원문정보
초록
영어
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.
목차
1. Introduction
2. Genetic algorithm
3. Proposed Approach
3.1 Procedure
3.2 Selection
3.3 Reproduction (crossover)
3.4 Mutation
4. Case Study
4.1 Assigning Weights
4.2 Solving Case study Using Genetic Algorithms
5. Conclusion
References
Authors