Evaluating Combined Influence of Weighted Analysis Class Diagram Metrics on Early Software Size Estimation

Authors

  • Marriam Daud Department of Software Engineering, National University of Modern Languages (NUML), Islamabad, Pakistan
  • Ali Afzal Malik FAST School of Computing, National University of Computer and Emerging Sciences (NUCES), Lahore, Pakistan

Keywords:

Analysis class diagram metrics, early software size estimation, information systems, objective class points, simple linear regression models, source lines of code, weights

Abstract

Analysis Class Diagram (ACD) metrics like number of classes, number of methods, and number of attributes can be used for early software size estimation by project managers during initial project planning. However, not all of these ACD metrics have the same influence on software size. This study aims to empirically determine the relative influence of these ACD metrics on software size using historical data from academia and industry. Using the Objective Class Points (OCP) metric as a base, two new metrics – Enhanced OCP (EOCP) and Weighted EOCP (WEOCP) – are proposed. Separate linear regression-based early software size estimation models are also constructed and validated using the original OCP metric and its newly proposed variants. A comparison of these models reveals that models based on our newly proposed metrics perform better in terms of early size estimation accuracy.

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Published

2025-02-28

How to Cite

Daud, M., & Afzal Malik, A. (2025). Evaluating Combined Influence of Weighted Analysis Class Diagram Metrics on Early Software Size Estimation. Computing and Informatics, 44(1). Retrieved from http://147.213.75.17/ojs/index.php/cai/article/view/6843