期刊名称：International Journal of Innovative Research in Computer and Communication Engineering
印刷版ISSN：2320-9798
电子版ISSN：2320-9801
出版年度：2016
卷号：4
期号：2
页码：1147
DOI：10.15680/IJIRCCE.2016.0402009
出版社：S&S Publications
摘要：The software industry has become one of the world's key industries in recent decades. The tremendous amount of growth in software development industry has taken a pace and has become a driving force. It has grabbed the attention of researchers due to its s ubtle impact on world's economy and society. Software engineering deals with the design and development of high quality and reliable software. The overall objective in developing software is to provide high quality software without errors and failures. In order to produce h igh quality software which confi rms to be the requirement specifications, it is necessary to test the software. Testing is required to make the software error free. This paper also highlights different techniques used for test case generat ion. Multi - objective formulations are realistic models for many complex engineering optimization problems. Customized genetic algorithms have been demonstrated to be particularly effective to determine excellent solutions to these problems. In many real - li fe problems, objectives under consideration conflict with each other, and optimizing a particular solution with respect to a single objective can result in unacceptable results with respect to the other objectives. A reasonable solution to a multi - objectiv e problem is to investigate a set of solutions, each of which satisfies the objectives at an acceptable level without being dominated by any other solution. This paper describes a method using multi - objective evolutionary algorithm for the automatic genera tion of test cases
关键词：Random;cyclomatic complexity; fitness factor; multi-objective genetic algorithm; test data
