000},"page":"36-38","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":12,"title":["DeepXplore"],"prefix":"10.1145","volume":"22","author":[{"given":"Kexin","family":"Pei","sequence":"first","affiliation":[{"name":"Columbia University, New York, NY, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Yinzhi","family":"Cao","sequence":"additional","affiliation":[{"name":"The Johns Hopkins University, Baltimore, MD, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Junfeng","family":"Yang","sequence":"additional","affiliation":[{"name":"Columbia University, New York, NY, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Suman","family":"Jana","sequence":"additional","affiliation":[{"name":"Columbia University, New York, NY, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"320","published-online":{"date-parts":[[2019,1,17]]},"reference":[{"key":"e_1_2_1_1_1","unstructured":"Google-accident 2016. \"A Google self-driving car caused a crash for the first time.\" http:\/\/www. theverge.com\/2016\/2\/29\/11134344\/google-selfdriving- car-crash-report. (2016).  Google-accident 2016. \"A Google self-driving car caused a crash for the first time.\" http:\/\/www. theverge.com\/2016\/2\/29\/11134344\/google-selfdriving- car-crash-report. (2016)."},{"key":"e_1_2_1_2_1","unstructured":"Tesla-accident 2016. \"Understanding the fatal Tesla accident on Autopilot and the NHTSA probe.\" https:\/\/electrek.co\/2016\/07\/01\/understanding-fataltesla- accident-autopilot-nhtsa-probe\/. (2016).  Tesla-accident 2016. \"Understanding the fatal Tesla accident on Autopilot and the NHTSA probe.\" https:\/\/electrek.co\/2016\/07\/01\/understanding-fataltesla- accident-autopilot-nhtsa-probe\/. (2016)."},{"key":"e_1_2_1_3_1","volume-title":"Crowdsourcing, benchmarking & other cool things.\" Carnegie Mellon University VASC Seminar","author":"Fei-Fei Li.","year":"2010","unstructured":"Fei-Fei , Li. \" ImageNet : Crowdsourcing, benchmarking & other cool things.\" Carnegie Mellon University VASC Seminar . Vol. 16 . 2010 . Fei-Fei, Li. \"ImageNet: Crowdsourcing, benchmarking & other cool things.\" Carnegie Mellon University VASC Seminar. Vol. 16. 2010."},{"key":"e_1_2_1_4_1","unstructured":"2016. Report on autonomous mode disengagements for waymo self-driving vehicles in california. https:\/\/ www.dmv.ca.gov\/portal\/wcm\/connect\/42aff875- 7ab1--4115-a72a-97f6f24b23cc\/Waymofull. pdf?MOD=AJPERES&CVID=  2016. Report on autonomous mode disengagements for waymo self-driving vehicles in california. https:\/\/ www.dmv.ca.gov\/portal\/wcm\/connect\/42aff875- 7ab1--4115-a72a-97f6f24b23cc\/Waymofull. pdf?MOD=AJPERES&CVID="},{"key":"e_1_2_1_5_1","unstructured":"2017. \"Inside Waymo's secret world for training self-driving cars.\" https:\/\/www.theatlantic.com\/ technology\/archive\/2017\/08\/inside-waymos-secrettesting- and-simulation-facilities\/537648\/. (2017).  2017. \"Inside Waymo's secret world for training self-driving cars.\" https:\/\/www.theatlantic.com\/ technology\/archive\/2017\/08\/inside-waymos-secrettesting- and-simulation-facilities\/537648\/. (2017)."},{"key":"e_1_2_1_6_1","unstructured":"Ian Goodfellow Jonathon Shlens and Christian Szegedy. 2015. \"Explaining and harnessing adversarial examples.\" In Proceedings of the 3rd International Conference on Learning Representations. https:\/\/arxiv.org\/abs\/1412.6572  Ian Goodfellow Jonathon Shlens and Christian Szegedy. 2015. \"Explaining and harnessing adversarial examples.\" In Proceedings of the 3rd International Conference on Learning Representations. https:\/\/arxiv.org\/abs\/1412.6572"},{"key":"e_1_2_1_7_1","volume-title":"High confidence predictions for unrecognizable images.\" In Proceedings of the 28th IEEE Conference on Computer Vision and Pattern Recognition","author":"Anh Nguyen Jason Yosinski","unstructured":"Anh Nguyen , Jason Yosinski , and Jeff Clune . 2015. \"Deep neural networks are easily fooled : High confidence predictions for unrecognizable images.\" In Proceedings of the 28th IEEE Conference on Computer Vision and Pattern Recognition . Anh Nguyen, Jason Yosinski, and Jeff Clune. 2015. \"Deep neural networks are easily fooled: High confidence predictions for unrecognizable images.\" In Proceedings of the 28th IEEE Conference on Computer Vision and Pattern Recognition."},{"key":"e_1_2_1_8_1","unstructured":"Christian Szegedy Wojciech Zaremba Ilya Sutskever Joan Bruna Dumitru Erhan Ian Goodfellow and Rob Fergus. 2014. \"Intriguing properties of neural networks.\" In Proceedings of the 2nd International Conference on Learning Representations.  Christian Szegedy Wojciech Zaremba Ilya Sutskever Joan Bruna Dumitru Erhan Ian Goodfellow and Rob Fergus. 2014. \"Intriguing properties of neural networks.\" In Proceedings of the 2nd International Conference on Learning Representations."},{"key":"e_1_2_1_9_1","unstructured":"William M McKeeman. 1998. \"Differential testing for software.\" Digital Technical Journal (1998).  William M McKeeman. 1998. \"Differential testing for software.\" Digital Technical Journal (1998)."}],"container-title":["GetMobile: Mobile Computing and Communications"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3308755.3308767","content-type":"unspecified","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/dl.acm.org\/doi\/pdf\/10.1145\/3308755.3308767","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,6,18]],"date-time":"2025-06-18T00:58:03Z","timestamp":1750208283000},"score":1,"resource":{"primary":{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3308755.3308767"}},"subtitle":["Automated Whitebox Testing of Deep Learning Systems"],"short-title":[],"issued":{"date-parts":[[2019,1,17]]},"references-count":9,"journal-issue":{"issue":"3","published-print":{"date-parts":[[2019,1,17]]}},"alternative-id":["10.1145\/3308755.3308767"],"URL":"https:\/\/doi.org\/10.1145\/3308755.3308767","relation":{},"ISSN":["2375-0529","2375-0537"],"issn-type":[{"value":"2375-0529","type":"print"},{"value":"2375-0537","type":"electronic"}],"subject":[],"published":{"date-parts":[[2019,1,17]]},"assertion":[{"value":"2019-01-17","order":2,"name":"published","label":"Published","group":{"name":"publication_history","label":"Publication History"}}]}}