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View all- Rajabli NFlammini FNardone RVittorini V(2021)Software Verification and Validation of Safe Autonomous Cars: A Systematic Literature ReviewIEEE Access10.1109/ACCESS.2020.30480479(4797-4819)Online publication date: 2021
Saving virtual testing time for CPS by analyzing code coverage on the example of a lane-following algorithm
Pages 7 - 10
Abstract
Self-driving cars are announced to be available at the end of this decade. For testing these highly complex systems, experiments on proving grounds and long-term validations on public roads need to be complemented by extensive tests in virtual environments. However, efficient planning of these virtual tests is essential to focus only on those tests, which are affected by changes to the software during the development. In previous work, meta-data from the development process of a real-scale self-driving car was analyzed to develop an approach, which relates changes in the source code to scenarios for virtual testing environments. In this article, results from applying that approach during the development of a lane-following algorithm for a self-driving miniature car are presented. With the help of the approach, 11% of the tests in the virtual environment could be omitted safely to save virtual testing time.
References
[1]
C. Basarke, C. Berger, K. Cornelsen, M. Doering, J. Effertz, K. Homeier, C. Lipski, T. Nothdurft, and J. M. Wille. Team CarOLO. Technical report, Technische Universität Braunschweig, Braunschweig, Germany, June 2007.
[2]
C. Basarke, C. Berger, K. Homeier, and B. Rumpe. Design and Quality Assurance of Intelligent Vehicle Functions in the "Virtual Vehicle". Proceedings of 11. Automobiltechnische Konferenz - Virtual Vehicle Creation, Stuttgart, 9:131--142, June 2007.
[3]
C. Berger. From Autonomous Vehicles to Safer Cars: Selected Challenges for the Software Engineering. In F. Ortmeier and P. Daniel, editors, Proceedings of the SAFECOMP 2012 Workshops, LNCS 7613, pages 180--189, Magdeburg, Germany, Sept. 2012. Springer-Verlag Berlin Heidelberg.
[4]
C. Berger. Improving Scenario Selection for Simulations by Run-Time Control-Flow Analysis. In A. Abhari, A. G. Bruzzone, P. Kropf, F. Longo, and A. O. Solis, editors, Proceedings of the 2013 Summer Computer Simulation Conference, pages 94--102, Toronto, ON, Canada, July 2013. Simulation Councils, Inc.
[5]
C. Berger, M. Chaudron, R. Heldal, O. Landsiedel, and E. M. Schiller. Model-based, Composable Simulation for the Development of Autonomous Miniature Vehicles. In Proceedings of the SCS/IEEE Symposium on Theory of Modeling and Simulation, San Diego, CA, USA, Apr. 2013.
[6]
C. Berger and B. Rumpe. Autonomous Driving - 5 Years after the Urban Challenge: The Anticipatory Vehicle Cyber-Physical System. In U. Goltz, M. Magnor, H.-J. Appelrath, H. K. Matthies, W.-T. Balke, and L. Wolf, editors, Proceedings of the INFORMATIK 2012, pages 789--798, Braunschweig, Germany, Sept. 2012.
[7]
M. Buehler, K. Iagnemma, and S. Singh, editors. The 2005 DARPA Grand Challenge: The Great Robot Race. Springer Verlag, Berlin Heidelberg, 2007.
[8]
E. Engström, P. Runeson, and M. Skoglund. A systematic review on regression test selection techniques. Information and Software Technology, 52(1):14--30, Jan. 2010.
[9]
J. Felez, J. Maroto, J. M. Cabanellas, and J. M. Mera. A full-scale simulation model to reproduce urban traffic in real conditions in driving simulators. Simulation, (April), Apr. 2013.
[10]
High Tech Automotive Systems. Grand Cooperative Driving Challenge, Jan. 2011.
[11]
J. Hirsch. Self-driving cars inch closer to mainstream availability, Oct. 2013.
[12]
M. Pahlavan, M. Papatriantafilou, and E. M. Schiller. Gulliver: A Test-bed for Developing, Demonstrating and Prototyping Vehicular Systems. In Proceedings of the MobiWac' 11, pages 1--8, Miami, Florida, Oct. 2011.
[13]
P. Runeson and M. Höst. Guidelines for conducting and reporting case study research in software engineering. Empirical Software Engineering, 14(2):131--164, Dec. 2008.
[14]
F. Shull, J. Singer, and D. I. K. Sjø berg, editors. Guide to Advanced Empirical Software Engineering. Springer London, London, 2008.
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- Saving virtual testing time for CPS by analyzing code coverage on the example of a lane-following algorithm
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Published: 14 April 2014
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View all- Rajabli NFlammini FNardone RVittorini V(2021)Software Verification and Validation of Safe Autonomous Cars: A Systematic Literature ReviewIEEE Access10.1109/ACCESS.2020.30480479(4797-4819)Online publication date: 2021
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