COSMOS – DevOps for Complex Cyber-physical Systems of Systems
Description
Much of the increasing complexity of ICT systems is being driven by the more distributed and heterogeneous nature of these systems, with Cyber Physical Systems accounting for an increasing portion of Software Ecosystems. This basic premise underpins the COSMOS proposal which focuses on blending best practices DevOps solutions with the development processes used in the CPS context: this will enable the CPS world to deliver software more rapidly and result in more secure and trustworthy systems.COSMOS brings together a balanced consortium of big industry, SMEs and academics which will develop enhanced DevOps pipelines which target development of CPS software. These pipelines will integrate more sophisticated validation and verification (V&V) which will comprise of a mix of static code analysis correlated with issues and bug reports, automated test case generation, runtime verification, Hardware in the Loop (HiL) testing and feedback from field devices. Approaches based on Machine Learning, model based testing and search based test generation will be employed. Techniques to prioritize and schedule testing to maximize efficacy of the testing process and to minimize security threats will also be developed. COSMOS will leverage existing prototype technologies developed by the partners supporting enhancing them throughout the project.The COSMOS CPS pipelines will be validated against 5 use cases provided by industrial partners representing healthcare, avionics, automotive, utility and railway sectors. These will act as reference use cases when promoting the technology amongst Open Source and standardization communities. For the former a specific community building activity will be performed to stimulate engagement with Open Source; for the latter, the standards experience of the coordinator and partners will be employed to promote COSMOS technologies within heavily regulated sectors where there is an increasing need for well-defined software V&V solutions.
Key Data
Projectlead
Dr. Sebastiano Panichella
Project team
Bruno ALMEIDA, Dr. Domenico BIANCULLI, Prof. Lionel BRIAND, Christian Birchler, Davide DE PASQUALE, Prof. Massimiliano DI PENTA, Christopher Drexler, Thomas Graf, James HUNT, Scott Hansen, Pedro MALÓ, David Malgiaritta, Sajad Mazraeh Khatiri, Petr Novobílský, Dr. Annibale Panichella, Dr. Fabrizio Pastore, Oliver Remus, Dr. Carolin Rubner, Prof. Dr. Marcela Ruiz, José António SALVADO NEVES, Prof. Jürgen Spielberger, Dr. Andreas ULRICH, Prof. Andy ZAIDMAN
Project status
completed, 01/2021 - 03/2024
Funding partner
Horizon 2020 / Projekt Nr. 957254
Further documents and links
Publications
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Continuous integration and delivery practices for cyber-physical systems : an interview-based study
2024 Zampetti, Fiorella; Tamburri, Damian A.; Panichella, Sebastiano; Panichella, Annibale; Canfora, Gerardo; Penta, Massimiliano Di
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Using code reviews to automatically configure static analysis tools
2024 Zampetti, Fiorella; Mudbhari, Saghan; Arnaoudova, Venera; Di Penta, Massimiliano; Panichella, Sebastiano; Antoniol, Giuliano
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An empirical characterization of software bugs in open-source Cyber–Physical Systems
2024 Zampetti, Fiorella; Kapur, Ritu; Di Penta, Massimiliano; Panichella, Sebastiano
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DeepTC-Enhancer : improving the readability of automatically generated tests
2024 Roy, Devjeet; Zhang, Ziyi; Ma, Maggie; Arnaoudova, Venera; Panichella, Annibale; Panichella, Sebastiano; Gonzalez, Danielle; Mirakhorli, Mehdi
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A decade of code comment quality assessment : a systematic literature review
2024 Rani, Pooja; Blasi, Arianna; Stulova, Nataliia; Panichella, Sebastiano; Gorla, Alessandra; Nierstrasz, Oscar
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SBST tool competition 2021
2024 Panichella, Sebastiano; Gambi, Alessio; Zampetti, Fiorella; Riccio, Vincenzo
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Summary of the 2nd Natural Language-based Software Engineering Workshop (NLBSE 2023)
2024 Panichella, Sebastiano; Di Sorbo, Andrea
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“Won’t we fix this issue?” : qualitative characterization and automated identification of wontfix issues on GitHub
2024 Panichella, Sebastiano; Canfora, Gerardo; Di Sorbo, Andrea
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Test smells 20 years later : detectability, validity, and reliability
2024 Panichella, Annibale; Panichella, Sebastiano; Fraser, Gordon; Sawant, Anand; Hellendoorn, Vincent
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SBFT tool competition 2024 : CPS-UAV test case generation track
2024 Khatiri, Sajad; Saurabh, Prasun; Zimmermann, Timothy; Munasinghe, Charith; Birchler, Christian; Panichella, Sebastiano
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Simulation-based testing of unmanned aerial vehicles with Aerialist
2024 Khatiri, Sajad; Panichella, Sebastiano; Tonella, Paolo
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NLBSE’22 tool competition
2024 Kallis, Rafael; Chaparro, Oscar; Di Sorbo, Andrea; Panichella, Sebastiano
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SBFT tool competition 2024 : Python test case generation track
2024 Erni, Nicolas; Al-Ameen, Mohammed; Birchler, Christian; Derakhshanfar, Pouria; Lukasczyk, Stephan
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Summary of the 1st Natural Language-based Software Engineering Workshop (NLBSE 2022)
2024 Di Sorbo, Andrea; Panichella, Sebastiano
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JUGE : an infrastructure for benchmarking Java unit test generators
2024 Devroey, Xavier; Gambi, Alessio; Galeotti, Juan Pablo; Just, René; Kifetew, Fitsum; Panichella, Annibale; Panichella, Sebastiano
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Diversity-guided search exploration for self-driving cars test generation through Frenet space encoding
2024 Blattner, Timo; Birchler, Christian; Kehrer, Timo; Panichella, Sebastiano
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TEASER : simulation-based CAN bus regression testing for self-driving cars software
2024 Birchler, Christian; Rohrbach, Cyrill; Kim, Hyeongkyun; Gambi, Alessio; Liu, Tianhai; Horneber, Jens; Kehrer, Timo; Panichella, Sebastiano
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Cost-effective simulation-based test selection in self-driving cars software
2024 Birchler, Christian; Ganz, Nicolas; Khatiri, Sajad; Gambi, Alessio; Panichella, Sebastiano
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Cost-effective simulation-based test selection in self-driving cars software with SDC-Scissor
2024 Birchler, Christian; Ganz, Nicolas; Khatiri, Sajad; Gambi, Alessio; Panichella, Sebastiano
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Exposed! : a case study on the vulnerability-proneness of Google Play Apps
2021 Di Sorbo, Andrea; Panichella, Sebastiano