Deeper at the SBST 2021 Tool Competition: ADAS Testing Using Multi-Objective Search

M. H. Moghadam, Markus Borg, S. J. Mousavirad
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引用次数: 9

Abstract

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.
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深入了解SBST 2021工具竞赛:使用多目标搜索的ADAS测试
deep是一个基于模拟的测试生成器,它使用一个进化过程,即一个基于档案的NSGA-II,增强了一个高质量的种群种子,用于生成测试用例来测试一个基于深度神经网络的车道保持系统。本文简要介绍了Deeper,并总结了Deeper参加SBST 2021网络物理系统(CPS)测试竞赛的结果。
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Evosuite at the SBST 2021 Tool Competition Augmenting Search-based Techniques with Static Synthesis-based Input Generation Beacon: Automated Test Generation for Stack-Trace Reproduction using Genetic Algorithms Frenetic at the SBST 2021 Tool Competition Deeper at the SBST 2021 Tool Competition: ADAS Testing Using Multi-Objective Search
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