Skip to main content
U.S. flag

An official website of the United States government

Official websites use .gov
A .gov website belongs to an official government organization in the United States.

Secure .gov websites use HTTPS
A lock ( ) or https:// means you’ve safely connected to the .gov website. Share sensitive information only on official, secure websites.

Fault Localization Based on Failure-Inducing Combinations

Published

Author(s)

Raghu N. Kacker

Abstract

Combinatorial testing has been shown to be a very effective testing strategy. After a failure is detected, the next task is to identify the actual fault that causes the failure. In this paper, we present an approach to fault localization that leverages the result of combinatorial testing. Our approach is based on a notion called failure-inducing combinations. A combination is failure- inducing if it causes any test in which it appears to fail. Given a failure-inducing combination, our approach derives a group of tests that are likely to exercise similar traces but produce different outcomes. These tests are then analyzed to locate the faults. We conducted an experiment in which our approach was applied to a suite of programs with seeded errors often used in testing research. The experimental results show that our approach can effectively and efficiently localize the faults in these programs.
Proceedings Title
Proceedings of Sixth IEEE International Conference on Software Testing, Verification and Validation
ICST 2013
Conference Dates
March 17-22, 2013
Conference Location
Luxembourg
Conference Title
Sixth IEEE International Conference on Software Testing, Verification and Validation ICST 2013

Keywords

Combinatorial Testing, Fault Localization, Debugging

Citation

Kacker, R. (2013), Fault Localization Based on Failure-Inducing Combinations, Proceedings of Sixth IEEE International Conference on Software Testing, Verification and Validation ICST 2013, Luxembourg, -1, [online], https://doi.org/10.1109/ISSRE.2013.6698916 (Accessed March 29, 2024)
Created November 7, 2013, Updated November 10, 2018