Application of ensemble techniques in predicting object-oriented software maintainability

Alsolai, Hadeel and Roper, Marc; (2019) Application of ensemble techniques in predicting object-oriented software maintainability. In: Proceedings of EASE 2019 - Evaluation and Assessment in Software Engineering. ACM, DNK, pp. 370-373. ISBN 9781450371452 (https://doi.org/10.1145/3319008.3319716)

[thumbnail of Alsolai-Roper-EASE-2019-Application-of-ensemble-techniques-in-predicting-object]
Preview
Text. Filename: Alsolai_Roper_EASE_2019_Application_of_ensemble_techniques_in_predicting_object.pdf
Accepted Author Manuscript

Download (174kB)| Preview

Abstract

While prior object-oriented software maintainability literature acknowledges the role of machine learning techniques as valuable predictors of potential change, the most suitable technique that achieves consistently high accuracy remains undetermined. With the objective of obtaining more consistent results, an ensemble technique is investigated to advance the performance of the individual models and increase their accuracy in predicting software maintainability of the object-oriented system. This paper describes the research plan for predicting object-oriented software maintainability using ensemble techniques. First, we present a brief overview of the main research background and its different components. Second, we explain the research methodology. Third, we provide expected results. Finally, we conclude summary of the current status.