ROBUST: 221 Bugs in the Robot Operating System

Abstract

As robotic systems such as autonomous cars and delivery drones assume greater roles and responsibilities within society, the likelihood and impact of catastrophic software failure within those systems is increased.To aid researchers in the development of new methods to measure and assure the safety and quality of robotics software, we systematically curated a dataset of 221 bugs across 7 popular and diverse software systems implemented via the Robot Operating System (ROS). We produce historically accurate recreations of each of the 221 defective software versions in the form of Docker images, and use a grounded theory approach to examine and categorize their corresponding faults, failures, and fixes. Finally, we reflect on the implications of our findings and outline future research directions for the community.

References in corpus (4)

• Anomaly Detection for a Water Treatment System Using Unsupervised Machine Learning
• BugsInPy: A Database of Existing Bugs in Python Programs to Enable Controlled Testing and Debugging Studies
• Bears: An Extensible Java Bug Benchmark for Automatic Program Repair Studies
• PHYSFRAME: Type Checking Physical Frames of Reference for Robotic Systems