Deeper at the SBST 2021 Tool Competition: ADAS Testing Using Multi-Objective Search
2021 (engelsk)Inngår i: Proceedings - 2021 IEEE/ACM 14th International Workshop on Search-Based Software Testing, SBST 2021, Institute of Electrical and Electronics Engineers Inc. , 2021, s. 40-41Konferansepaper, Publicerat paper (Fagfellevurdert)
Abstract [en]
Deeper is a simulation-based test generator that uses an evolutionary process, i.e., an archive-based NSGA-II augmented with a quality population seed, for generating test cases to test a deep neural network-based lane-keeping system. This paper presents Deeper briefly and summarizes the results of Deeper's participation in the Cyber-physical systems (CPS) testing competition at SBST 2021.
sted, utgiver, år, opplag, sider
Institute of Electrical and Electronics Engineers Inc. , 2021. s. 40-41
Emneord [en]
advanced driver assistance systems, automotive simulators, cyber-physical systems, deep learning, search-based software testing, Deep neural networks, Embedded systems, Cyber-physical systems (CPS), Evolutionary process, Lane keeping, Multi objective, NSGA-II, Test case, Software testing
HSV kategori
Identifikatorer
URN: urn:nbn:se:mdh:diva-55524DOI: 10.1109/SBST52555.2021.00018ISI: 000803912700012Scopus ID: 2-s2.0-85111105647ISBN: 9781665445719 (tryckt)OAI: oai:DiVA.org:mdh-55524DiVA, id: diva2:1583147
Konferanse
14th IEEE/ACM International Workshop on Search-Based Software Testing, SBST 2021, 22 May 2021 through 30 May 2021
2021-08-052021-08-052022-06-22bibliografisk kontrollert