Please use this identifier to cite or link to this item: http://hdl.handle.net/123456789/308
Title: Retrieving Best Component from Reusable Repository
Authors: Kaur, Navneet
Supervisor: Bhatia, Rajesh K.
Keywords: Reusable Repository;CBSE;Retrieval Technique;Fuzzy Logic Based Retrieval
Issue Date: 1-May-2007
Abstract: The main purpose of information retrieval system is to retrieve the information according to user need. In principle, information storage and retrieval is simple. But practically the effective information retrieval is not as simple. Much of the research and development in information retrieval is aimed at improving the effectiveness and efficiency of retrieval. Effective component retrieval from a large repository is one such aim of the on going research. In software component repository thousand of components are stored using various classification techniques. Retrieving a software component that can be reused is a tedious process. Software components have certain attributes associated with them, and each attribute has relative importance for that component, which is called as weights. Retrieving the components considering these features becomes more difficult and time consuming. The objective of thesis is to select the best component from a repository that can be reused. In the proposed system one such component repository is developed. From repository best component has to be found. Best components are retrieved in a two step process. The first step gives all the relevant components, and the second step gives the best component to the user. This enhances the chances of retrieval of best component from a repository. The first technique used is simple keyword based retrieval and second technique is genetic algorithm. Genetic algorithms give satisfactory results for those components which have attributes and weights. The genetic algorithms based technique is very effective when the repository size is very large. It is based on mechanism of natural selection and natural genetics.
URI: http://hdl.handle.net/123456789/308
Appears in Collections:Masters Theses@CSED

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