一句话：探索无人机飞行日志中软件缺陷引发异常的代码级模式，为诊断与定位工具提供依据。
无人机日益普及，但与许多复杂系统一样容易受到软件缺陷影响，导致系统行为异常并产生不良后果。这类由软件 bug 引发的 UAV 异常常体现在飞行日志中，对保障 UAV 系统质量与安全至关重要。然而，现有研究对软件 bug 导致的 UAV 异常在代码层面的模式关注有限，阻碍了 UAV 系统代码中缺陷诊断与定位工具的开发。本文对此开展探索性调查，聚焦无人机日志异常，尝试揭示其与代码级缺陷模式的关联，从而为理解、诊断和定位 UAV 软件异常提供经验证据，并为后续自动化质量保障工具的设计奠定基础。
Unmanned aerial vehicles (UAVs) are becoming increasingly ubiquitous in our daily lives. However, like many other complex systems, UAVs are susceptible to software bugs that can lead to abnormal system behaviors and undesirable consequences. It is crucial to study such software bug-induced UAV anomalies, which are often manifested in flight logs, to help assure the quality and safety of UAV systems. However, there has been limited research on investigating the code-level patterns of software bug-induced UAV anomalies. This impedes the development of effective tools for diagnosing and localizing bugs within UAV system code.
@inproceedings{paperbot11331,
title = {An Exploratory Investigation of Log Anomalies in Unmanned Aerial Vehicles},
author = {Dinghua Wang and Shuqing Li and Guanping Xiao and Yepang Liu and Yulei Sui and Pinjia He and Michael R. Lyu},
booktitle = {ICSE},
year = {2024},
doi = {10.1145/3597503.3639186}
}