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Combinatorial Coverage as an Aspect of Test Quality
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Published: March 31, 2015
Citation: Crosstalk (Hill AFB): the Journal of Defense Software Engineering vol. 28, no. 2, (March/April 2015) pp. 19-23
Author(s)
Richard Kuhn (NIST), Raghu Kacker (NIST), Yu Lei (UTA)
There are relatively few good methods for evaluating test set quality, after ensuring basic requirements traceability. Structural coverage, mutation testing, and related methods can be used if source code is available, but these approaches may entail significant cost in time and resources. This paper introduces an alternative measure of test quality that is directly related to fault detection, simple to compute, and can be applied prior to execution of the system under test. As such, it provides an inexpensive complement to current approaches for evaluating test quality.
There are relatively few good methods for evaluating test set quality, after ensuring basic requirements traceability. Structural coverage, mutation testing, and related methods can be used if source code is available, but these approaches may entail significant cost in time and resources. This...
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There are relatively few good methods for evaluating test set quality, after ensuring basic requirements traceability. Structural coverage, mutation testing, and related methods can be used if source code is available, but these approaches may entail significant cost in time and resources. This paper introduces an alternative measure of test quality that is directly related to fault detection, simple to compute, and can be applied prior to execution of the system under test. As such, it provides an inexpensive complement to current approaches for evaluating test quality.
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Keywords
combinatorial coverage; combinatorial testing; software testing
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Document History:
03/31/15: Journal Article (Final)
