面向自动驾驶系统调试的系统性映射研究
A Systematic Mapping Study on the Debugging of Autonomous Driving Systems
AI总结：
本研究系统性地分析了自动驾驶系统调试方法，揭示了现有技术现状及未来研究方向。
摘要：
随着自动驾驶系统（ADS）向商业化部署迈进，确保其安全性和可靠性越来越受到关注。尽管已有大量研究关注测试方法以检测ADS中的故障，但对ADS调试的关注却非常有限。调试是测试失败后定位并修复系统中故障的关键过程，以维持其安全性和可靠性。本系统性映射研究（SMS）旨在提供当前ADS调试现状的详细概述，突出现有方法并识别研究中的空白。该研究还提出了未来工作的方向以及该领域问题定义和术语的标准。我们的发现揭示了多种ADS调试方法，并突显了当前碎片化但充满希望的现状。
英文摘要：
As Autonomous Driving Systems (ADS) progress towards commercial deployment, there is an increasing focus on ensuring their safety and reliability. While considerable research has been conducted on testing methods for detecting faults in ADS, very little attention has been paid to debugging in ADS. Debugging is an essential process that follows test failures to localise and repair the faults in the systems to maintain their safety and reliability. This Systematic Mapping Study (SMS) aims to provide a detailed overview of the current landscape of ADS debugging, highlighting existing approaches and identifying gaps in research. The study also proposes directions for future work and standards for problem definition and terminology in the field. Our findings reveal various methods for ADS debugging and highlight the current fragmented yet promising landscape.
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