Authors:
Thaise Yano
1
;
Eliane Martins
1
and
Fabiano L. de Sousa
2
Affiliations:
1
State University of Campinas, Brazil
;
2
National Institute for Space Research, Brazil
Keyword(s):
Robustness testing, Protocol testing, Evolutionary testing.
Related
Ontology
Subjects/Areas/Topics:
Artificial Intelligence
;
Computational Intelligence
;
Evolutionary Computing
;
Genetic Algorithms
;
Informatics in Control, Automation and Robotics
;
Intelligent Control Systems and Optimization
;
Soft Computing
Abstract:
In this paper we present an evolutionary testing approach to automatically generate robustness test sequences to test a communication protocol, modeled as an extended finite state machine (EFSM). The model represents the normal situation as well as in presence of faults, which makes the model too large to be treated by conventional test case generation approaches, because of the risk of combinatorial explosion. To cope with this problem, we use a testing approach based on test purposes. To search sequences that satisfy the test purposes, we use two evolutionary algorithms: the Generalized Extremal Optimization (GEO) and a Genetic Algorithm (GA). For the moment, only the control flow part of the model is taken into account. Results show that the approach is viable and potentially useful to consider data flow part of complex EFSM models.