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Therefore, it is necessary to discover the techniques with the goal of increasing the regression testing‟s effectiveness, by arranging test cases of test suites according to some objective criteria.
In order to reduce the cost of regression testing, we propose a test case classification methodology based on k-means clustering with the purpose of classifying test cases into two groups of effective and non-effective test cases.
Experience shows that code coverage information can assist in selecting candidate test cases for regression testing.
This special test statistic can also detect a change in the regression function.
This paper shows a new technique to select effective test cases for regression testing of software.
Proceedings ArticleDOI
Sheng Huang, Jun Zhu, Yuan Ni 
25 Oct 2009
11 Citations
The whole design strategy is lightweight, making the regression test selection process more automated and effective, and scalable to commercial regression testing scenarios with resource and time constraints.
Proceedings ArticleDOI
Wenwu Ding, Jisong Kou, Kewen Li, Zhixia Yang 
19 May 2009
8 Citations
The test case study result shows the method can reduce the scale of test suite effectively and decrease the regression test cost.
Our empirical results support several conclusions about regression test selection.
Proceedings ArticleDOI
B. Athira, Philip Samuel 
22 Nov 2010
25 Citations
Our approach is effective in revealing the most promising regression test cases.