{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,12,18]],"date-time":"2025-12-18T12:30:18Z","timestamp":1766061018938,"version":"3.48.0"},"reference-count":78,"publisher":"Institute of Electrical and Electronics Engineers (IEEE)","issue":"12","license":[{"start":{"date-parts":[[2025,12,1]],"date-time":"2025-12-01T00:00:00Z","timestamp":1764547200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/ieeexplore.ieee.org\/Xplorehelp\/downloads\/license-information\/IEEE.html"},{"start":{"date-parts":[[2025,12,1]],"date-time":"2025-12-01T00:00:00Z","timestamp":1764547200000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-029"},{"start":{"date-parts":[[2025,12,1]],"date-time":"2025-12-01T00:00:00Z","timestamp":1764547200000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-037"}],"funder":[{"DOI":"10.13039\/100002463","name":"General Motors","doi-asserted-by":"publisher","id":[{"id":"10.13039\/100002463","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100000038","name":"Canada Research Chair and Discovery Grant Programs of the Natural Sciences and Engineering Research Council of Canada","doi-asserted-by":"publisher","id":[{"id":"10.13039\/501100000038","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100001602","name":"Research Ireland","doi-asserted-by":"publisher","award":["13\/RC\/2094-2"],"award-info":[{"award-number":["13\/RC\/2094-2"]}],"id":[{"id":"10.13039\/501100001602","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["IIEEE Trans. Software Eng."],"published-print":{"date-parts":[[2025,12]]},"DOI":"10.1109\/tse.2025.3611329","type":"journal-article","created":{"date-parts":[[2025,9,19]],"date-time":"2025-09-19T17:37:12Z","timestamp":1758303432000},"page":"3284-3309","source":"Crossref","is-referenced-by-count":0,"title":["DiffGAN: A Test Generation Approach for Differential Testing of Deep Neural Networks for Image Analysis"],"prefix":"10.1109","volume":"51","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-9375-4095","authenticated-orcid":false,"given":"Zohreh","family":"Aghababaeyan","sequence":"first","affiliation":[{"name":"School of EECS, University of Ottawa, Ottawa, ON, Canada"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-8647-1676","authenticated-orcid":false,"given":"Manel","family":"Abdellatif","sequence":"additional","affiliation":[{"name":"Software and Information Technology Engineering Department, &#x00C9;cole de Technologie Sup&#x00E9;rieure, Montreal, QC, Canada"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-1393-1010","authenticated-orcid":false,"given":"Lionel","family":"Briand","sequence":"additional","affiliation":[{"name":"School of Electrical Engineering and Computer Science (EECS), University of Ottawa, Ottawa, ON, Canada"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-8501-7447","authenticated-orcid":false,"given":"Ramesh","family":"S.","sequence":"additional","affiliation":[{"name":"Department of Research and Development, General Motors, Warren, MI, USA"}]}],"member":"263","reference":[{"key":"ref1","doi-asserted-by":"publisher","DOI":"10.1109\/TSE.2023.3243522"},{"key":"ref2","doi-asserted-by":"publisher","DOI":"10.1016\/j.neucom.2020.07.053"},{"key":"ref3","doi-asserted-by":"publisher","DOI":"10.1109\/ICSE48619.2023.00104"},{"key":"ref4","doi-asserted-by":"publisher","DOI":"10.1145\/3132747.3132785"},{"key":"ref5","doi-asserted-by":"publisher","DOI":"10.1145\/3293882.3330579"},{"key":"ref6","doi-asserted-by":"publisher","DOI":"10.1007\/s10664-022-10202-w"},{"key":"ref7","doi-asserted-by":"publisher","DOI":"10.1109\/ICSME.2019.00078"},{"key":"ref8","doi-asserted-by":"publisher","DOI":"10.24963\/ijcai.2019\/800"},{"key":"ref9","doi-asserted-by":"publisher","DOI":"10.1145\/3583564"},{"key":"ref10","doi-asserted-by":"publisher","DOI":"10.1109\/ICSE48619.2023.00019"},{"key":"ref11","doi-asserted-by":"publisher","DOI":"10.1145\/3533767.3534386"},{"key":"ref12","doi-asserted-by":"publisher","DOI":"10.1145\/3460319.3464816"},{"key":"ref13","doi-asserted-by":"publisher","DOI":"10.1109\/CVPRW53098.2021.00356"},{"article-title":"TensorFlow lite guide","year":"2024","author":"Authors","key":"ref14"},{"key":"ref15","doi-asserted-by":"publisher","DOI":"10.1109\/IOLTS.2019.8854377"},{"key":"ref16","article-title":"Adversarial sample detection via channel pruning","volume-title":"Proc. Workshop Adversarial Mach. Learn.","author":"Chen","year":"2021"},{"article-title":"GAN augmentation: Augmenting training data using generative adversarial networks","year":"2018","author":"Bowles","key":"ref17"},{"key":"ref18","doi-asserted-by":"publisher","DOI":"10.1186\/s40537-019-0197-0"},{"key":"ref19","doi-asserted-by":"publisher","DOI":"10.1145\/3238147.3238187"},{"key":"ref20","doi-asserted-by":"publisher","DOI":"10.1109\/hpcc-dss-smartcity-dependsys57074.2022.00244"},{"key":"ref21","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2017.632"},{"key":"ref22","first-page":"321","article-title":"Gan-based synthetic medical image augmentation for increased CNN performance in liver lesion classification","volume-title":"Neurocomputing","volume":"321","author":"Frid-Adar","year":"2018"},{"article-title":"Unsupervised representation learning with deep convolutional generative adversarial networks","year":"2015","author":"Radford","key":"ref23"},{"key":"ref24","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR42600.2020.00926"},{"key":"ref25","doi-asserted-by":"publisher","DOI":"10.1145\/2430536.2430540"},{"key":"ref26","doi-asserted-by":"publisher","DOI":"10.1016\/j.jss.2014.08.024"},{"key":"ref27","doi-asserted-by":"publisher","DOI":"10.1145\/3644388"},{"key":"ref28","doi-asserted-by":"publisher","DOI":"10.1109\/TEC.2022.3208129"},{"issue":"4","key":"ref29","first-page":"567","article-title":"NSGAN: Multi-objective optimization-oriented generative adversarial design for multi-principal element alloys","volume":"11","author":"Wang","year":"2022","journal-title":"Integr. Mater. Manuf. Innov."},{"issue":"4","key":"ref30","first-page":"1033","article-title":"Aerodynamic shape optimization using graph variational autoencoders and genetic algorithms","volume":"65","author":"Hou","year":"2022","journal-title":"Struct. Multidiscip. Optim."},{"key":"ref31","doi-asserted-by":"publisher","DOI":"10.1109\/ICST.2015.7102604"},{"key":"ref32","doi-asserted-by":"publisher","DOI":"10.1186\/s40537-019-0197-0"},{"article-title":"An empirical study on evaluation metrics of generative adversarial networks","year":"2018","author":"Xu","key":"ref33"},{"key":"ref34","first-page":"6629","article-title":"GANs trained by a two time-scale update rule converge to a local Nash equilibrium","volume-title":"Proc. 31st Int. Conf. Neural Inform. Process. Syst. (NIPS)","author":"Heusel","year":"2017"},{"key":"ref35","doi-asserted-by":"publisher","DOI":"10.1145\/3292500.3330701"},{"key":"ref36","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-030-43722-0_38"},{"key":"ref37","doi-asserted-by":"publisher","DOI":"10.1109\/ICASSP.2007.366913"},{"key":"ref38","doi-asserted-by":"publisher","DOI":"10.21105\/joss.00205"},{"key":"ref39","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-030-51935-3_34"},{"key":"ref40","article-title":"Multi-objective wind power scenario forecasting based on PG-GAN","volume-title":"Energy","volume":"226","author":"Yuan","year":"2021"},{"issue":"2","key":"ref41","first-page":"115","article-title":"Simulated binary crossover for continuous search space","volume":"9","author":"Deb","year":"1995","journal-title":"Complex Syst."},{"key":"ref42","volume-title":"Multi-Objective Optimization Using Evolutionary Algorithms","volume":"16","author":"Deb","year":"2001"},{"key":"ref43","doi-asserted-by":"publisher","DOI":"10.1162\/evco.1996.4.2.113"},{"key":"ref44","doi-asserted-by":"publisher","DOI":"10.1109\/2.294849"},{"article-title":"Adaptation in natural and artificial systems: An introductory analysis with applications to biology, control, and artificial intelligence","year":"1975","author":"Holland","key":"ref45"},{"key":"ref46","first-page":"167","article-title":"A search-based approach for accurate identification of log message formats","volume-title":"Proc. IEEE\/ACM 26th Int. Conf. Program Comprehension (ICPC)","author":"Messaoudi","year":"2018"},{"key":"ref47","doi-asserted-by":"publisher","DOI":"10.1109\/ACCESS.2020.2990567"},{"key":"ref48","doi-asserted-by":"publisher","DOI":"10.1109\/TIP.2003.819861"},{"key":"ref49","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2017.632"},{"key":"ref50","first-page":"15093","article-title":"Improving GANs with a dynamic discriminator","volume-title":"Proc. Adv. Neural Inform. Process. Syst.","volume":"35","author":"Yang","year":"2022"},{"key":"ref51","doi-asserted-by":"publisher","DOI":"10.1016\/j.patcog.2014.05.003"},{"key":"ref52","doi-asserted-by":"publisher","DOI":"10.1016\/j.inffus.2017.09.010"},{"key":"ref53","doi-asserted-by":"publisher","DOI":"10.1145\/3338906.3338930"},{"key":"ref54","doi-asserted-by":"publisher","DOI":"10.1109\/MSP.2012.2211477"},{"author":"Alex","key":"ref55","article-title":"The CIFAR-10 dataset"},{"key":"ref56","first-page":"1097","article-title":"ImageNet classification with deep convolutional neural networks","volume-title":"Proc. Adv. Neural Inf. Process. Syst. (NIPS)","author":"Krizhevsky","year":"2012"},{"key":"ref57","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2015.7298594"},{"key":"ref58","doi-asserted-by":"publisher","DOI":"10.1109\/5.726791"},{"key":"ref59","doi-asserted-by":"publisher","DOI":"10.1002\/j.1538-7305.1948.tb01338.x"},{"key":"ref60","doi-asserted-by":"publisher","DOI":"10.1109\/18.119732"},{"volume-title":"The Cambridge Dictionary of Statistics, Repr. with Corrections ed","year":"1998","author":"Everitt","key":"ref61"},{"issue":"11","key":"ref62","first-page":"1","article-title":"Sampling techniques & determination of sample size in applied statistics research: An overview","volume":"2","author":"Singh","year":"2014","journal-title":"Int. J. Econ., Commerce Manage."},{"key":"ref63","doi-asserted-by":"publisher","DOI":"10.2307\/3315487"},{"key":"ref64","doi-asserted-by":"publisher","DOI":"10.4135\/9781412983532"},{"key":"ref65","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-319-30634-6_5"},{"key":"ref66","doi-asserted-by":"publisher","DOI":"10.1109\/ICAIIC48513.2020.9065274"},{"key":"ref67","article-title":"Differential image analysis using Shannon\u2019s entropy: Preliminary results","volume-title":"Proc. 7th ICT Innov., Ohrid, North Macedonia","author":"Garcia","year":"2015"},{"article-title":"GANs with variational entropy regularizers: Applications in mitigating the mode-collapse issue","year":"2020","author":"Khorramshahi","key":"ref68"},{"key":"ref69","doi-asserted-by":"publisher","DOI":"10.1561\/9781601986290"},{"key":"ref70","first-page":"2069","article-title":"Diverse sequential subset selection for supervised video summarization","volume-title":"Proc. Adv. Neural Inf. Process. Syst.","volume":"27","author":"Gong","year":"2014"},{"issue":"1","key":"ref71","first-page":"3133","article-title":"Do we need hundreds of classifiers to solve real world classification problems?","volume":"15","author":"Fern\u00e1ndez-Delgado","year":"2014","journal-title":"J. Mach. Learn. Res."},{"key":"ref72","doi-asserted-by":"publisher","DOI":"10.29172\/7c2a6982-6d72-4cd8-bba6-2fccb06a7011"},{"key":"ref73","doi-asserted-by":"publisher","DOI":"10.2307\/2699986"},{"article-title":"When, why, and which pretrained GANs are useful?","volume-title":"Proc. Int. Conf. Learn. Representations","author":"Grigoryev","key":"ref74"},{"key":"ref75","first-page":"11340","volume-title":"Proc. Int. Conf. Mach. Learn. PMLR","author":"Zhao","year":"2020"},{"key":"ref76","doi-asserted-by":"publisher","DOI":"10.1145\/3597503.3639106"},{"key":"ref77","first-page":"6471","volume-title":"Proc. Int. Conf. Mach. Learn.","author":"Li","year":"2021"},{"key":"ref78","doi-asserted-by":"publisher","DOI":"10.1109\/32.605761"}],"container-title":["IEEE Transactions on Software Engineering"],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx8\/32\/11298241\/11173835.pdf?arnumber=11173835","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,12,18]],"date-time":"2025-12-18T12:25:59Z","timestamp":1766060759000},"score":1,"resource":{"primary":{"URL":"https:\/\/ieeexplore.ieee.org\/document\/11173835\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2025,12]]},"references-count":78,"journal-issue":{"issue":"12"},"URL":"https:\/\/doi.org\/10.1109\/tse.2025.3611329","relation":{},"ISSN":["0098-5589","1939-3520","2326-3881"],"issn-type":[{"type":"print","value":"0098-5589"},{"type":"electronic","value":"1939-3520"},{"type":"electronic","value":"2326-3881"}],"subject":[],"published":{"date-parts":[[2025,12]]}}}