一句话：对 Paparazzi 无人机框架开展实证研究，提出边界函数五类分类法并动态评估其对 UAV 行为的影响。
本文关注安全关键型无人机（UAV）软件中由开发者注入的运行时范围检查，即边界函数（Bounding Functions, BFs）。作者对广泛使用的开源 UAV 框架 Paparazzi 进行自底向上的实证研究：静态分析所有 BF 实例，提出基于数据类型的 5 类分类法，刻画 BFs 在保障 UAV 系统安全中的角色；动态采用差分方法比较有无 BFs 时的 UAV 行为差异。研究发现 109 个 BF 实例大量用于限制推力、速度和传感器值等安全关键变量。该静态与动态结合的方法揭示了此前鲜有研究的 UAV 安全关键软件设计空间。
Unmanned Aerial Vehicles (UAVs) are an emerging computation platform known for their safety-critical need. In this paper, we conduct an empirical study on a widely used open-source UAV software framework, Paparazzi, with the goal of understanding the safety-critical concerns of UAV software from a bottom-up developer-in-the-field perspective. We set our focus on the use of Bounding Functions (BFs), the runtime checks injected by Paparazzi developers on the range of variables. Through an in-depth analysis on BFs in the Paparazzi autopilot software, we found a large number of them (109 instances) are used to bound safety-critical variables essential to the cyber-physical nature of the UAV, such as its thrust, its speed, and its sensor values. The novel contributions of this study are two fold. First, we take a static approach to classify all BF instances, presenting a novel datatype-based 5-category taxonomy with fine-grained insight on the role of BFs in ensuring the safety of UAV systems. Second, we dynamically evaluate the impact of the BF uses through a differential approach, establishing the UAV behavioral difference with and without BFs. The two-pronged static and dynamic approach together illuminates a rarely studied design space of safety-critical UAV software systems.
DOI 原文 · arXiv · PDF（开放获取） · DBLP
@inproceedings{abs-2102-07020,
title = {Understanding Bounding Functions in Safety-Critical UAV Software},
author = {Xiaozhou Liang and John Henry Burns and Joseph Sanchez and Karthik Dantu and Lukasz Ziarek and Yu David Liu},
booktitle = {ICSE},
year = {2021},
doi = {10.1109/icse43902.2021.00119}
}