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Title: Generating feasible transition paths for testing from an extended finite state machine (EFSM)
Authors: Kalaji, AS
Hierons, RM
Swift, S
Keywords: Genetic algorithm
Feasible transition paths (FTPs)
Model-based testing
Automatic test sequence generation
Extended finite state machine (EFSM)
Fitness metric
Path feasibility
EFSM testing
Generating feasible transition paths
Publication Date: 2008
Publisher: IEEE
Citation: 2nd IEEE International Conference on Software Testing Verification and Validation (ICST09), Denver, pp. 230-239, Apr 2009
Abstract: The problem of testing from an extended finite state machine (EFSM) can be expressed in terms of finding suitable paths through the EFSM and then deriving test data to follow the paths. A chosen path may be infeasible and so it is desirable to have methods that can direct the search for appropriate paths through the EFSM towards those that are likely to be feasible. However, generating feasible transition paths (FTPs) for model based testing is a challenging task and is an open research problem. This paper introduces a novel fitness metric that analyzes data flow dependence among the actions and conditions of the transitions in order to estimate the feasibility of a transition path. The proposed fitness metric is evaluated by being used in a genetic algorithm to guide the search for FTPs.
Appears in Collections:Computer Science
Software Engineering (B-SERC)
Dept of Computer Science Research Papers

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