Title: Utility of an object-oriented metrics component: examining the feasibility of .Net and C# object-oriented program from the perspective of mobile learning

Authors: Neelamadhab Padhy; R.P. Singh; Suresh Chandra Satapathy

Addresses: Sri Satya Sai University of Technology and Medical Sciences, Pachama, Sehore (M.P.) 466001, India ' Sri Satya Sai University of Technology and Medical Sciences, Pachama, Sehore (M.P.) 466001, India ' Department of Computer Science and Engineering, PVP Siddhartha Institute of Technology, Vijayawada, Andhra Pradesh, India

Abstract: In the 21st century, mobile applications could be built using different object-oriented languages like C#, Java and object-oriented framework. Increasing and maintaining the software product for multiple applications remains to be a challenging task. Object-oriented metrics play a crucial role in development of a software product. The estimation of object-oriented metrics is essential in the software engineering domain, including measuring the software code complexity, and estimating the size and quality of the products. Developers generally implements applications on different platforms, such as the Android in Java and Windows in C#, by having the metrics estimation conducted automatically since manual calculation is difficult. The metrics are generated in different ways owing to the change of mobile technologies and other marketing factors. This research not only reviews both manual and automated design tools for the estimation of object-oriented metrics for mobile applications, but also proposes a novel approach for estimating the metrics by recognising individual metrics and estimating the re-usability factors in a dynamic manner. The Chidamber and Kemerer metrics suite is best suited for measuring the object-oriented design metrics. This paper reviews the object-oriented metrics and analyses the difference through a comparison table; following that, several suggestions are provided to researchers and system developers.

Keywords: object-oriented metrics; CK metrics; DRUBM; ATDFEOOMFA.

DOI: 10.1504/IJMLO.2018.092777

International Journal of Mobile Learning and Organisation, 2018 Vol.12 No.3, pp.263 - 279

Received: 25 Apr 2017
Accepted: 03 Sep 2017

Published online: 26 Mar 2018 *

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