Analysis of the Impacts of Overestimation Sources on the Accuracy of Worst Case Timing Analysis

• Authors: Sung-Kwan Kim;Sang Lyul Min;Rhan Ha
• Venue: RTSS '99 Proceedings of the 20th IEEE Real-Time Systems Symposium
• Year: 1999

To predict the worst case execution time (WCET) of real-time tasks, we should consider various factors (e.g., caching, pipelining, and infeasible paths) that affect the accuracy of the prediction. However, some of them are inherently difficult to analyze statically, and thus may give rise to significant overestimation in WCET prediction. Therefore, for more accurate WCET prediction, we need to identify such overestimation sources and analyze how much each of them can make overestimation. Then, such analysis results can be used to refine existing timing analysis techniques. In this paper, we do not propose any new timing analysis techniques, but present quantitative analysis results on the impacts of overestimation sources on the accuracy of the worst case timing analysis.For this purpose, we use variance analysis based on a simulation-based methodology to make our analysis independent of any existing techniques. The results show that the dominant factor is pipelining analysis when the cache miss penalty is small and instruction caching analysis when the cache miss penalty is larger than 10 cycles. The results also show that although the impact of data caching analysis is small compared with that of pipelining or instruction caching analysis, if we ignore its effect in the WCET estimation, the WCET can be overestimated up to 275% even when the effects of the other factors are completely analyzed. Finally, the results show that the effects of infeasible paths are largely orthogonal to other analysis features and depend on program characteristics. Also, as for data caching, if infeasible paths are ignored in the WCET estimation, the accuracy of the WCET estimation is degraded significantly (up to 564%).