期刊名称：International Journal of Software Engineering and Its Applications
印刷版ISSN：1738-9984
出版年度：2009
卷号：3
期号：4
出版社：SERSC
摘要：This paper presents a method for optimizing software testing efficiency by identifying the most critical path clusters in a program. We do this by developing variable length Genetic Algorithms that optimize and select the software path clusters which are weighted in accordance with the criticality of the path. Exhaustive software testing is rarely possible because it becomes intractable for even medium sized software. Typically only parts of a program can be tested, but these parts are not necessarily the most error prone. Therefore, we are developing a more selective approach to testing by focusing on those parts that are most critical so that these paths can be tested first. By identifying the most critical paths, the testing efficiency can be increased.
关键词：Software Testing; Genetic Algorithm; Test Data
