Towards Improving Object-Oriented Software Maintenance during Change Impact Analysis

Today, resources are geared towards modifying rather than developing new software systems. Changes are necessary during the system’s lifetime to keep it useful but the major challenge is how these changes are controlled and managed. Software systems are complex with large dependency webs and components that are fault-prone. Modifying components without regard to its dependencies or its fault-proneness may have some unpredicted and potential effects on the quality or increase their risk to fail. Objectoriented software (OOS) systems are not exception. Identifying these components early may reduce system failure risks when implementing changes. Traditional researches on change impact analysis (CIA) of software code change and failure prediction are disjointed. Therefore, the main goal is to propose a change impact analysis framework that incorporates change and failure prediction while enhancing software quality and reducing maintenance time, cost and effort. By way of contribution and extension of existing knowledge, this research will explore and analyze OOS component’s relationship for effective change impact analysis and predicting early, the failure associated with fault-prone components by utilizing OO metrics.