|Authors||M. Z. Iqbal, A. Arcuri and L. Briand|
|Title||Automated System Testing of Real-Time Embedded Systems Based on Environment Models|
|Project(s)||The Certus Centre (SFI)|
|Publication Type||Technical reports|
|Year of Publication||2011|
|Publisher||Simula Research Laboratory|
Testing real-time embedded systems (RTES) is in many ways challenging. Thousands of test cases may need to be executed on an industrial RTES. Given the magnitude of testing at the system level, only a fully automated approach can really scale up to test in an industrial context. In this paper we take a blackbox approach and model the RTES environment using the UML/MARTE international modeling standards. Our main motivation is to provide a more practical approach to the model-based testing of RTES. To do so, we enable system testers, who are often not familiar with the system design but know the application domain well-enough, to model the environment, using well-supported modeling standards, to enable test automation. Environment models can support the automation of three tasks: the code generation of an environment simulator to enable testing on the development platform, the selection of test cases, and the evaluation of their expected results (oracles). In this paper, we focus on the second task (test case selection) and investigate four test automation strategies using inputs from UML/MARTE environment models: Random Testing (baseline), Adaptive Random Testing, and Search-Based Testing (using Genetic Algorithms and (1+1) Evolutionary Algorithm). Results on artificial problems and one industrial case study show that Adaptive Random Testing performs best and, more importantly, that our automated testing framework is effective in finding faults.