1 Department of Informatics and Mathematical Modeling, Technical University of Denmark2 Embedded Systems Engineering, Department of Informatics and Mathematical Modeling, Technical University of Denmark3 Embedded Systems Engineering, Department of Applied Mathematics and Computer Science, Technical University of Denmark4 Vienna University of Technology
With the increasing performance demand in real-time systems it becomes more and more relevant to provide feedback to engineers and programmers, but also software development tools, on the performance-relevant code parts of a real-time program. So far, the information provided to programmers through tools was limited to an estimation of the worst-case execution time (WCET) and its associated worst-case execution path (WCEP). However, these metrics only provide partial information. Only those code parts that are on one of the WCEPs are indicated to the programmer. No information is provided for all other code parts. To give an accurate view covering the entire code base, tools in the spirit of standard program profiling tools are required. This work proposes an efficient approach to compute worst-case timing information for all code parts of a program using a complementary metric, called criticality. Every statement of a real-time program is assigned a criticality value, expressing how critical the respective code is with respect to the global WCET. This gives an accurate view to programmers how close the worst execution path passing through a specific part of a real-time program is to the global WCEP. We formally define the criticality metric and investigate some of its properties with respect to dominance in control-flow graphs. Exploiting some of those properties, we propose an algorithm that reduces the overhead of computing the metric to cover complete real-time programs.
Proceedings of the 20th International Conference on Real-time and Network Systems, 2012, p. 101-110
Criticality; Worst-Case Execution Time; Program Profiling; Program Analysis
Main Research Area:
20th International Conference on Real-Time and Network Systems (RTNS 2012)