Dynamic Requirement Clustering of Requirement with Usable Test Cases by Cosine-Correlation

In software engineering testing plays an important role in development and maintenance of software. Component based software development gained a lot of practical importance in the field of Software engineering by the academic researcher and industry for finding reusable efficient test cases. It is the predominant problem in software engineering that clustering reduces the search space of the component of test cases by grouping of similar entities together ensuring reduce time complexity and reduce the search time for retrieve test cases according to requirement. In this research paper we investigate how k-mean work on the set of requirement and usable test cases we also define how to resolve the k-mean clustering static number of cluster when new requirement or test cases will come. In this research paper we investigate how k-mean work on the set of requirement and usable test cases we also define how to resolve the k-mean clustering static number of cluster when new requirement or test cases will come. Here we purposed an approach for dynamic clustering for test cases and requirement.