Proceedings Article10.1109/QSIC.2007.4385510
An Effective Iterative Metamorphic Testing Algorithm Based on Program Path Analysis
Guowei Dong,Changhai Nie,Baowen Xu,Lulu Wang +3 more
- 11 Oct 2007
- pp 292-297
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TL;DR: A new iterative MT algorithm, APCEMSI, is presented to avoid the blindness of existing MT methods and shows that APCemSI could find errors effectively with much fewer test cases.
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Abstract: Metamorphic testing (MT) is very practical and effective for programs with oracle problems, and many researches have been done in this field. In this article, we present a new iterative MT algorithm, APCEMSI, to avoid the blindness of existing MT methods. The test suites generated by APCEMSI satisfy a criterion which is defined upon program path analysis technique. Experiment result shows that APCEMSI could find errors effectively with much fewer test cases.
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Citations
A survey of combinatorial testing
Changhai Nie,Hareton Leung +1 more
TL;DR: Previous work on CT is reviewed, the evolution of CT is highlighted, important issues, methods, and applications of CT are identified, and the growing trend of CT research is presented.
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A Survey on Metamorphic Testing
TL;DR: This article provides a comprehensive survey on metamorphic testing, which summarises the research results and application areas, and analyses common practice in empirical studies of metamorphIC testing as well as the main open challenges.
A New Method for Constructing Metamorphic Relations
Huai Liu,Xuan Liu,Tsong Yueh Chen +2 more
- 27 Aug 2012
TL;DR: This paper proposes a simple method, namely, the composition of metamorphic relations, for systematically constructing new metamorpho-social relations based on the already identified metamorphIC relations, and shows that new metmorphic relations can be easily constructed by compositing some existing metamorphics relations.
Test cases generation for multiple paths based on PSO algorithm with metamorphic relations
TL;DR: A test case generation method for multiple-path coverage is proposed, which combines a particle swarm optimisation (PSO) algorithm with metamorphic relations (MRs) and can significantly enhance the efficiency in terms of fitness evaluations and time consumption.
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Constrained multi-objective test data generation based on set evolution
TL;DR: The experimental results show that the test data generated by the proposed model have higher fault finding ability than statement coverage testing and adaptive random testing; in addition, compared with conventional GAs, the proposed algorithm needs less execution time with the number of test data not increasing significantly.
18
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•Posted Content
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TL;DR: A novel test case selection technique is proposed that derives new test cases from the successful ones and helps uncover software errors in the production phase and can be used in the absence of test oracles.
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