Learning-Based testing for autonomous systems using spatial and temporal requirements
2018 (English)In: MASES 2018 - Proceedings of the 1st International Workshop on Machine Learning and Software Engineering in Symbiosis, co-located with ASE 2018, Association for Computing Machinery, Inc , 2018, p. 6-15Conference paper, Published paper (Refereed)
Abstract [en]
Cooperating cyber-physical systems-of-systems (CO-CPS) such as vehicle platoons, robot teams or drone swarms usually have strict safety requirements on both spatial and temporal behavior. Learning-based testing is a combination of machine learning and model checking that has been successfully used for black-box requirements testing of cyber-physical systems-of-systems. We present an overview of research in progress to apply learning-based testing to evaluate spatio-temporal requirements on autonomous systems-of-systems through modeling and simulation.
Place, publisher, year, edition, pages
Association for Computing Machinery, Inc , 2018. p. 6-15
Keywords [en]
Automotive software, Black-box testing, Learningbased testing, Machine learning, Model-based testing, Requirements testing, Spatio-temporal logic, Artificial intelligence, Cyber Physical System, Embedded systems, Learning systems, Model checking, System of systems, Systems engineering, Autonomous systems, Cyber physical systems (CPSs), Model and simulation, Model based testing, Safety requirements, Spatio temporal, Temporal behavior
National Category
Computer and Information Sciences
Identifiers
URN: urn:nbn:se:kth:diva-247188DOI: 10.1145/3243127.3243129ISI: 1317490800006Scopus ID: 2-s2.0-85055868610ISBN: 9781450359726 (print)OAI: oai:DiVA.org:kth-247188DiVA, id: diva2:1313744
Conference
1st International Workshop on Machine Learning and Software Engineering in Symbiosis, MASES 2018, co-located with ASE 2018 Conference, 3 September 2018
Note
QC 20190506
2019-05-062019-05-062025-11-28Bibliographically approved