Verification Of Timing Constraints Research Articles

A Comparison of Static Analysis and Evolutionary Testing for the Verification of Timing Constraints

This paper contrasts two methods to verify timing constraints of real-time applications. The method of static analysis predicts the worst-case and best-case execution times of a tasks code by analy...

Verifying Timing Constraints of Real-Time Systems by Means of Evolutionary Testing

Many industrial products are based on the use of embedded computer systems. Usually, these systems have to fulfil real-time requirements, and correct system functionality depends on their logical correctness as well as on their temporal correctness. In order to verify the temporal behavior of real-time systems, previous scientific work has, to a large extent, concentrated on static analysis techniques. Although these techniques offer the possibilty of providing safe estimates of temporal behavior for certain cases, there are a number of cases in practice for which static analysis can not be easily applied. Furthermore, no commercial tools for timing analysis of real-world programs are available. Therefore, the developed systems have to be thoroughly tested in order to detect existing deficiencies in temporal behavior, as well as to strengthen the confidence in temporal correctness. An investigation of existing test methods shows that they mostly concentrate on testing for logical correctness. They are not specialised in the examination of temporal correctness which is also essential to real-time systems. For this reason, existing test procedures must be supplemented by new methods which concentrate on determining whether the system violates its specified timing constraints. Normally, a violation means that outputs are produced too early, or their computation takes too long. The task of the tester therefore is to find the input situations with the longest or shortest execution times, in order to check whether they produce a temporal error. If the search for such inputs is interpreted as a problem of optimization, evolutionary computation can be used to automatically find the inputs with the longest or shortest execution times. This automatic search for accurate test data by means of evolutionary computation is called evolutionary testing. Experiments using evolutionary testing on a number of programs with up to 1511 LOC and 5000 input parameters have successfully identified new longer and shorter execution times than had been found using other testing techniques. Evolutionary testing, therefore, seems to be a promising approach for the verification of timing constraints. A combination of evolutionary testing and systematic testing offers further opportunities to improve the test quality, and could lead to an effective test strategy for real-time systems.