A Study on Defect Density of Open Source Software

Open source software (OSS) development is considered an effective approach to ensuring acceptable levels of software quality. One facet of quality improvement involves the detection of potential relationship between defect density and other open source software metrics. This paper presents an empirical study of the relationship between defect density and download number, software size and developer number as three popular repository metrics. This relationship is explored by examining forty-four randomly selected open source software projects retrieved from SourceForge.net. By applying simple and multiple linear regression analysis, the results reveal a statistically significant relationship between defect density and number of developers and software size jointly. However, despite theoretical expectations, no significant relationship was found between defect density and number of downloads in OSS projects.

[1]  Capers Jones,et al.  Programming Productivity , 1986 .

[2]  Xianggui Qu,et al.  Multivariate Data Analysis , 2007, Technometrics.

[3]  Khaled El-Emam Ethics and Open Source , 2004, Empirical Software Engineering.

[4]  D HerbslebJames,et al.  Two case studies of open source software development , 2002 .

[5]  Mladen A. Vouk,et al.  Using In-Process Metrics to Predict Defect Density in Haskell Programs , 2004 .

[6]  Reidar Conradi,et al.  An empirical study of software reuse vs. defect-density and stability , 2004, Proceedings. 26th International Conference on Software Engineering.

[7]  Eric S. Raymond,et al.  The cathedral and the bazaar - musings on Linux and Open Source by an accidental revolutionary , 2001 .

[8]  Eric Lease Morgan,et al.  Review of The Cathedral & the Bazaar: Musings on Linux and Open Source by an Accidental Revolutionary by Eric S. Raymond, Sebastopol, Calif.: O'Reilly, 1999 , 2000 .

[9]  Bora Caglayan,et al.  Merits of using repository metrics in defect prediction for open source projects , 2009, 2009 ICSE Workshop on Emerging Trends in Free/Libre/Open Source Software Research and Development.

[10]  Jakub Rudzki,et al.  Evaluating Quality of Open Source Components for Reuse-Intensive Commercial Solutions , 2009, 2009 35th Euromicro Conference on Software Engineering and Advanced Applications.

[11]  Elaine J. Weyuker,et al.  Do too many cooks spoil the broth? Using the number of developers to enhance defect prediction models , 2008, Empirical Software Engineering.

[12]  Victor R. Basili,et al.  Software errors and complexity: an empirical investigation0 , 1984, CACM.

[13]  Victor R. Basili,et al.  Software errors and complexity: an empirical investigation , 1993 .

[14]  Tze-Jie Yu,et al.  Identifying Error-Prone Software—An Empirical Study , 1985, IEEE Transactions on Software Engineering.

[15]  J. Herbsleb,et al.  Two case studies of open source software development: Apache and Mozilla , 2002, TSEM.

[16]  Stefan Koch,et al.  Exploring the effects of SourceForge.net coordination and communication tools on the efficiency of open source projects using data envelopment analysis , 2009, Empirical Software Engineering.

[17]  Chris F. Kemerer,et al.  A Metrics Suite for Object Oriented Design , 2015, IEEE Trans. Software Eng..

[18]  Stephen H. Kan,et al.  Metrics and Models in Software Quality Engineering , 1994, SOEN.