AuthorsM. Zhang, S. Ali, T. Yue and Malin Hedman
TitleUncertainty-based Test Case Generation and Minimization for Cyber-Physical Systems: A Multi-Objective Search-based Approach
AfilliationSoftware Engineering, The Certus Centre (SFI), Software Engineering
Publication TypeTechnical reports
Year of Publication2016
PublisherSimula Research Laboratory
KeywordsCyber-Physical Systems, Multi-Objective Search, Test Case Generation, Test Case Minimization, Uncertainty

Cyber-Physical Systems (CPSs) typically operate in highly indeterminate conditions that require the development of testing methods that must explicitly consider uncertainty in test design, test generation, and test optimization. Towards this direction, we propose uncertainty-based test case generation and test case minimization strategies that rely on test ready models explicitly specifying subjective uncertainty. We propose two test case generation strategies and four test case minimization strategies based on Uncertainty Theory and multi-objective search. First, we performed an empirical evaluation, where we evaluated the cost-effectiveness and efficiency of the proposed test strategies using one case study from the literature based on various criteria, e.g., mutation score and test execution time. Second, based on the results of the empirical evaluation, we chose the best strategy and tested one real CPS with it. Based on the results of the test case execution on the real CPS, we managed to discover 18 new uncertainties.


This work is supported by U-Test project (Testing Cyber-Physical Systems under Uncertainty).

Citation Key24840