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Erschienen in:
Efficiency and Effectiveness Metrics in Evolutionary Algorithms and Their Application Kapitel lesen Erstes Kapitel lesen

2015 | OriginalPaper | Buchkapitel

A Genetic Local Search Algorithm for Optimal Testing Resource Allocation in Module Software Systems

verfasst von : Ruimin Gao, Siyan Xiong

Erschienen in: Intelligent Computing Theories and Methodologies

Verlag: Springer International Publishing

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Abstract

As modern software systems have been expanded continuously, the problem of how to optimally allocate the limited testing resource during the software testing phase attracted lots of attention. The Optimal Testing Resource Allocation Problems (OTRAPs) involve seeking for an optimal allocation of limited testing resource. There are two major objectives in the OTRAPs: reliability and cost. Since the designers pay more and more attention to reducing the cost, in this paper, we studied OTRAPs with the latter objective. In previous work, approaches based on genetic algorithms have been claimed to be strong alternatives in solving the problem. Hence, in this paper we proposed a new algorithm based on genetic algorithm and local search strategy (GLSA) to solve the OTRAPs. Experimental results show that the algorithm proposed can obtain better performance than some existing approaches for solving the software testing resource problem.

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Vorheriges Kapitel Efficiency and Effectiveness Metrics in Evolutionary Algorithms and Their Application
Nächstes Kapitel An Improved Artificial Bee Colony Algorithm Based on Particle Swarm Optimization and Differential Evolution
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Metadaten
Titel
A Genetic Local Search Algorithm for Optimal Testing Resource Allocation in Module Software Systems
verfasst von
Ruimin Gao
Siyan Xiong
Copyright-Jahr
2015
Buch
Intelligent Computing Theories and Methodologies

Print ISBN: 978-3-319-22185-4

Electronic ISBN: 978-3-319-22186-1

Copyright-Jahr: 2015

DOI
https://doi.org/10.1007/978-3-319-22186-1_2