Published: September 7, 2016
Author(s)
Richard Kuhn (NIST), Raghu Kacker (NIST), Yu Lei (UTSA)
Conference
Name: 2016 IEEE 40th Annual Computer Software and Applications Conference (COMPSAC)
Dates: 06/10/2016 - 06/14/2016
Location: Atlanta, Georgia, United States
Citation: Proceedings of the 2016 IEEE 40th Annual Computer Software and Applications Conference Workshops (COMPSACW 2016), pp. 596-597
Empirical studies have shown that most software interaction faults involve one or two variables interacting, with progressively fewer triggered by three or more, and no failure has been reported involving more than six variables interacting. This paper introduces a model for the origin of this distribution, evaluates model predictions against empirical data, and discusses implications for removal of interaction faults and reliability growth.
Empirical studies have shown that most software interaction faults involve one or two variables interacting, with progressively fewer triggered by three or more, and no failure has been reported involving more than six variables interacting. This paper introduces a model for the origin of this...
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Empirical studies have shown that most software interaction faults involve one or two variables interacting, with progressively fewer triggered by three or more, and no failure has been reported involving more than six variables interacting. This paper introduces a model for the origin of this distribution, evaluates model predictions against empirical data, and discusses implications for removal of interaction faults and reliability growth.
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Keywords
testing; combinatorial testing; software fault
Control Families
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