{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,13]],"date-time":"2026-04-13T23:17:01Z","timestamp":1776122221902,"version":"3.50.1"},"publisher-location":"New York, NY, USA","reference-count":30,"publisher":"ACM","license":[{"start":{"date-parts":[[2018,9,3]],"date-time":"2018-09-03T00:00:00Z","timestamp":1535932800000},"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":[[2018,9,3]]},"DOI":"10.1145\/3238147.3238172","type":"proceedings-article","created":{"date-parts":[[2018,8,20]],"date-time":"2018-08-20T20:04:36Z","timestamp":1534795476000},"page":"109-119","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":233,"title":["Concolic testing for deep neural networks"],"prefix":"10.1145","author":[{"given":"Youcheng","family":"Sun","sequence":"first","affiliation":[{"name":"University of Oxford, UK"}]},{"given":"Min","family":"Wu","sequence":"additional","affiliation":[{"name":"University of Oxford, UK"}]},{"given":"Wenjie","family":"Ruan","sequence":"additional","affiliation":[{"name":"University of Oxford, UK"}]},{"given":"Xiaowei","family":"Huang","sequence":"additional","affiliation":[{"name":"University of Liverpool, UK"}]},{"given":"Marta","family":"Kwiatkowska","sequence":"additional","affiliation":[{"name":"University of Oxford, UK"}]},{"given":"Daniel","family":"Kroening","sequence":"additional","affiliation":[{"name":"University of Oxford, UK"}]}],"member":"320","published-online":{"date-parts":[[2018,9,3]]},"reference":[{"key":"e_1_3_2_1_1_1","volume-title":"arXiv preprint arXiv:1701.07875","author":"Arjovsky Martin","year":"2017","unstructured":"Martin Arjovsky , Soumith Chintala , and L\u00e9on Bottou . 2017. Wasserstein GAN. arXiv preprint arXiv:1701.07875 ( 2017 ). Martin Arjovsky, Soumith Chintala, and L\u00e9on Bottou. 2017. Wasserstein GAN. arXiv preprint arXiv:1701.07875 (2017)."},{"key":"e_1_3_2_1_2_1","volume-title":"Derivative-Free and Blackbox Optimization","author":"Audet Charles","unstructured":"Charles Audet and Warren Hare . 2017. Derivative-Free and Blackbox Optimization . Springer . Charles Audet and Warren Hare. 2017. Derivative-Free and Blackbox Optimization. Springer."},{"key":"e_1_3_2_1_3_1","volume-title":"Lipschitz Properties for Deep Convolutional Networks. arXiv preprint arXiv:1701.05217","author":"Balan Radu","year":"2017","unstructured":"Radu Balan , Maneesh Singh , and Dongmian Zou . 2017. Lipschitz Properties for Deep Convolutional Networks. arXiv preprint arXiv:1701.05217 ( 2017 ). Radu Balan, Maneesh Singh, and Dongmian Zou. 2017. Lipschitz Properties for Deep Convolutional Networks. arXiv preprint arXiv:1701.05217 (2017)."},{"key":"e_1_3_2_1_4_1","doi-asserted-by":"publisher","DOI":"10.1109\/ASE.2008.69"},{"key":"e_1_3_2_1_5_1","first-page":"209","article-title":"KLEE: Unassisted and Automatic Generation of High-Coverage Tests for Complex Systems Programs","volume":"8","author":"Cadar Cristian","year":"2008","unstructured":"Cristian Cadar , Daniel Dunbar , and Dawson R. Engler . 2008 . KLEE: Unassisted and Automatic Generation of High-Coverage Tests for Complex Systems Programs . In OSDI , Vol. 8. 209 \u2013 224 . Cristian Cadar, Daniel Dunbar, and Dawson R. Engler. 2008. KLEE: Unassisted and Automatic Generation of High-Coverage Tests for Complex Systems Programs. In OSDI, Vol. 8. 209\u2013224.","journal-title":"OSDI"},{"key":"e_1_3_2_1_6_1","doi-asserted-by":"publisher","DOI":"10.1145\/3180155.3180166"},{"key":"e_1_3_2_1_7_1","doi-asserted-by":"publisher","DOI":"10.1109\/SP.2018.00058"},{"key":"e_1_3_2_1_8_1","doi-asserted-by":"publisher","DOI":"10.1145\/1065010.1065036"},{"key":"e_1_3_2_1_9_1","first-page":"151","article-title":"Automated Whitebox Fuzz Testing","volume":"8","author":"Godefroid Patrice","year":"2008","unstructured":"Patrice Godefroid , Michael Y Levin , David A Molnar , and others. 2008 . Automated Whitebox Fuzz Testing . In NDSS , Vol. 8. 151 \u2013 166 . Patrice Godefroid, Michael Y Levin, David A Molnar, and others. 2008. Automated Whitebox Fuzz Testing. In NDSS, Vol. 8. 151\u2013166.","journal-title":"NDSS"},{"key":"e_1_3_2_1_11_1","volume-title":"Safety Verification of Deep Neural Networks. In International Conference on Computer Aided Verification, CAV. Springer, 3\u201329","author":"Huang Xiaowei","year":"2017","unstructured":"Xiaowei Huang , Marta Kwiatkowska , Sen Wang , and Min Wu . 2017 . Safety Verification of Deep Neural Networks. In International Conference on Computer Aided Verification, CAV. Springer, 3\u201329 . Xiaowei Huang, Marta Kwiatkowska, Sen Wang, and Min Wu. 2017. Safety Verification of Deep Neural Networks. In International Conference on Computer Aided Verification, CAV. Springer, 3\u201329."},{"key":"e_1_3_2_1_12_1","volume-title":"Exploratory Testing. In Quality Assurance Institute Worldwide Annual Software Testing Conference.","author":"Kaner Cem","year":"2006","unstructured":"Cem Kaner . 2006 . Exploratory Testing. In Quality Assurance Institute Worldwide Annual Software Testing Conference. Cem Kaner. 2006. Exploratory Testing. In Quality Assurance Institute Worldwide Annual Software Testing Conference."},{"key":"e_1_3_2_1_13_1","volume-title":"Challenges and Opportunities with Concolic Testing. In Aerospace and Electronics Conference (NAECON)","author":"Kannavara Raghudeep","year":"2015","unstructured":"Raghudeep Kannavara , Christopher J Havlicek , Bo Chen , Mark R Tuttle , Kai Cong , Sandip Ray , and Fei Xie . 2015 . Challenges and Opportunities with Concolic Testing. In Aerospace and Electronics Conference (NAECON) , 2015 National. IEEE, 374\u2013378. Raghudeep Kannavara, Christopher J Havlicek, Bo Chen, Mark R Tuttle, Kai Cong, Sandip Ray, and Fei Xie. 2015. Challenges and Opportunities with Concolic Testing. In Aerospace and Electronics Conference (NAECON), 2015 National. IEEE, 374\u2013378."},{"key":"e_1_3_2_1_14_1","volume-title":"Reluplex: An Efficient SMT Solver for Verifying Deep Neural Networks. In International Conference on Computer Aided Verification. Springer, 97\u2013117","author":"Katz Guy","year":"2017","unstructured":"Guy Katz , Clark Barrett , David L Dill , Kyle Julian , and Mykel J Kochenderfer . 2017 . Reluplex: An Efficient SMT Solver for Verifying Deep Neural Networks. In International Conference on Computer Aided Verification. Springer, 97\u2013117 . Guy Katz, Clark Barrett, David L Dill, Kyle Julian, and Mykel J Kochenderfer. 2017. Reluplex: An Efficient SMT Solver for Verifying Deep Neural Networks. In International Conference on Computer Aided Verification. Springer, 97\u2013117."},{"key":"e_1_3_2_1_15_1","volume-title":"DeepGauge: Comprehensive and Multi-Granularity Testing Criteria for Gauging the Robustness of Deep Learning Systems. arXiv preprint arXiv:1803.07519","author":"Ma Lei","year":"2018","unstructured":"Lei Ma , Felix Juefei-Xu , Jiyuan Sun , Chunyang Chen , Ting Su , Fuyuan Zhang , Minhui Xue , Bo Li , Li Li , Yang Liu , and others. 2018. DeepGauge: Comprehensive and Multi-Granularity Testing Criteria for Gauging the Robustness of Deep Learning Systems. arXiv preprint arXiv:1803.07519 ( 2018 ). Lei Ma, Felix Juefei-Xu, Jiyuan Sun, Chunyang Chen, Ting Su, Fuyuan Zhang, Minhui Xue, Bo Li, Li Li, Yang Liu, and others. 2018. DeepGauge: Comprehensive and Multi-Granularity Testing Criteria for Gauging the Robustness of Deep Learning Systems. arXiv preprint arXiv:1803.07519 (2018)."},{"key":"e_1_3_2_1_16_1","volume-title":"Differentiable Abstract Interpretation for Provably Robust Neural Networks. In International Conference on Machine Learning. 3575\u20133583","author":"Mirman Matthew","year":"2018","unstructured":"Matthew Mirman , Timon Gehr , and Martin Vechev . 2018 . Differentiable Abstract Interpretation for Provably Robust Neural Networks. In International Conference on Machine Learning. 3575\u20133583 . Matthew Mirman, Timon Gehr, and Martin Vechev. 2018. Differentiable Abstract Interpretation for Provably Robust Neural Networks. In International Conference on Machine Learning. 3575\u20133583."},{"key":"e_1_3_2_1_17_1","volume-title":"Rectified Linear Units Improve Restricted Boltzmann Machines. In International Conference on Machine Learning. 807\u2013814","author":"Nair Vinod","year":"2010","unstructured":"Vinod Nair and Geoffrey E Hinton . 2010 . Rectified Linear Units Improve Restricted Boltzmann Machines. In International Conference on Machine Learning. 807\u2013814 . Vinod Nair and Geoffrey E Hinton. 2010. Rectified Linear Units Improve Restricted Boltzmann Machines. In International Conference on Machine Learning. 807\u2013814."},{"key":"e_1_3_2_1_18_1","doi-asserted-by":"publisher","DOI":"10.1145\/3132747.3132785"},{"key":"e_1_3_2_1_19_1","volume-title":"Relaxation in Optimization Theory and Variational Calculus","author":"Roubicek T.","unstructured":"T. Roubicek . 1997. Relaxation in Optimization Theory and Variational Calculus . Berlin : Walter de Gruyter . T. Roubicek. 1997. Relaxation in Optimization Theory and Variational Calculus. Berlin: Walter de Gruyter."},{"key":"e_1_3_2_1_20_1","volume-title":"Reachability Analysis of Deep Neural Networks with Provable Guarantees. In The 27th International Joint Conference on Artificial Intelligence, IJCAI. 2651\u20132659","author":"Ruan Wenjie","year":"2018","unstructured":"Wenjie Ruan , Xiaowei Huang , and Marta Kwiatkowska . 2018 . Reachability Analysis of Deep Neural Networks with Provable Guarantees. In The 27th International Joint Conference on Artificial Intelligence, IJCAI. 2651\u20132659 . Wenjie Ruan, Xiaowei Huang, and Marta Kwiatkowska. 2018. Reachability Analysis of Deep Neural Networks with Provable Guarantees. In The 27th International Joint Conference on Artificial Intelligence, IJCAI. 2651\u20132659."},{"key":"e_1_3_2_1_21_1","volume-title":"Global Robustness Evaluation of Deep Neural Networks with Provable Guarantees for L0 Norm. arXiv preprint arXiv:1804.05805v1","author":"Ruan Wenjie","year":"2018","unstructured":"Wenjie Ruan , Min Wu , Youcheng Sun , Xiaowei Huang , Daniel Kroening , and Marta Kwiatkowska . 2018. Global Robustness Evaluation of Deep Neural Networks with Provable Guarantees for L0 Norm. arXiv preprint arXiv:1804.05805v1 ( 2018 ). Wenjie Ruan, Min Wu, Youcheng Sun, Xiaowei Huang, Daniel Kroening, and Marta Kwiatkowska. 2018. Global Robustness Evaluation of Deep Neural Networks with Provable Guarantees for L0 Norm. arXiv preprint arXiv:1804.05805v1 (2018)."},{"key":"e_1_3_2_1_22_1","doi-asserted-by":"publisher","DOI":"10.1145\/1095430.1081750"},{"key":"e_1_3_2_1_23_1","volume-title":"Testing Deep Neural Networks. arXiv preprint arXiv:1803.04792","author":"Sun Youcheng","year":"2018","unstructured":"Youcheng Sun , Xiaowei Huang , and Daniel Kroening . 2018. Testing Deep Neural Networks. arXiv preprint arXiv:1803.04792 ( 2018 ). Youcheng Sun, Xiaowei Huang, and Daniel Kroening. 2018. Testing Deep Neural Networks. arXiv preprint arXiv:1803.04792 (2018)."},{"key":"e_1_3_2_1_24_1","volume-title":"Intriguing Properties of Neural Networks. In International Conference on Learning Representations (ICLR).","author":"Szegedy Christian","year":"2014","unstructured":"Christian Szegedy , Wojciech Zaremba , Ilya Sutskever , Joan Bruna , Dumitru Erhan , Ian Goodfellow , and Rob Fergus . 2014 . Intriguing Properties of Neural Networks. In International Conference on Learning Representations (ICLR). Christian Szegedy, Wojciech Zaremba, Ilya Sutskever, Joan Bruna, Dumitru Erhan, Ian Goodfellow, and Rob Fergus. 2014. Intriguing Properties of Neural Networks. In International Conference on Learning Representations (ICLR)."},{"key":"e_1_3_2_1_25_1","doi-asserted-by":"publisher","DOI":"10.1145\/3180155.3180220"},{"key":"e_1_3_2_1_26_1","doi-asserted-by":"publisher","DOI":"10.1145\/1013886.1007526"},{"key":"e_1_3_2_1_27_1","doi-asserted-by":"publisher","DOI":"10.1145\/3180155.3180177"},{"key":"e_1_3_2_1_28_1","volume-title":"Conference Record of the Thirty-Seventh Asilomar Conference on.","author":"Wang Zhou","year":"2003","unstructured":"Zhou Wang , Eero P Simoncelli , and Alan C Bovik . 2003 . Multiscale Structural Similarity for Image Quality Assessment. In Signals, Systems and Computers , Conference Record of the Thirty-Seventh Asilomar Conference on. Zhou Wang, Eero P Simoncelli, and Alan C Bovik. 2003. Multiscale Structural Similarity for Image Quality Assessment. In Signals, Systems and Computers, Conference Record of the Thirty-Seventh Asilomar Conference on."},{"key":"e_1_3_2_1_29_1","doi-asserted-by":"publisher","DOI":"10.1109\/TIT.2017.2776228"},{"key":"e_1_3_2_1_30_1","volume-title":"Feature-Guided Black-Box Safety Testing of Deep Neural Networks. In International Conference on Tools and Algorithms for the Construction and Analysis of Systems, TACAS. Springer, 408\u2013426","author":"Wicker Matthew","year":"2018","unstructured":"Matthew Wicker , Xiaowei Huang , and Marta Kwiatkowska . 2018 . Feature-Guided Black-Box Safety Testing of Deep Neural Networks. In International Conference on Tools and Algorithms for the Construction and Analysis of Systems, TACAS. Springer, 408\u2013426 . Matthew Wicker, Xiaowei Huang, and Marta Kwiatkowska. 2018. Feature-Guided Black-Box Safety Testing of Deep Neural Networks. In International Conference on Tools and Algorithms for the Construction and Analysis of Systems, TACAS. Springer, 408\u2013426."},{"key":"e_1_3_2_1_31_1","volume-title":"A Game-Based Approximate Verification of Deep Neural Networks with Provable Guarantees. arXiv preprint arXiv:1807.03571","author":"Wu Min","year":"2018","unstructured":"Min Wu , Matthew Wicker , Wenjie Ruan , Xiaowei Huang , and Marta Kwiatkowska . 2018. A Game-Based Approximate Verification of Deep Neural Networks with Provable Guarantees. arXiv preprint arXiv:1807.03571 ( 2018 ). Min Wu, Matthew Wicker, Wenjie Ruan, Xiaowei Huang, and Marta Kwiatkowska. 2018. A Game-Based Approximate Verification of Deep Neural Networks with Provable Guarantees. arXiv preprint arXiv:1807.03571 (2018)."}],"event":{"name":"ASE '18: 33rd ACM\/IEEE International Conference on Automated Software Engineering","location":"Montpellier France","acronym":"ASE '18","sponsor":["SIGAI ACM Special Interest Group on Artificial Intelligence","CNRS Centre National De La Rechercue Scientifique","SIGSOFT ACM Special Interest Group on Software Engineering","IEEE-CS Computer Society"]},"container-title":["Proceedings of the 33rd ACM\/IEEE International Conference on Automated Software Engineering"],"original-title":[],"link":[{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3238147.3238172","content-type":"unspecified","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/dl.acm.org\/doi\/pdf\/10.1145\/3238147.3238172","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,6,18]],"date-time":"2025-06-18T01:39:35Z","timestamp":1750210775000},"score":1,"resource":{"primary":{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3238147.3238172"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2018,9,3]]},"references-count":30,"alternative-id":["10.1145\/3238147.3238172","10.1145\/3238147"],"URL":"https:\/\/doi.org\/10.1145\/3238147.3238172","relation":{},"subject":[],"published":{"date-parts":[[2018,9,3]]},"assertion":[{"value":"2018-09-03","order":2,"name":"published","label":"Published","group":{"name":"publication_history","label":"Publication History"}}]}}