Towards a Unified Source Code Measurement Framework Supporting Multiple Programming Languages

Software metrics measure various attributes of a piece of software and are becoming essential for a variety of purposes, including software quality evaluation. One type of measurement is based on source code evaluation. Many tools have been developed to perform source code analysis or to measure various metrics, but most use different metrics definitions, leading to inconsistencies in measurement results. The metrics measured by these tools also vary by programming language. We propose a unified framework for measuring source code that supports multiple programming languages. In this paper, we present commonalities of measurable elements from various programming languages as the foundation for developing the framework. We then describe the approach used within the framework and also its preliminary development. We believe that our approach can solve the problems with existing measurement

[1]  David Alex Lamb,et al.  A Data Model for Object-Oriented Design Metrics , 1997 .

[2]  Linda M. Laird,et al.  Software Measurement and Estimation: A Practical Approach , 2006 .

[3]  Rüdiger Lincke,et al.  Comparing software metrics tools , 2008, ISSTA '08.

[4]  Fernando Brito e Abreu,et al.  An OCL-Based Formalization of the MOOSE Metric Suite , 2003 .

[5]  Norman E. Fenton,et al.  Measurement : A Necessary Scientific Basis , 2004 .

[6]  Shinji Kusumoto,et al.  A Pluggable Tool for Measuring Software Metrics from Source Code , 2011, 2011 Joint Conference of the 21st International Workshop on Software Measurement and the 6th International Conference on Software Process and Product Measurement.

[7]  Nikolay Grozev,et al.  A framework for source code metrics , 2010, CompSysTech '10.