Abstract—Regression testing is used to revalidate modified program and provide confidence that changes does not harm the behavior of the existing code. Test suites grows in size as software evolve, a simple approach of regression testing is re-test all approach in which all the pre-existing test suites are executed on the code but it is too expensive and increase the cost of testing activity. Different problems have been involved with regression testing, e.g. test suites minimization problem, test selection problem, coverage identification problem, test case execution problem, test case maintenance problem etc. Another problem may occur, when tester has to select the changed paths from the set of modified paths for test case execution. This paper presents a new path selection strategy based on static analysis for regression testing which enables the tester to execute the test cases in an order that increases their effectiveness to find faults taking minimum efforts. With the proposed approach, tester can select the paths among the set of paths in an order to achieve the testing objective. Infeasible paths are also identified by the proposed approach which can reduce the effort, time, and cost.
—Regression testing, software complexity metrics, path selection strategy.
M. K. Debbarma is with the Department of Computer Science and Engineering, National Institute of Technology, Agartala, Tripura, PIN 799055, India (e-mail: firstname.lastname@example.org).
S. Tiwari and A. K. Misra are with the Computer Science and Engineering Department of Motilal Nehru Institute of Technology Allahabad, PIN 211-004, India, (e-mail: email@example.com, firstname.lastname@example.org).
Cite: S. Tiwari and A. K. Misra are with the Computer Science and Engineering Department of Motilal Nehru Institute of Technology Allahabad, PIN 211-004, India, (e-mail: email@example.com, firstname.lastname@example.org)., "Efficient Path Selection Strategy Based on Static Analysis for Regression Testing," International Journal of Computer Theory and Engineering
vol. 5, no. 2, pp. 248-252, 2013.