深入了解SBST 2021工具竞赛:使用多目标搜索的ADAS测试

2021 IEEE/ACM 14th International Workshop on Search-Based Software Testing (SBST) Pub Date : 2021-05-01 DOI:10.1109/SBST52555.2021.00018

M. H. Moghadam, Markus Borg, S. J. Mousavirad

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引用次数: 9

摘要

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。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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

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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来源期刊

2021 IEEE/ACM 14th International Workshop on Search-Based Software Testing (SBST)

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