Estimating t-Way Fault Profile Evolution During Testing

Kuhn, Richard; Kacker, Raghu; Lei, Yu

doi:https://doi.org/10.1109/COMPSAC.2016.110

Conference Proceedings

Estimating t-Way Fault Profile Evolution During Testing

Documentation Topics

Published: September 07, 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: June 10-14, 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

Abstract

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.

Keywords

testing; combinatorial testing; software fault

Control Families

None selected

Documentation

Publication:
Conference Proceedings (DOI)

Supplemental Material:
Preprint (pdf)

Document History:
09/07/16: Conference Proceedings (Final)

Topics

Security and Privacy
general security & privacy