Improving the Confidence in Measurement-Based Timing Analysis

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. The most challenging part of MBTA is test data generation. Choosing an adequate set of test vectors determines safety and efficiency of the overall analysis. So far, there are no feasible criteria that determine how well the worst-case temporal behavior of program parts is covered by a given test-suite. In this paper we introduce a relative safety metric that compares test suites with respect to how well the observed worst-case behavior of program parts is exercised. Using this metric, we empirically show that common code coverage criteria from the domain of functional testing can produce unsafe WCET estimates in the context of MBTA for systems with a processor like the TriCore 1796. Further, we use the relative safety metric to examine coverage criteria that require all feasible pairs of, e.g., basic blocks to be exercised in combination. These are shown to be superior to code coverage criteria from the domain of functional testing, but there is still a chance that an unsafe WCET estimate is derived by MBTA in our experimental setup. Based on the outcomes of our evaluation we introduce and examine Balanced Path Generation, an input data generation technique that combines the advantages of all evaluated coverage criteria and random input data generation.