Lrpt- Linear Regression Based Prioritization Techniques for Early Fault Detection
John Bruce. E1, T. Sasi Prabha2
1John Bruce. E, Research Scholar, Department of Computing, Sathyabama Institute of Science and Technology University, Chennai (Tamil Nadu), India.
2Dr. T. Sasi Prabha, Professor, Department of Computing, Sathyabama Institute of Science and Technology University, Chennai (Tamil Nadu), India.
Manuscript received on 22 April 2019 | Revised Manuscript received on 01 May 2019 | Manuscript Published on 05 May 2019 | PP: 237-241 | Volume-8 Issue-2S2, May 2019 | Retrieval Number: B10500182S219/19©BEIESP
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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC-BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: The role of Regression testing in the maintenance of software systems is significant when it undergoes frequent revision and enhancements. A novel technique for test case prioritization has been proposed, in this paper. The objective is to maximize fault coverage and to improve the efficiency. The test cases are ordered and analyzed with brute force prioritization techniques with initial, reverse and random ordering and Linear Regression based prioritization technique (LRPT). In this technique, regression models are used as a basis for selecting the features form as the components of the selection of test suite. The finely selected order of test suite prioritizes test cases for maximum fault coverage with fewer execution of test suite and its effective is compared with brute force orderings. The results of LRPT method shows an increase in the percentage of faults detected in comparison with brute force approaches.
Keywords: Linear Regression, Prioritization, Fault Detection, Data Reduction, Coverage Criterion etc.
Scope of the Article: Regression and Prediction