2011Unpublished venueOpen access

Let's get less optimistic in measurement-based timing analysis

Sven Bünte, Michael Zolda, Raimund Kirner

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Abstract

Measurement-based timing analysis (MBTA) is a hybrid approach that combines execution time measurements with static program analysis techniques to obtain an estimate of the worst-case execution time (WCET) of a program. In order to minimize the chance that the WCET estimate is below the real WCET, the set of representative execution-time measurements has to be selected advisedly. We present an input data generation technique that uses a combination of model checking and genetic algorithms in order to heuristically optimize the set of measurements in terms of safety.

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Measurement-based timing analysis (MBTA) is a hybrid approach that combines execution time measurements with static program analysis techniques to obtain an estimate of the worst-case execution time (WCET) of a program. In order to minimize the chance that the WCET estimate is below the real WCET, the set of representative execution-time measurements has to be selected advisedly. We present an input data generation technique that uses a combination of model checking and genetic algorithms in order to heuristically optimize the set of measurements in terms of safety.

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Available abstract

Measurement-based timing analysis (MBTA) is a hybrid approach that combines execution time measurements with static program analysis techniques to obtain an estimate of the worst-case execution time (WCET) of a program. In order to minimize the chance that the WCET estimate is below the real WCET, the set of representative execution-time measurements has to be selected advisedly. We present an input data generation technique that uses a combination of model checking and genetic algorithms in order to heuristically optimize the set of measurements in terms of safety.

Key concepts: Computer science, Worst-case execution time, Execution time, Set (abstract data type), Static timing analysis, Static analysis, Model checking, Program analysis

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