Measuring the odds of statements being faulty

Xiaozhen Xue, Akbar Siami Namin

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

7 Scopus citations


The statistics captured during testing a faulty program are the primary source of information for effective fault localization. A typical ranking metric estimates suspiciousness of executable statements and ranks them according to the estimated scores. The coverage-based ranking schemes, such as the metric used in Tarantula and Ochiai score, utilize the execution profile of each test case, including code coverage and the statistics associated with the number of failing and passing test cases. Although the coverage-based fault localization metrics could be extended to hypothesis testing and in particular to the chi-square test associated with crosstab or known as contingency tables, not all contingency table association metrics are explored and studied. We introduce the odds ratio metric and its application to the fault localization problem. The odds-ratio metric has been used extensively in categorical data analysis and in measuring the association of dependency between dichotomous variables. However, its application to fault localization metric is new. Furthermore, we investigate the effectiveness of conditional odds ratio metric for fault localization when there are multiple faults in the programs. Our experimental results show that the odds ratio metric performs better than the other ranking metrics studied for single faults, whereas, the conditional odds ratio ranking scheme is competitive when there are multiple faults in the software under test.

Original languageEnglish
Title of host publicationAda Europe 2013 - 18th Ada-Europe International Conference on Reliable Software Technologies, Proceedings
Number of pages18
StatePublished - 2013
Event18th Ada-Europe International Conference on Reliable Software Technologies, Ada Europe 2013 - Berlin, Germany
Duration: Jun 10 2013Jun 14 2013

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume7896 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349


Conference18th Ada-Europe International Conference on Reliable Software Technologies, Ada Europe 2013


  • fault localization
  • testing


Dive into the research topics of 'Measuring the odds of statements being faulty'. Together they form a unique fingerprint.

Cite this