A Test Generation Strategy For Variable-Strength and T-way Interaction

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9783639661149: A Test Generation Strategy For Variable-Strength and T-way Interaction
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Recently, researchers have started to explore the use of Artificial Intelligence (AI)-based algorithms as t-way (where t indicates the interaction strength) and variable-strength testing strategies. Many AI-based strategies have been developed, such as Ant Colony, Simulated Annealing, Genetic Algorithm, and Tabu Search. Although useful, most existing AI-based strategies adopt complex search processes and require heavy computations. For this reason, existing AI-based strategies have been confined to small interaction strengths (i.e., t≤3) and small test configurations. Recent studies demonstrate the need to go up to t=6 in order to capture most faults. This book presents the design and implementation of a new interaction test generation strategy, known as the Particle Swarm-based Test Generator (PSTG), for generating t-way and variable-strength test suites. Unlike other existing AI-based strategies, the lightweight computation of the particle swarm search process enables PSTG to support high interaction strengths of up to t=6. The performance of PSTG is evaluated using several sets of benchmark experiments. PSTG consistently outperforms its AI counterparts.

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Obtained his BSc degree in Electrical Engineering from the Salahuddin University-Hawler in 2004 and his MSc degree from University Putra Malaysia in 2009 and his PhD degree from University Sains Malaysia, Software Engineering, in 2012. He is now a lecturer and IT director in the college of engineering, Salahaddin University-Hawler, Software Dep.

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Book Description SPS Aug 2014, 2014. Taschenbuch. Condition: Neu. Neuware - Recently, researchers have started to explore the use of Artificial Intelligence (AI)-based algorithms as t-way (where t indicates the interaction strength) and variable-strength testing strategies. Many AI-based strategies have been developed, such as Ant Colony, Simulated Annealing, Genetic Algorithm, and Tabu Search. Although useful, most existing AI-based strategies adopt complex search processes and require heavy computations. For this reason, existing AI-based strategies have been confined to small interaction strengths (i.e., t 3) and small test configurations. Recent studies demonstrate the need to go up to t=6 in order to capture most faults. This book presents the design and implementation of a new interaction test generation strategy, known as the Particle Swarm-based Test Generator (PSTG), for generating t-way and variable-strength test suites. Unlike other existing AI-based strategies, the lightweight computation of the particle swarm search process enables PSTG to support high interaction strengths of up to t=6. The performance of PSTG is evaluated using several sets of benchmark experiments. PSTG consistently outperforms its AI counterparts. 144 pp. Englisch. Seller Inventory # 9783639661149

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Book Description SPS Aug 2014, 2014. Taschenbuch. Condition: Neu. Neuware - Recently, researchers have started to explore the use of Artificial Intelligence (AI)-based algorithms as t-way (where t indicates the interaction strength) and variable-strength testing strategies. Many AI-based strategies have been developed, such as Ant Colony, Simulated Annealing, Genetic Algorithm, and Tabu Search. Although useful, most existing AI-based strategies adopt complex search processes and require heavy computations. For this reason, existing AI-based strategies have been confined to small interaction strengths (i.e., t 3) and small test configurations. Recent studies demonstrate the need to go up to t=6 in order to capture most faults. This book presents the design and implementation of a new interaction test generation strategy, known as the Particle Swarm-based Test Generator (PSTG), for generating t-way and variable-strength test suites. Unlike other existing AI-based strategies, the lightweight computation of the particle swarm search process enables PSTG to support high interaction strengths of up to t=6. The performance of PSTG is evaluated using several sets of benchmark experiments. PSTG consistently outperforms its AI counterparts. 144 pp. Englisch. Seller Inventory # 9783639661149

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Book Description Scholars' Press. Paperback. Condition: New. 144 pages. Dimensions: 8.7in. x 5.9in. x 0.3in.Recently, researchers have started to explore the use of Artificial Intelligence (AI)-based algorithms as t-way (where t indicates the interaction strength) and variable-strength testing strategies. Many AI-based strategies have been developed, such as Ant Colony, Simulated Annealing, Genetic Algorithm, and Tabu Search. Although useful, most existing AI-based strategies adopt complex search processes and require heavy computations. For this reason, existing AI-based strategies have been confined to small interaction strengths (i. e. , t3) and small test configurations. Recent studies demonstrate the need to go up to t6 in order to capture most faults. This book presents the design and implementation of a new interaction test generation strategy, known as the Particle Swarm-based Test Generator (PSTG), for generating t-way and variable-strength test suites. Unlike other existing AI-based strategies, the lightweight computation of the particle swarm search process enables PSTG to support high interaction strengths of up to t6. The performance of PSTG is evaluated using several sets of benchmark experiments. PSTG consistently outperforms its AI counterparts. This item ships from multiple locations. Your book may arrive from Roseburg,OR, La Vergne,TN. Paperback. Seller Inventory # 9783639661149

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