Publication Type

Conference Proceeding Article

Publication Date



In statistics and data mining communities, there have been many measures proposed to gauge the strength of association between two variables of interest, such as odds ratio, confidence, Yule-Y, Yule-Q, Kappa, and gini index. These association measures have been used in various domains, for example, to evaluate whether a particular medical practice is associated positively to a cure of a disease or whether a particular marketing strategy is associated positively to an increase in revenue, etc. This paper models the problem of locating faults as association between the execution or non-execution of particular program elements with failures. There have been special measures, termed as suspiciousness measures, proposed for the task. Two state-of-the-art measures are Tarantula and Ochiai, which are different from many other statistical measures. To the best of our knowledge, there is no study that comprehensively investigates the effectiveness of various association measures in localizing faults. This paper fills in the gap by evaluating 20 wellknown association measures and compares their effectiveness in fault localization tasks with Tarantula and Ochiai. Evaluation on the Siemens programs show that a number of association measures perform statistically comparable as Tarantula and Ochiai.


Association measures, Fault location, Debugging, Data mining, Statistical analysis, Variables of interest


Software Engineering

Research Areas

Software Systems


Proceedings of the IEEE International Conference on Software Maintenance (ICSM)

First Page


Last Page








City or Country

Timisoara, Romania

Creative Commons License

Creative Commons Attribution-Noncommercial-No Derivative Works 4.0 License
This work is licensed under a Creative Commons Attribution-Noncommercial-No Derivative Works 4.0 License.

dataset_Comprehensive Evaluation of Association Measures.rar (31506 kB)
Data from Comprehensive Evaluation of Association Measures for Fault Localization

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To cite the data package, please use the following citation:

Lucia, Lo, D., Lingxiao, J., & Budi, A. (2010). Data from: Comprehensive evaluation of association measures for fault localization. InK Repository at Singapore Management University.