Stress testing real-time systems with genetic algorithms
Reactive real-time systems have to react to external events within time constraints: Triggered tasks must execute within deadlines. The goal of this article is to automate, based on the system task architecture, the derivation of test cases that maximize the chances of critical deadline misses within the system. We refer to that testing activity as stress testing. We have developed a method based on genetic algorithms and implemented it in a tool. Case studies were run and results show that the tool may actually help testers identify test cases that will likely stress the system to such an extent that some tasks may miss deadlines. Copyright 2005 ACM.
|Genetic algorithms, Schedulability theory|
|GECCO 2005 - Genetic and Evolutionary Computation Conference|
|Organisation||Department of Systems and Computer Engineering|
Briand, L.C. (Lionel C.), Labiche, Y, & Shousha, M. (Marwa). (2005). Stress testing real-time systems with genetic algorithms. Presented at the GECCO 2005 - Genetic and Evolutionary Computation Conference. doi:10.1145/1068009.1068183