Testing vision-based control systems using learnable evolutionary algorithms

Vision-based control systems are key enablers of many autonomous vehicular systems, including self-driving cars. Testing such systems is complicated by complex and multidimensional input spaces. We propose an automated testing algorithm that builds on learnable evolutionary algorithms. These algorit...

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Bibliographic Details
Published in:2018 IEEE/ACM 40th International Conference on Software Engineering (ICSE) pp. 1016 - 1026
Main Authors: Abdessalem, Raja Ben, Nejati, Shiva, Briand, Lionel C., Stifter, Thomas
Format: Conference Proceeding
Language:English
Published: New York, NY, USA ACM 27.05.2018
Series:ACM Conferences
Subjects:
Automotive engineering
Automotive Software Systems
Classification algorithms
Control systems
Decision trees
Evolutionary algorithms
Evolutionary computation
Roads
Search-based Software Engineering
Software and its engineering > Software creation and management > Search-based software engineering
Software and its engineering > Software creation and management > Software verification and validation > Software defect analysis > Software testing and debugging
Software Testing
Testing
automotive software systems
software testing
evolutionary algorithms
search-based software engineering
ISBN:9781450356381, 1450356389
ISSN:1558-1225
Online Access:Get full text
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