Case generation by constraints combinatorial testing

doi:10.16511/j.cnki.qhdxxb.2017.26.001

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Abstract The inputs parameters to software systems usually have various constraints correlated to each other. However, the input often violates the required constraints and constraint correlations. When there are many parameters with a large input domain, combinatorial testing can be used to reduce the test cost while ensuring test coverage. This paper defines a test adequacy criterion for constraint coverage using constrained combinatorial testing to detect conflicts caused by violating the constraints and constraint combinations. The system was applied to a member registration service for an online payment platform. Three typical combinatorial algorithms, OA (orthogonal array), IPO (in parameter order) and OFOT (one factor one time), were compared in forward their speeds, defect detection efficiency, and test case size using different configurations and parameter settings. The results showed that the OA algorithm was fast, produced fewer, more stable test cases with a reasonable defect detection efficiency, so this algorithm is good for iterative optimizations.

Keywords software testing combinatorial testing constraints combination test generation

ZTFLH:

TP311.5

Issue Date: 15 March 2017

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	BAI Xiaoying
	HUANG Jun

Cite this article:

BAI Xiaoying,HUANG Jun. Case generation by constraints combinatorial testing[J]. Journal of Tsinghua University(Science and Technology), 2017, 57(3): 225-233.

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http://jst.tsinghuajournals.com/EN/10.16511/j.cnki.qhdxxb.2017.26.001 OR http://jst.tsinghuajournals.com/EN/Y2017/V57/I3/225

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