Published: March 22, 2013
Author(s)
M. Borazjany, L. Ghandehari, Yu Lei, Raghu Kacker, Richard Kuhn
Conference
Name: Second International Workshop on Combinatorial Testing 2013 (IWCT 2013)
Dates: 03/18/2013 - 03/22/2013
Location: Luxembourg, Luxembourg
Citation: Proceedings of the IEEE Sixth International Conference on Software Testing, Verification and Validation Workshops (ICSTW 2013), pp. 372-381
The input space of a system must be modeled before combinatorial testing can be applied to this system. The effectiveness of combinatorial testing to a large extent depends on the quality of the input space model. In this paper we introduce an input space modeling methodology for combinatorial testing. The main idea is to consider the process of input space modeling as two steps, namely, input structure modeling and input parameter modeling. The first step tries to capture the structural relationship among different components in the input space. The second step tries to identify parameters, values, relations and constraints for individual components. We also suggest strategies about how to perform unit and integration testing based on the input space structure. We applied the proposed methodology to two real-life programs. We report our experience and results that demonstrate the effectiveness of the proposed methodology.
The input space of a system must be modeled before combinatorial testing can be applied to this system. The effectiveness of combinatorial testing to a large extent depends on the quality of the input space model. In this paper we introduce an input space modeling methodology for combinatorial...
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The input space of a system must be modeled before combinatorial testing can be applied to this system. The effectiveness of combinatorial testing to a large extent depends on the quality of the input space model. In this paper we introduce an input space modeling methodology for combinatorial testing. The main idea is to consider the process of input space modeling as two steps, namely, input structure modeling and input parameter modeling. The first step tries to capture the structural relationship among different components in the input space. The second step tries to identify parameters, values, relations and constraints for individual components. We also suggest strategies about how to perform unit and integration testing based on the input space structure. We applied the proposed methodology to two real-life programs. We report our experience and results that demonstrate the effectiveness of the proposed methodology.
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Keywords
combinatorial testing; input parameter modeling; software testing
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