Safety-Critical Software Development in C++

Kastner, Daniel L.; Cullmann, Christoph; Gebhard, Gernot; Hahn, Sebastian; Karos, Thomas; Mauborgne, Laurent; Wilhelm, Stephan; Ferdinand, Christian

doi:10.1007/978-3-030-55583-2_7

Cited by 4 publications

(3 citation statements)

References 5 publications

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“…Automotive software in open source is now developed mostly in Python, replacing MATLAB as reported in prior studies (see Table 12 in [2]). A similar trend of C++ domination replacing C or Ada for safety critical software development [20] is seen. Our advice to the readers interested in venturing into automotive software is to consider these findings while choosing programming languages.…”

Section: Practicesupporting

confidence: 55%

“…Organizations generally prefer (based on repository count) Python (82), C++ (37), C (16), MATLAB (10), and Jupyter Notebook (7) for their projects. Notably, users also prefer the same languages but in slightly different order: Python (209), C++ (61), Jupyter Notebook (26), MATLAB (20), and C (17).…”

Section: Resultsmentioning

confidence: 99%

“…The distribution of programming languages across projects shows a shift from MATLAB as preferred language of development [2] to Python. Likewise, traditionally most safety critical software were developed in C or Ada which has now shifted to C++ in GitHub [20].…”

Section: Resultsmentioning

confidence: 99%

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Painting the Landscape of Automotive Software in GitHub

Kochanthara¹,

Dajsuren²,

Cleophas³

et al. 2022

Preprint

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The automotive industry has transitioned from being an electromechanical 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 a 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 span of 12 years from 2010 until 2021. These projects range from vehicle dynamics-related software; firmware and drivers for sensors like LiDAR and camera; algorithms for perception and motion control; to complete operating systems integrating the above. Developments in the field are spearheaded by industry and academia alike, with one in three actively developed automotive software repositories owned by an organization. We observe shifts along multiple dimensions, including preferred language from MATLAB to Python and prevalence of perception and decision-related software over traditional automotive software. This study witnesses open source automotive software boom in its infancy with many implications for future research and practice.

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Section: Practicesupporting

confidence: 55%