Aiding Test Case Generation in Temporally Constrained State Based Systems Using Genetic Algorithms

Generating test data for formal state based specifications is computationally expensive. This paper improves a framework that addresses this issue by representing the test data generation problem as an optimisation problem and uses heuristics to help generate test cases. The paper considers the temporal constraints and behaviour of a certain class of finite state machines. A short case study of a communication protocol details how the test case generation problem can be presented as a search problem and automated. Genetic algorithms (GAs) and random search are used to generate test data and evaluate the approach. GAs show to outperform random search and seem to scale well as the problem size increases. A very simple fitness function is used that can be used with other evolutionary search techniques and automated test case generation suits.

• Type: Conference
• Year: 2009
• Where: IWANN
• Authors: Karnig Derderian, Mercedes G. Merayo, Robert M. Hierons, Manuel Núñez
• Keywords: Artificial Intelligence, IWANN 2009, Test Case, Test Case Generation, Test Data