Title
Successive Refinement of Models for Model-Based Testing to Increase System Test Effectiveness
Abstract
Model-based testing is used for automatically generating test cases based on models of the system under test. The effectiveness of tests depends on the contents of these models. Therefore, we introduce a novel three-step model refinement approach. We represent test models in the form of Markov chains. First, we update state transition probabilities in these models based on usage profile. Second, we perform an update based on fault likelihood that is estimated with static code analysis. Our third update is based on error likelihood that is estimated with dynamic analysis. We generate and execute test cases after each refinement. We applied our approach for model-based testing of a Smart TV system and new faults were revealed after each refinement.
Year
DOI
Venue
2016
10.1109/ICSTW.2016.10
2016 IEEE Ninth International Conference on Software Testing, Verification and Validation Workshops (ICSTW)
Keywords
Field
DocType
model-based testing,model refinement,statistical usage testing,risk-based testing,industrial case study,software test automation
Static program analysis,System under test,Markov process,Risk-based testing,System testing,Computer science,Simulation,Markov chain,Algorithm,Model-based testing,Test case
Conference
ISSN
ISBN
Citations 
2159-4848
978-1-5090-3675-2
6
PageRank 
References 
Authors
0.44
9
3
Name
Order
Citations
PageRank
Ceren Sahin Gebizli1224.56
Hasan Sözer2101.87
Ali Ozer Ercan3616.90