Abstract
Continuous Integration and Delivery (CI/CD) practices have shown several benefits for software development and operations, e.g., faster release cycles and early discovery of defects. For Cyber-Physical System (CPS) development, CI/CD can help achieving required goals, such as high dependability, yet it may be challenging to apply. This paper empirically investigates challenges, barriers, and their mitigation occurring when applying CI/CD practices to develop CPSs in 10 organizations working in 8 different domains. The study has been conducted through semi-structured interviews, by applying an open card sorting procedure together with a member-checking survey within the same organizations, and by validating the results through a further survey involving 55 professional developers. The study reveals several peculiarities in the application of CI/CD to CPSs. These include the need for (i) combining continuous and periodic builds, while balancing the use of Hardware-in-the-Loop (HiL) and simulators; (ii) coping with difficulties in software deployment (iii) accounting for simulators and HiL differing in their behavior; and (vi) combining hardware/software expertise in the development team. Our findings open the road towards recommenders aimed at supporting the setting and evolution of CI/CD pipelines, as well as university curricula requiring interdisciplinarity, such as knowledge about hardware, software, and their interplay.
Original language | English |
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Journal | ACM Transactions on Software Engineering and Methodology |
Publication status | E-pub ahead of print - Oct 2022 |
Funding
H2020 COSMOS (DevOps for Complex Cyber-physical Systems), Project No. 957254-COSMOSKeywords
- Continuous Integration and Delivery
- Cyber-Physical Systems
- empirical software engineering
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Continuous Integration and Delivery practices for Cyber-Physical systems: An interview-based study
Zampetti, F. (Creator), Tamburri, D. A. (Creator), Panichella, S. (Creator), Panichella, A. (Creator), Di Penta, M. (Creator) & Canfora, G. (Creator), TU Delft - 4TU.ResearchData, Oct 2022
DOI: https://zenodo.org/record/6915537
Dataset/Software: Dataset