Selection of Change prone Software Components using the Expertise of Semantic Web and Intelligent Computing Methods

Abstract

Software component development, like generic software development, deals with the construction of multi-version software which will relentlessly be predisposed to changes either to add novel features or to reform source code for accommodating future changes or for removing existing defects as a part of corrective maintenance. Therefore, knowledge regarding the change-prone source code components of any software project or component is vital as they are prospective cradles of modifications and defects and could also depict possible design issues that need to be solved. This thesis work proposes a novel change-prone software selection mechanism that employs Semantic web technology and Intelligent Computing Methods (ICM). The mechanism essentially selects those code components (Java files) of a software component that will be employed with change in the successive release of the component. Additionally, the work also identifies and establishes a cognitive aspect to the software change process. We first begin by extensively surveying the existing research in order to understand the topic in concern from three primary standpoints: (i) Software change prediction with an emphasis on the metrics used for software change prediction along with the prediction techniques employed, statistical tests used and validation strategies applied, (ii) The cognitive complexity metrics introduced and validated in literature and their use to estimate any software development procedure, and (iii) Application of Semantic web technologies for software component-based tasks with a key focus on the year wise trend of the research articles and possible justification of the usage of Semantic web technology and tools for a specific phase of component-based software development. From the literature studied, we observed that it is challenging to modify code fragments from existing software that are difficult to comprehend.