Paper Info
Title
Generating Feasible Transition Paths for Testing from an Extended Finite State Machine (EFSM)
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 of a path in order to estimate its feasibility. The proposed fitness metric is evaluated by being used in a genetic algorithm to guide the search for FTPs.
Year
DOI
Venue
2009
10.1109/ICST.2009.29
Denver, CO
Keywords
Field
DocType
generating feasible transition paths,analyzes data flow dependence,extended finite state machine,challenging task,open research problem,novel fitness,test data,feasible transition path,chosen path,appropriate path,proposed fitness metric,suitable path,system testing,data flow analysis,software metrics,hardware,genetic algorithms,data analysis,finite state machines,probability density function,software testing,model based testing,genetic algorithm,data mining,testing,data models,automatic control,automata,information systems
Computer science,System testing,Extended finite-state machine,Algorithm,Finite-state machine,Model-based testing,Test data,Software metric,Genetic algorithm,Data flow diagram
Conference
ISBN
Citations 
PageRank 
978-0-7695-3601-9
47
1.44
References 
Authors
24
3
Name
Order
Citations
PageRank
Abdul Salam Kalaji1862.86
Robert Mark Hierons2862.86
Stephen Swift342731.32