Abstract
This paper reports our experiences in estimating the worst case execution time (WCET) of automotive software components with evolutionary testing (ET). The concept maximizes the runtime of software components (SWCs) with internal states by evolving the applied test sequences. We show that the use of timing tests is strongly facilitated by the automotive architecture framework AUTOSAR. A problem of the testing concept is the high temporal effort, that comes along with measuring the execution time of a test sequence on the target hardware. An analysis of the evolutionary testability shows, that the high number of input parameters makes it hard to find the maximum execution time. The WCET estimates obtained with genetic algorithms (GAs) are inferior compared with the results of random testing. GAs run into local optima in case of flat execution time profiles, whereas random testing keeps searching globally. Random testing is outperformed by extended GAs which are adaptive to the underlying optimization problem.
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Franz, F. (2008). Experiences with Evolutionary Timing Test of Automotive Software Components. In: Margaria, T., Steffen, B. (eds) Leveraging Applications of Formal Methods, Verification and Validation. ISoLA 2008. Communications in Computer and Information Science, vol 17. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-88479-8_29
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DOI: https://doi.org/10.1007/978-3-540-88479-8_29
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