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Journal of Information Science and Engineering, Vol. 32 No. 1, pp. 177-196 (January 2016)

A New Spectrum-based Fault Localization With the Technique of Test Case Optimization*

School of Information and Communication Engineering
Sungkyunkwan University
Suwon 400-746, South Korea
E-mail: {jeonghodot; ilovef12; leees}

Fault localization is an essential step for debugging, even though it is a still tedious and time-consuming activity. For decades, many researchers have tried to find a good way for more effective testing. We are also studying about fault localization via various method. Especially, we perform an empirical evaluation for existing 32 algorithms that are prominent in the domain of spectrum-based fault localization. Through the evaluation, we analyze them with some properties such as accuracy, and categorize them with a clustering method. Based on the analysis result, we suggest new formulas, and technique of test case optimization. These formulas, named SEM(Sungkyunkwan Enhanced Method), can cover the weakness of each categorized group, and test case optimization method can maximize performance using minimum test cases. These two methods individually out-performs previously proposed methods. When both methods are used together, the performance is maximized with respect to accuracy, and cost. In experimental result, EXAM score is reduced by maximum 29.41%, and code coverage is reduced by maximum 42.21%. In addition, all the experimental effort is performed with a tool, named SKKU_FL (Sung-KyunKwanUniversity Fault Localizer), which has been developed by us. The goal of this paper is to provide an accurate testing guideline by suggesting methods such as SEM, and test case optimization. Ultimately we help testers to reduce time, and costs for effective test.

Keywords: spectrum-based fault localization, software debugging, suspicious ratio, empirical evaluation, Siemens test suite

Full Text () Retrieve PDF document (201601_10.pdf)

Received June 26, 2014; revised November 2, 2014; accepted December 15, 2014.
Communicated by Jiann-Liang Chen.
* This research was supported by the National Research Foundation of Korea (NRF) grant funded by the Korea government (MEST) (No.2012008240) and by Next-Generation Information Computing Development Program through the National Research Foundation of Korea (NRF) funded by the Ministry of Education, Science and Technology (No. 2012033347).