<?xml version="1.0" encoding="UTF-8"?><xml><records><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Steven Muegge</style></author><author><style face="normal" font="default" size="100%">Roberto Milev</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Measuring Modularity in Open Source Code Bases</style></title><secondary-title><style face="normal" font="default" size="100%">Open Source Business Resource</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2009</style></year><pub-dates><date><style  face="normal" font="default" size="100%">04/2009</style></date></pub-dates></dates><urls><web-urls><url><style face="normal" font="default" size="100%">http://timreview.ca/article/245</style></url></web-urls></urls><publisher><style face="normal" font="default" size="100%">Talent First Network</style></publisher><pub-location><style face="normal" font="default" size="100%">Ottawa</style></pub-location><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%"> Modularity of an open source software code base has been associated with growth of the software development community, the incentives for voluntary code contribution, and a reduction in the number of users who take code without contributing back to the community. As a theoretical construct, modularity links OSS to other domains of research, including organization theory, the economics of industry structure, and new product development. However, measuring the modularity of an OSS design has proven difficult, especially for large and complex systems.

In this article, we describe some preliminary results of recent research at Carleton University that examines the evolving modularity of large-scale software systems. We describe a measurement method and a new modularity metric for comparing code bases of different size, introduce an open source toolkit that implements this method and metric, and provide an analysis of the evolution of the Apache Tomcat application server as an illustrative example of the insights gained from this approach. Although these results are preliminary, they open the door to further cross-discipline research that quantitatively links the concerns of business managers, entrepreneurs, policy-makers, and open source software developers. 
</style></abstract><issue><style face="normal" font="default" size="100%">April 2009</style></issue><work-type><style face="normal" font="default" size="100%">Articles</style></work-type><custom1><style face="normal" font="default" size="100%">Carleton University
Steven Muegge is a faculty member of the Department of Systems and Computer Engineering at Carleton University, Ottawa, Canada. Professor Muegge teaches within the Technology Innovation Management program. His current research interests include open source software, open innovation, and open source ecosystems. </style></custom1><custom2><style face="normal" font="default" size="100%">Carleton University
Roberto Milev completed an M.Eng. degree in Technology Innovation Management in 2008.  As part of his research into open source software, he derived the relative clustered cost metric and developed the jDSM open source toolset for computing DSMs and modularity metrics.  He is currently working as a manager for a software development company. </style></custom2></record></records></xml>