Web-of-Service Software Reusability Prediction using Heterogenous Ensemble Classifier
Prakash V. Parande1, M. K. Banga2

1Prakash V. Parande, Research Scholar, School of Computing & Information Technology, Reva University, Bangalore, India.

2Dr. M. K. Banga, Professor, Department of CSE Director of School of Computing and information technology, Reva University, Bangalore India.

Manuscript received on 09 July 2019 | Revised Manuscript received on 21 July 2019 | Manuscript Published on 23 August 2019 | PP: 1276-1282 | Volume-8 Issue-9S3 August 2019 | Retrieval Number: I32810789S319/2019©BEIESP | DOI: 10.35940/ijitee.I3281.0789S319

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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open-access article under the CC-BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)

Abstract: WoS computing environment is expected to have numerous parallel computing engines. Presently, software professionals or developers often want to reuse existing software components to exhibit a task with time-efficient and cost effective solutions. However, software component reusability in uncontrolled manner leads to failure, premature shutdown and software smells or aging. This paper develops a novel evolutionary computing assisted ensemble classification system for WoS software reusability prediction. This applies different base learners such asNaïve Bayes (NB), Linear Regression (LR), Decision Tress (DT),Logarithmic Regression (LOGR),and Support Vector Machine (SVM),Multivariate Adaptive Regression Spline (MARS). Once training the base learners, the outputs of each classifier have been processed with majority vote.The computation in conjunction with weighted sum enabled final labelling of each software class. The performance results affirmed that the present work ensemble classifier has better performance with respect to base classifiers.

Keywords: Ensemble Classifier; Heterogeneous Ensemble; Web-Of-Service; Software Reusability Predictio
Scope of the Article: Software & System Security