Robustness Testing of Autonomy Software

Casidhe Hutchison, Milda Zizyte, Patrick E. Lanigan, David Guttendorf, Michael D. Wagner, Claire Le Goues, P. Koopman
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引用次数: 52

Abstract

As robotic and autonomy systems become progressively more present in industrial and human-interactive applications, it is increasingly critical for them to behave safely in the presence of unexpected inputs. While robustness testing for traditional software systems is long-studied, robustness testing for autonomy systems is relatively uncharted territory. In our role as engineers, testers, and researchers we have observed that autonomy systems are importantly different from traditional systems, requiring novel approaches to effectively test them. We present Automated Stress Testing for Autonomy Architectures (ASTAA), a system that effectively, automatically robustness tests autonomy systems by building on classic principles, with important innovations to support this new domain. Over five years, we have used ASTAA to test 17 real-world autonomy systems, robots, and robotics-oriented libraries, across commercial and academic applications, discovering hundreds of bugs. We outline the ASTAA approach and analyze more than 150 bugs we found in real systems. We discuss what we discovered about testing autonomy systems, specifically focusing on how doing so differs from and is similar to traditional software robustness testing and other high-level lessons.
自治软件的稳健性测试
随着机器人和自主系统越来越多地出现在工业和人机交互应用中,它们在出现意外输入时的安全行为变得越来越重要。传统软件系统的鲁棒性测试研究已久,而自主系统的鲁棒性测试则是相对未知的领域。在我们作为工程师、测试人员和研究人员的角色中,我们观察到自治系统与传统系统有很大的不同,需要新的方法来有效地测试它们。我们提出自动压力测试自治架构(ASTAA),一个系统,有效地,自动鲁棒性测试自治系统通过建立在经典的原则,重要的创新,以支持这一新的领域。在过去的五年里,我们已经使用ASTAA测试了17个真实世界的自主系统、机器人和面向机器人的库,涵盖了商业和学术应用,发现了数百个bug。我们概述了ASTAA方法,并分析了我们在实际系统中发现的150多个bug。我们讨论了我们在测试自治系统方面的发现,特别关注这样做与传统软件健壮性测试的区别和相似之处,以及其他高级课程。
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