Which One Is Better, Simple or Complex Metrics?

Fangjun Wu^1,2,3

¹School of Information Technology, Jiangxi University of Finance and Economics, Nanchang, China.
²Jiangxi Key Laboratory of Data and Knowledge Engineering, Jiangxi University of Finance and Economics, Nanchang, China.
³High Level Engineering Research Center of Electronic-Commerce, Jiangxi Provincial Colleges and Universities, Nanchang, China.

DOI: 10.4236/jcc.2015.311009                

Abstract

At the early stage of software lifecycle, the complexity measurement of UML class diagrams plays an important role in software development, testing and maintenance, and provides guidance for developing high quality software. In order to study which one is better, simple or complex metrics, this paper analyzes and compares four typical metrics of UML class diagrams from experimental software engineering view points. Understandability, analyzability and maintainability were classified and predicted for 27 class diagrams related to a banking system by means of algorithm C5.0 within the famous toolkit Weka. Results suggest that the performance of simple metrics is not inferior to that of complex metrics, in some cases even better than that of complex metrics.

Keywords

Software Measurement, UML Class Diagram, Empirical Validation, Classification

Conflicts of Interest

The authors declare no conflicts of interest.

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