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  • 标题:A Genetic Algorithm Approach for Automatic Patch Prediction
  • 本地全文:下载
  • 作者:P. Maragathavalli ; S. Kanmani
  • 期刊名称:International Journal of Advanced Research In Computer Science and Software Engineering
  • 印刷版ISSN:2277-6451
  • 电子版ISSN:2277-128X
  • 出版年度:2013
  • 卷号:3
  • 期号:6
  • 出版社:S.S. Mishra
  • 摘要:Software system should be reliable and available failing which huge losses may incur. To achieve these objectives a thorough testing is required. In recent years, there has been a dramatic rise in the number of languages used in mainstream projects. In particular, languages which run on the JVM or Common Language Runtime (CLR) have become quite popular in creating a global development framework. Naturally, such languages prefer to inter-operate with other languages built on these core platforms, particularly Java and C#. The problem is that such efforts are crippled by one fundamental limitation: circular dependencies-a relation between two or more modules which either directly or indirectly depend on each other to function properly. This paper presents the study of patch prediction using a common testing software to minimize cost of testing and optimization of software testing techniques by using Genetic Algorithms (GAs) and Sequential Quadratic Programming Algorithm(SQPA) to provide features like memory management, security, garbage collection, thread management and exception handling
  • 关键词:Optimization techniques; Genetic algorithm; SQP algorithm; Patch prediction
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