Leveraging Modular Architecture for Bug Characterization and Analysis in Automated Driving Software

With the rapid advancement of automated driving technology, numerous manufacturers deploy vehicles with auto-driving features. This highlights the importance of ensuring the quality of automated driving software. To achieve this, characterizing bugs in automated driving software is important, as it can facilitate bug detection and bug fixes, thereby ensuring software quality. Automated driving software typically has a modular architecture, where software is divided into multiple modules, each designed for its own functionality for automated driving. This may lead to varying bug characteristics. Additionally, our recent study has shown a correlation between bugs caused by code clones and the functionalities of modules in automated driving software. Hence, we consider the modular structure when analyzing bug characteristics. In this article, we analyze 3,078 bugs from two representative open-source Level-4 automated driving systems, Apollo and Autoware. By analyzing the bug report description, title, and developers’ discussions, we have identified 20 bug symptoms and 17 bug-fixing strategies and analyzed their relationships with the respective modules. Our analysis achieves 12 main findings offering a comprehensive view of bug characteristics in automated driving software. We believe our findings can help developers better understand and manage bugs in automated driving software, thereby improving software quality and reliability.