2014/10/17 by Chayanika Sharma, Sharma, Chayanika, Sangeeta Sabharwal +3
Computer Science · #FOS: Computer and information sciences #Software Engineering (cs.SE) #Software Reliability and Analysis Research #Software System Performance and Reliability #Software Testing and Debugging Techniques #cs.SE
paper · pdf · doi:10.48550/arxiv.1410.4838
12 pages
arxiv created 2014/10/17 · openalex publication_date 2014/10/17 · arxiv updated 2014/10/21 · openalex created_date 2022/10/02 · openalex updated_date 2026/07/28
Software testing involves identifying the test cases whichdiscover errors in the program. However, exhaustive testing ofsoftware is very time consuming. In this paper, a technique isproposed to prioritize test case scenarios by identifying the critical path clusters using genetic algorithm. The test case scenarios are derived from the UML activity diagram and state chart diagram. The testing efficiency is optimized by applying the genetic algorithm on the test data. The information flow metric is adopted in this work for calculating the information flow complexity associated with each node of the activity diagram and state chart diagram.