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Constraint-Based Techniques for Software Testing

Constraint-Based Techniques for Software Testing

Nikolai Kosmatov
Copyright: © 2010 |Pages: 15
ISBN13: 9781605667584|ISBN10: 1605667587|EISBN13: 9781605667591
DOI: 10.4018/978-1-60566-758-4.ch011
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MLA

Kosmatov, Nikolai. "Constraint-Based Techniques for Software Testing." Artificial Intelligence Applications for Improved Software Engineering Development: New Prospects, edited by Farid Meziane and Sunil Vadera, IGI Global, 2010, pp. 218-232. https://doi.org/10.4018/978-1-60566-758-4.ch011

APA

Kosmatov, N. (2010). Constraint-Based Techniques for Software Testing. In F. Meziane & S. Vadera (Eds.), Artificial Intelligence Applications for Improved Software Engineering Development: New Prospects (pp. 218-232). IGI Global. https://doi.org/10.4018/978-1-60566-758-4.ch011

Chicago

Kosmatov, Nikolai. "Constraint-Based Techniques for Software Testing." In Artificial Intelligence Applications for Improved Software Engineering Development: New Prospects, edited by Farid Meziane and Sunil Vadera, 218-232. Hershey, PA: IGI Global, 2010. https://doi.org/10.4018/978-1-60566-758-4.ch011

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Abstract

In this chapter, the authors discuss some innovative applications of artificial intelligence techniques to software engineering, in particular, to automatic test generation. Automatic testing tools translate the program under test, or its model, and the test criterion, or the test objective, into constraints. Constraint solving allows then to find a solution of the constraint solving problem and to obtain test data. The authors focus on two particular applications: model-based testing as an example of black-box testing, and all-paths test generation for C programs as a white-box testing strategy. Each application is illustrated by a running example showing how constraint-based methods allow to automatically generate test data for each strategy. They also give an overview of the main difficulties of constraint-based software testing and outline some directions for future research.

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