{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,7,1]],"date-time":"2026-07-01T03:12:30Z","timestamp":1782875550162,"version":"3.54.5"},"publisher-location":"New York, NY, USA","reference-count":49,"publisher":"ACM","license":[{"start":{"date-parts":[[2022,5,21]],"date-time":"2022-05-21T00:00:00Z","timestamp":1653091200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":["dl.acm.org"],"crossmark-restriction":true},"short-container-title":[],"published-print":{"date-parts":[[2022,5,21]]},"DOI":"10.1145\/3510003.3510165","type":"proceedings-article","created":{"date-parts":[[2022,7,5]],"date-time":"2022-07-05T22:42:59Z","timestamp":1657060979000},"page":"798-810","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":34,"title":["EAGLE"],"prefix":"10.1145","author":[{"given":"Jiannan","family":"Wang","sequence":"first","affiliation":[{"name":"Purdue University"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Thibaud","family":"Lutellier","sequence":"additional","affiliation":[{"name":"University of Waterloo, Waterloo, Canada"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Shangshu","family":"Qian","sequence":"additional","affiliation":[{"name":"Purdue University"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Hung Viet","family":"Pham","sequence":"additional","affiliation":[{"name":"University of Waterloo, Waterloo, Canada"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Lin","family":"Tan","sequence":"additional","affiliation":[{"name":"Purdue University"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"320","published-online":{"date-parts":[[2022,7,5]]},"reference":[{"key":"e_1_3_2_1_1_1","unstructured":"Mart\u00edn Abadi Ashish Agarwal Paul Barham Eugene Brevdo Zhifeng Chen Craig Citro Greg S. Corrado Andy Davis Jeffrey Dean Matthieu Devin Sanjay Ghemawat Ian Goodfellow Andrew Harp Geoffrey Irving Michael Isard Yangqing Jia Rafal Jozefowicz Lukasz Kaiser Manjunath Kudlur Josh Levenberg Dandelion Man\u00e9 Rajat Monga Sherry Moore Derek Murray Chris Olah Mike Schuster Jonathon Shlens Benoit Steiner Ilya Sutskever Kunal Talwar Paul Tucker Vincent Vanhoucke Vijay Vasudevan Fernanda Vi\u00e9gas Oriol Vinyals Pete Warden Martin Wattenberg Martin Wicke Yuan Yu and Xiaoqiang Zheng. 2015. TensorFlow: Large-Scale Machine Learning on Heterogeneous Systems. https:\/\/www.tensorflow.org\/ Software available from tensorflow.org."},{"key":"e_1_3_2_1_2_1","volume-title":"ONNX: Open Neural Network Exchange. https:\/\/github.com\/onnx\/onnx.","author":"Bai Junjie","year":"2019","unstructured":"Junjie Bai, Fang Lu, Ke Zhang, et al. 2019. ONNX: Open Neural Network Exchange. https:\/\/github.com\/onnx\/onnx."},{"key":"e_1_3_2_1_3_1","doi-asserted-by":"publisher","DOI":"10.1145\/3213846.3213872"},{"key":"e_1_3_2_1_4_1","unstructured":"Fran\u00e7ois Chollet et al. 2015. Keras. https:\/\/keras.io."},{"key":"e_1_3_2_1_5_1","doi-asserted-by":"publisher","DOI":"10.5555\/3103620.3103631"},{"key":"e_1_3_2_1_6_1","doi-asserted-by":"publisher","DOI":"10.1145\/3236024.3236057"},{"key":"e_1_3_2_1_7_1","doi-asserted-by":"publisher","DOI":"10.1145\/3213846.3213858"},{"key":"e_1_3_2_1_8_1","volume-title":"Uber Finds Deadly Accident Likely Caused by Software Set to Ignore Objects on Road. The information","author":"Efrati Amir","year":"2018","unstructured":"Amir Efrati. 2018. Uber Finds Deadly Accident Likely Caused by Software Set to Ignore Objects on Road. The information (2018)."},{"key":"e_1_3_2_1_9_1","doi-asserted-by":"crossref","unstructured":"Simos Gerasimou Hasan Ferit-Eniser Alper Sen and Alper \u00c7akan. 2020. Importance-Driven Deep Learning System Testing. In ICSE.","DOI":"10.1145\/3377811.3380391"},{"key":"e_1_3_2_1_10_1","volume-title":"Proceedings of the ACM SIGPLAN conference on Programming language design and implementation. 206--215","author":"Godefroid P.","unstructured":"P. Godefroid, A. Kiezun, and M. Y. Levin. 2008. Grammar-based Whitebox Fuzzing. In Proceedings of the ACM SIGPLAN conference on Programming language design and implementation. 206--215."},{"key":"e_1_3_2_1_11_1","unstructured":"Google. 2021. OSS-Fuzz. https:\/\/github.com\/google\/oss-fuzz"},{"key":"e_1_3_2_1_12_1","doi-asserted-by":"publisher","DOI":"10.1109\/ISSRE.2014.40"},{"key":"e_1_3_2_1_13_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.jcss.2009.05.008"},{"key":"e_1_3_2_1_14_1","doi-asserted-by":"publisher","DOI":"10.1145\/3324884.3416571"},{"key":"e_1_3_2_1_15_1","volume-title":"proceedings of the 17th international conference on data engineering. Citeseer, 215--224","author":"Han Jiawei","year":"2001","unstructured":"Jiawei Han, Jian Pei, Behzad Mortazavi-Asl, Helen Pinto, Qiming Chen, Umeshwar Dayal, and Meichun Hsu. 2001. Prefixspan: Mining sequential patterns efficiently by prefix-projected pattern growth. In proceedings of the 17th international conference on data engineering. Citeseer, 215--224."},{"key":"e_1_3_2_1_16_1","doi-asserted-by":"publisher","DOI":"10.1145\/3341301.3359630"},{"key":"e_1_3_2_1_17_1","doi-asserted-by":"publisher","DOI":"10.1145\/2345156.2254075"},{"key":"e_1_3_2_1_18_1","unstructured":"Keras. 2019. Keras 2.3.0: This is also the last major release of multi-backend Keras. https:\/\/github.com\/keras-team\/keras\/releases\/tag\/2.3.0."},{"key":"e_1_3_2_1_19_1","volume-title":"34th European Conference on Object-Oriented Programming (ECOOP","author":"Lagouvardos Sifis","year":"2020","unstructured":"Sifis Lagouvardos, Julian Dolby, Neville Grech, Anastasios Antoniadis, and Yannis Smaragdakis. 2020. Static analysis of shape in TensorFlow programs. In 34th European Conference on Object-Oriented Programming (ECOOP 2020). Schloss Dagstuhl-Leibniz-Zentrum f\u00fcr Informatik."},{"key":"e_1_3_2_1_20_1","doi-asserted-by":"publisher","DOI":"10.1145\/2594291.2594334"},{"key":"e_1_3_2_1_21_1","doi-asserted-by":"publisher","DOI":"10.1145\/2814270.2814319"},{"key":"e_1_3_2_1_22_1","doi-asserted-by":"publisher","DOI":"10.1145\/3338906.3338930"},{"key":"e_1_3_2_1_23_1","doi-asserted-by":"publisher","DOI":"10.1109\/ISSRE.2019.00018"},{"key":"e_1_3_2_1_24_1","doi-asserted-by":"publisher","DOI":"10.1145\/3368089.3417051"},{"key":"e_1_3_2_1_25_1","unstructured":"LLVM. 2021. libFuzzer - a library for coverage-guided fuzz testing. http:\/\/llvm.org\/docs\/LibFuzzer.html"},{"key":"e_1_3_2_1_26_1","doi-asserted-by":"crossref","unstructured":"Lei Ma Felix Juefei-Xu Fuyuan Zhang Jiyuan Sun Minhui Xue Bo Li Chunyang Chen Ting Su Li Li Yang Liu Jianjun Zhao and Yadong Wang. 2018. DeepGauge: Multi-Granularity Testing Criteria for Deep Learning Systems. In ASE.","DOI":"10.1145\/3238147.3238202"},{"key":"e_1_3_2_1_27_1","volume-title":"Proceedings of the 22nd IEEE\/ACM International Conference on Automated Software Engineering. 134--143","author":"Majumda R.","unstructured":"R. Majumda and R. Xu. 2007. Directed Test Generation Using Symbolic Grammars. In Proceedings of the 22nd IEEE\/ACM International Conference on Automated Software Engineering. 134--143."},{"key":"e_1_3_2_1_28_1","doi-asserted-by":"publisher","DOI":"10.1109\/ASE.2019.00078"},{"key":"e_1_3_2_1_29_1","volume-title":"International Conference on Machine Learning. PMLR, 4901--4911","author":"Odena Augustus","year":"2019","unstructured":"Augustus Odena, Catherine Olsson, David Andersen, and Ian Goodfellow. 2019. Tensorfuzz: Debugging neural networks with coverage-guided fuzzing. In International Conference on Machine Learning. PMLR, 4901--4911."},{"key":"e_1_3_2_1_30_1","volume-title":"Companion to the 22nd ACM SIGPLAN conference on Object-oriented programming systems and applications companion. 815--816.","author":"Pacheco Carlos","unstructured":"Carlos Pacheco and Michael D Ernst. 2007. Randoop: feedback-directed random testing for Java. In Companion to the 22nd ACM SIGPLAN conference on Object-oriented programming systems and applications companion. 815--816."},{"key":"e_1_3_2_1_31_1","doi-asserted-by":"publisher","DOI":"10.1109\/ICSE.2019.00107"},{"key":"e_1_3_2_1_32_1","doi-asserted-by":"publisher","DOI":"10.1145\/3324884.3416545"},{"key":"e_1_3_2_1_33_1","doi-asserted-by":"publisher","DOI":"10.1145\/2939672.2945397"},{"key":"e_1_3_2_1_34_1","volume-title":"Workshops at the Thirty-Second AAAI Conference on Artificial Intelligence.","author":"Srisakaokul Siwakorn","year":"2018","unstructured":"Siwakorn Srisakaokul, Zhengkai Wu, Angello Astorga, Oreoluwa Alebiosu, and Tao Xie. 2018. Multiple-implementation testing of supervised learning software. In Workshops at the Thirty-Second AAAI Conference on Artificial Intelligence."},{"key":"e_1_3_2_1_35_1","doi-asserted-by":"publisher","DOI":"10.1145\/2983990.2984038"},{"key":"e_1_3_2_1_36_1","unstructured":"Youcheng Sun Min Wu Wenjie Ruan Xiaowei Huang Marta Kwiatkowska and Daniel Kroening. 2018. Concolic Testing for Deep Neural Networks. In ASE."},{"key":"e_1_3_2_1_37_1","doi-asserted-by":"publisher","DOI":"10.1145\/3180155.3180220"},{"key":"e_1_3_2_1_38_1","doi-asserted-by":"crossref","unstructured":"Yuchi Tian Ziyuan Zhong Vicente Ordonez Gail Kaiser and Baishakhi Ray. 2020. Testing DNN Image Classifier for Confusion & Bias Errors. In ICSE.","DOI":"10.1145\/3377811.3380400"},{"key":"e_1_3_2_1_39_1","doi-asserted-by":"publisher","DOI":"10.1145\/3395363.3397380"},{"key":"e_1_3_2_1_40_1","doi-asserted-by":"publisher","DOI":"10.1145\/3377811.3380379"},{"key":"e_1_3_2_1_41_1","volume-title":"RIFF: Reduced Instruction Footprint for Coverage-Guided Fuzzing. In 2021 USENIX Annual Technical Conference (USENIX ATC 21)","author":"Wang Mingzhe","year":"2021","unstructured":"Mingzhe Wang, Jie Liang, Chijin Zhou, Yu Jiang, Rui Wang, Chengnian Sun, and Jiaguang Sun. 2021. RIFF: Reduced Instruction Footprint for Coverage-Guided Fuzzing. In 2021 USENIX Annual Technical Conference (USENIX ATC 21). 147--159."},{"key":"e_1_3_2_1_42_1","doi-asserted-by":"publisher","DOI":"10.1145\/3368089.3409761"},{"key":"e_1_3_2_1_43_1","volume-title":"Lin Tan, Xiangyu Zhang, and Michael Godfrey.","author":"Xie Danning","year":"2021","unstructured":"Danning Xie, Yitong Li, Mijung Kim, Hung Viet Pham, Lin Tan, Xiangyu Zhang, and Michael Godfrey. 2021. Leveraging Documentation to Test Deep Learning Library Functions. (2021). arXiv:cs.SE\/2109.01002"},{"key":"e_1_3_2_1_44_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.jss.2010.11.920"},{"key":"e_1_3_2_1_45_1","doi-asserted-by":"publisher","DOI":"10.1145\/3293882.3330579"},{"key":"e_1_3_2_1_46_1","doi-asserted-by":"crossref","unstructured":"Mengshi Zhang Yuqun Zhang Lingming Zhang Cong Liu and Sarfraz Khurshid. 2018. DeepRoad: GAN-Based Metamorphic Testing and Input Validation Framework for Autonomous Driving Systems. In ASE.","DOI":"10.1145\/3238147.3238187"},{"key":"e_1_3_2_1_47_1","doi-asserted-by":"publisher","DOI":"10.1145\/3460319.3464843"},{"key":"e_1_3_2_1_48_1","doi-asserted-by":"publisher","DOI":"10.1109\/ICSE-Companion.2019.00131"},{"key":"e_1_3_2_1_49_1","doi-asserted-by":"crossref","unstructured":"Husheng Zhou Wei Li Zelun Kong Junfeng Guo Yuqun Zhang Lingming Zhang Bei Yu and Cong Liu. 2020. DeepBillboard: Systematic Physical-World Testing of Autonomous Driving Systems. In ICSE.","DOI":"10.1145\/3377811.3380422"}],"event":{"name":"ICSE '22: 44th International Conference on Software Engineering","location":"Pittsburgh Pennsylvania","acronym":"ICSE '22","sponsor":["SIGSOFT ACM Special Interest Group on Software Engineering","IEEE CS"]},"container-title":["Proceedings of the 44th International Conference on Software Engineering"],"original-title":[],"link":[{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3510003.3510165","content-type":"unspecified","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/dl.acm.org\/doi\/pdf\/10.1145\/3510003.3510165","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,6,17]],"date-time":"2025-06-17T18:10:25Z","timestamp":1750183825000},"score":1,"resource":{"primary":{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3510003.3510165"}},"subtitle":["creating equivalent graphs to test deep learning libraries"],"short-title":[],"issued":{"date-parts":[[2022,5,21]]},"references-count":49,"alternative-id":["10.1145\/3510003.3510165","10.1145\/3510003"],"URL":"https:\/\/doi.org\/10.1145\/3510003.3510165","relation":{},"subject":[],"published":{"date-parts":[[2022,5,21]]},"assertion":[{"value":"2022-07-05","order":2,"name":"published","label":"Published","group":{"name":"publication_history","label":"Publication History"}}]}}