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ECSA 2020
Mon 14 - Fri 18 September 2020 L'Aquila, Italy

As the automotive industry focuses its attention more and more towards the software functionality of vehicles, techniques to deliver new software value at a fast pace are needed. Continuous Experimentation, a practice coming from the web-based systems world, is one of such techniques. It enables researchers and developers to use real-world data to verify their hypothesis and steer the software evolution based on performances and user preferences, reducing the reliance on simulations and guesswork. Several challenges prevent the verbatim adoption of this practice on automotive cyber-physical systems, e.g., safety concerns and computational resources limitations; nonetheless, the automotive field is starting to take interest in this technique. This work aims at demonstrating and evaluating a prototypical Continuous Experimentation infrastructure, implemented on a distributed computational system housed in a commercial truck tractor that is used in daily operations by a logistic company on public roads. The system comprises computing units and sensors, and software deployment and data retrieval are only possible remotely via a mobile data connection due to the commercial interests of the logistics company. This study shows that the proposed experimentation process resulted in the development team being able to base software development choices on the real-world data collected during the experimental procedure. Additionally, a set of previously identified design criteria to enable Continuous Experimentation on automotive systems was discussed and their validity confirmed in light of the presented work.

Fri 18 Sep

Displayed time zone: Amsterdam, Berlin, Bern, Rome, Stockholm, Vienna change

14:30 - 15:10
S12: ApplicationsGender Diversity in SA / Research Papers at ECSA 2020 Teams Channel
Chair(s): Matthias Galster University of Canterbury, Elisa Yumi Nakagawa University of São Paulo

Virtualization support: Roberta Capuano

Continuous Experimentation for Automotive Software on the Example of a Heavy Commercial Vehicle in Daily OperationBest paper candidateResearch Track
Research Papers
Federico Giaimo Chalmers University of Technology, Christian Berger University of Gothenburg
Mining Gender Bias: A Preliminary Study on Implicit Biases and Gender Identity in the Department of Computer Science at the Technical University of MunichGender-Diversity
Gender Diversity in SA
Ana Petrovska Technical University of Munich, Germany, Patricia Goldberg Technical University of Munich, Anne Brüggemann-Klein Brüggemann-Klein Technical University of Munich, Anne Nyokabi Siemens AG