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

By: Contributor(s): Material type: TextTextSeries: SpringerBriefs in Computer SciencePublisher: Berlin, Heidelberg : Springer Berlin Heidelberg : Imprint: Springer, 2014Description: XI, 90 p. 31 illus. online resourceContent type:
  • text
Media type:
  • computer
Carrier type:
  • online resource
ISBN:
  • 9783662434291
Subject(s): Additional physical formats: Printed edition:: No titleDDC classification:
  • 005.1 23
LOC classification:
  • QA76.758
Online resources:
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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Item type Current library Call number Status Date due Barcode
E-Book E-Book Central Library Available E-51207

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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