When should objected-oriented software be scheduled for optimal maintenance? Prediction models need to be developed for effectively scheduling object-oriented systems for maintenance. Alsolai and Roper propose a collection of techniques for the examination of expenses, time, and labor required to maintain object-oriented software.

The authors present concise reviews of software quality assurance and metrics research in the literature. Indeed, the accurate measurement and prediction of software maintenance costs, time, and efforts will depend on the implicit assumptions of the models used to inspect the various datasets in public and private software systems. Consequently, the authors propose to identify reliable software datasets and forecast models for effectively maintaining object-oriented software. The ensemble object-oriented software maintenance prediction models under investigation consist of well-known regression and classification techniques for exploring patterns in homogeneous and heterogeneous datasets.

The paper reviews the literature on prediction models and presents research questions and anticipated results. The authors fail to identify the specific ensemble techniques to be investigated in predicting object-oriented software maintenance. The nature of the experiments to be performed to accurately forecast object-oriented software maintenance is unclear. Software developers and engineers should read this paper and help identify precise decision-making models for object-oriented software maintenance based on cost, manpower, and release deadlines.