Model-based testing and some steps towards test-based modelling
conference paper
Model-based testing is one of the promising technologies to increase the efficiency and effectiveness of software testing. In modelbased testing, a model specifies the required behaviour of a system, and test cases are algorithmically generated from this model. Obtaining a valid model, however, is often difficult if the system is complex, contains legacy or third-party components, or if documentation is incomplete.
Test-based modelling, also called automata learning, turns model-based testing around: it aims at automatically generating a model from test observations. This paper first gives an overview of formal, model-based testing in general, and of model-based testing for labelled transition system models in particular. Then the practice of model-based testing, the difficulty of obtaining models, and the role of learning are discussed. It is shown that model-based testing and learning are strongly related, and that learning can be fully expressed in the concepts of model-based testing. In particular, test coverage in model-based testing and precision of learned models turn out to be two sides of the same coin.
Test-based modelling, also called automata learning, turns model-based testing around: it aims at automatically generating a model from test observations. This paper first gives an overview of formal, model-based testing in general, and of model-based testing for labelled transition system models in particular. Then the practice of model-based testing, the difficulty of obtaining models, and the role of learning are discussed. It is shown that model-based testing and learning are strongly related, and that learning can be fully expressed in the concepts of model-based testing. In particular, test coverage in model-based testing and precision of learned models turn out to be two sides of the same coin.
TNO Identifier
954276
ISSN
03029743
ISBN
9783642214
Publisher
Springer
Source title
Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 11th International School on Formal Methods for the Design of Computer, Communication and Software Systems, SFM 2011, 13 June 2011 through 18 June 2011
Pages
297-326
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