Srinivas Prasad

Work place: Dept. of Computer Science &Engineering, GMR Institute of Technology, Andhra Pradesh

E-mail: srinivas_prasad@hotmail.com

Website:

Research Interests: Computational Science and Engineering, Software, Software Construction, Software Development Process, Software Engineering, Computer systems and computational processes, Operating Systems, Data Structures and Algorithms

Biography

Srinivas Prasad has done his PhD in Computer Science, UU, Orissa. He has 20 years of experience in industry as well as institution. Currently he is working as professor and Heads of Department in Dept. of Computer Science &Engineering, GMRIT, Andhra Pradesh, India. His Research areas include Internet Technologies, Software Engineering, Object-Oriented Technologies, Operating Systems, Software Testing, Soft Computing and Big data.

Author Articles
Finding Representative Test Case for Test Case Reduction in Regression Testing

By Sudhir Kumar Mohapatra Srinivas Prasad

DOI: https://doi.org/10.5815/ijisa.2015.11.08, Pub. Date: 8 Oct. 2015

Software testing is one of the important stages of software development. In software development, developers always depend on testing to reveal bugs. In the maintenance stage test suite size grow because of integration of new technique. An addition of new technique force to create new test case which increase the size of test suite. In regression testing new test case may be added to the test suite during the whole testing process. These additions of test cases create possibility of presence of redundant test cases. Due to limitation of time and resource, reduction techniques should be used to identify and remove them. Research shows that a subset of the test case in a suit may still satisfy all the test objectives which is called as representative set. Redundant test case increase the execution cost of the test suite, in spite of NP-completeness of the problem there are few good reduction techniques have been available. In this paper a new approach for test case reduction is proposed. This algorithm use genetic algorithm technique iteratively with varying chromosome length to reduce test case in a test suit by finding a representative set of test cases that are fulfill the testing criteria.

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