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Automatic Generation of Combinatorial Test Data [electronic resource] / by Jian Zhang, Zhiqiang Zhang, Feifei Ma.

By: Zhang, Jian [author.].
Contributor(s): Zhang, Zhiqiang [author.] | Ma, Feifei [author.] | SpringerLink (Online service).
Material type: materialTypeLabelBookSeries: SpringerBriefs in Computer Science: Publisher: Berlin, Heidelberg : Springer Berlin Heidelberg : Imprint: Springer, 2014Description: XI, 90 p. 31 illus. online resource.Content type: text Media type: computer Carrier type: online resourceISBN: 9783662434291.Subject(s): Computer science | Software engineering | Computer science -- Mathematics | Artificial intelligence | Computer Science | Software Engineering | Math Applications in Computer Science | Artificial Intelligence (incl. Robotics)Additional physical formats: Printed edition:: No titleDDC classification: 005.1 Online resources: Click here to access online
Contents:
Introduction to Combinatorial Testing -- Mathematical Construction Methods -- One Test at a Time -- The IPO Family -- Evolutionary Computation and Metaheuristics -- Evolutionary Computation and Metaheuristics -- Tools and Benchmarks -- Other Related Topics.
In: Springer eBooksSummary: This book reviews the state-of-the-art in combinatorial testing, with particular emphasis on the automatic generation of test data. It describes the most commonly used approaches in this area - including algebraic construction, greedy methods, evolutionary computation, constraint solving and optimization - and explains major algorithms with examples. In addition, the book lists a number of test generation tools, as well as benchmarks and applications. Addressing a multidisciplinary topic, it will be of particular interest to researchers and professionals in the areas of software testing, combinatorics, constraint solving and evolutionary computation.
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Introduction to Combinatorial Testing -- Mathematical Construction Methods -- One Test at a Time -- The IPO Family -- Evolutionary Computation and Metaheuristics -- Evolutionary Computation and Metaheuristics -- Tools and Benchmarks -- Other Related Topics.

This book reviews the state-of-the-art in combinatorial testing, with particular emphasis on the automatic generation of test data. It describes the most commonly used approaches in this area - including algebraic construction, greedy methods, evolutionary computation, constraint solving and optimization - and explains major algorithms with examples. In addition, the book lists a number of test generation tools, as well as benchmarks and applications. Addressing a multidisciplinary topic, it will be of particular interest to researchers and professionals in the areas of software testing, combinatorics, constraint solving and evolutionary computation.

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