Subject: Computer Science
; Engineering
Title: automatic verification of optimization algorithms: a case study of a quadratic assignment problem solver
Author: Merkel Robert
; Wang Daoming
; Lin Huimin
; Chen Tsong Yueh
Keyword: Computer software selection and evaluation
; Optimization
; Verification
Source: International Journal of Software Engineering and Knowledge Engineering
Issued Date: 2011
Volume: 21, Issue: 2, Pages: 289-307 Indexed Type: EI
; SCI
Department: (1) Faculty of Information Technology Monash University Clayton VIC 3800 Australia; (2) Institute of Software Chinese Academy of Sciences 4 South Fourth Street Zhong Guan Cun Beijing 10090 China; (3) Centre for Software Analysis and Testing Swinburne University of Technology John Street Hawthorn 3122 Australia
Sponsorship: National Natural Science Foundation of China60721061; Australian Research Council (ARC)LX0776490
Abstract: Metamorphic testing is a technique for the verification of software output without a complete testing oracle. Mathematical optimization, implemented in software, is a problem for which verification can often be challenging. In this paper, we apply metamorphic testing to one such optimization problem, the quadratic assignment problem (QAP). From simple observations of the properties of the QAP, we describe how to derive a number of metamorphic relations useful for verifying the correctness of a QAP solver. We then compare the effectiveness of these metamorphic relations, in "killing" mutant versions of an exact QAP solver, to a simulated oracle. We show that metamorphic testing can be as effective as the simulated oracle for killing mutants. We examine the relative effectiveness of different metamorphic relations, both singly and in combination, and conclude that combining metamorphic relations can be significantly more effective than using a single relation. © 2011 World Scientific Publishing Company. English Abstract: Metamorphic testing is a technique for the verification of software output without a complete testing oracle. Mathematical optimization, implemented in software, is a problem for which verification can often be challenging. In this paper, we apply metamorphic testing to one such optimization problem, the quadratic assignment problem (QAP). From simple observations of the properties of the QAP, we describe how to derive a number of metamorphic relations useful for verifying the correctness of a QAP solver. We then compare the effectiveness of these metamorphic relations, in "killing" mutant versions of an exact QAP solver, to a simulated oracle. We show that metamorphic testing can be as effective as the simulated oracle for killing mutants. We examine the relative effectiveness of different metamorphic relations, both singly and in combination, and conclude that combining metamorphic relations can be significantly more effective than using a single relation. © 2011 World Scientific Publishing Company. Language: 英语
WOS ID: WOS:000293093800007
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Content Type: 期刊论文
URI: http://ir.iscas.ac.cn/handle/311060/16011
Appears in Collections: 软件所图书馆_期刊论文
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Recommended Citation:
Merkel Robert,Wang Daoming,Lin Huimin,et al. automatic verification of optimization algorithms: a case study of a quadratic assignment problem solver[J]. International Journal of Software Engineering and Knowledge Engineering,2011-01-01,21(2):289-307.
