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Activity Number:
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214
- Combinatorial Testing: Using Covering Arrays to Maximize the Impact of Testing
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Type:
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Invited
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Date/Time:
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Monday, July 29, 2019 : 2:00 PM to 3:50 PM
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Sponsor:
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Section on Physical and Engineering Sciences
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Abstract #300197
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Title:
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Factorial Experiments, Covering Arrays, and Combinatorial Testing
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Author(s):
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Raghu Kacker* and Rick Kuhn and Yu Lei and Dimitris Simos
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Companies:
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National Institute of Standards and Technology and National Institute of Standards and Technology and University of Texas at Arlington and SBA-Research, Austria
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Keywords:
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Combinatorial testing;
Covering arrays;
Factorial experiments;
Orthogonal arrays;
Pairwise testing;
Software testing
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Abstract:
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Checking that a software-based system produces correct results for all possible inputs is far beyond the reach for even modest size systems, since the number of tests required grows exponentially with the number of factors and their possible settings. How can one assure that a system will operate correctly? It turns out that while the behavior of a system may be affected by many factors, only a few are involved in any given failure. Combinations (of the settings of factors) which induce a failure are known as interaction faults. Combinatorial testing (CT) is a versatile black-box methodology for detecting interaction faults. Test suites for CT are based on mathematical objects called covering arrays while avoiding logically invalid combinations. Once an interaction fault is detected, the underlying defect or vulnerability in the software is located and corrected. We will discuss the methods, tools and applications of CT. Combinatorial testing may be regarded as a variation of factorial experiments (FE) for testing software-based systems. We will explain the similarities and differences between FE and CT. CT has gained significant interest and widespread use.
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Authors who are presenting talks have a * after their name.
