Painting the Landscape of Automotive Software in GitHub
Sangeeth Kochanthara, Yanja Dajsuren, Loek Cleophas, Mark van den, Brand

TL;DR
This paper explores the open-source automotive software landscape on GitHub, highlighting its growth, characteristics, and development trends over 12 years, revealing a burgeoning industry with diverse projects and shifting technologies.
Contribution
It provides the first comprehensive analysis of open-source automotive software on GitHub, detailing its characteristics, development styles, and evolving trends from 2010 to 2021.
Findings
Over 600 active projects with 15,000+ contributors.
Shift from MATLAB to Python in programming languages.
Increase in perception and decision-making software.
Abstract
The automotive industry has transitioned from being an electro-mechanical to a software-intensive industry. A current high-end production vehicle contains 100 million+ lines of code surpassing modern airplanes, the Large Hadron Collider, the Android OS, and Facebook's front-end software, in code size by a huge margin. Today, software companies worldwide, including Apple, Google, Huawei, Baidu, and Sony are reportedly working to bring their vehicles to the road. This paper ventures into the automotive software landscape in open source, providing the first glimpse into this multi-disciplinary industry with a long history of closed source development. We paint the landscape of automotive software on GitHub by describing its characteristics and development styles. The landscape is defined by 15,000+ users contributing to ~600 actively-developed automotive software projects created in a…
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Taxonomy
TopicsReal-Time Systems Scheduling · Software Testing and Debugging Techniques · Advanced Software Engineering Methodologies
