Mining effort data from the OSS repository of developer's bug fix activity

During the evolution of any software, efforts are made to fix bugs or to add new features in software. In software engineering, previous history of effort data is required to build an effort estimation model, which estimates the cost and complexity of any software. Therefore, the role of effort data is indispensable to build state-of-the-art effort estimation models. Most of the Open Source Software does not maintain any effort related information. Consequently there is no state-of-the-art effort estimation model for Open Source Software, whereas most of the existing effort models are for commercial software. In this paper we present an approach to build an effort estimation model for Open Source Software. For this purpose we suggest to mine effort data from the history of the developer’s bug fix activities. Our approach determines the actual time spend to fix a bug, and considers it as an estimated effort. Initially, we use the developer’s bug-fix-activity data to construct the developer’s activity log-book. The log-book is used to store the actual time elapsed to fix a bug. Subsequently, the log-book information is used to mine the bug fix effort data. Furthermore, the developer’s bug fix activity data is used to define three different measures for the developer’s contribution or expertise level. Finally, we used the bug-fix-activity data to visualize the developer’s collaborations and the involved source files. In order to perform an experiment we selected the Mozilla open source project and downloaded 93,607 bug reports from the Mozilla project bug tracking system i.e., Bugzilla. We also downloaded the available CVS-log data from the Mozilla project repository. In this study we reveal that in case of Mozilla only 4.9% developers have been involved in fixing 71.5% of the reported bugs.

[1]  Andreas Zeller,et al.  How Long Will It Take to Fix This Bug? , 2007, Fourth International Workshop on Mining Software Repositories (MSR'07:ICSE Workshops 2007).

[2]  A. Zeller,et al.  If Your Bug Database Could Talk . . . , 2006 .

[3]  Brian Fitzgerald,et al.  Understanding open source software development , 2002 .

[4]  Thomas Zimmermann,et al.  Mining usage expertise from version archives , 2008, MSR '08.

[5]  Harald C. Gall,et al.  Analyzing and relating bug report data for feature tracking , 2003, 10th Working Conference on Reverse Engineering, 2003. WCRE 2003. Proceedings..

[6]  John E. Gaffney,et al.  Software Function, Source Lines of Code, and Development Effort Prediction: A Software Science Validation , 1983, IEEE Transactions on Software Engineering.

[7]  Michael Gertz,et al.  Expertise identification and visualization from CVS , 2008, MSR '08.

[8]  Lucas D. Panjer Predicting Eclipse Bug Lifetimes , 2007, Fourth International Workshop on Mining Software Repositories (MSR'07:ICSE Workshops 2007).

[9]  Jai Asundi,et al.  The need for effort estimation models for open source software projects , 2005, ACM SIGSOFT Softw. Eng. Notes.

[10]  Walt Scacchi,et al.  Socio-Technical Interaction Networks in Free/Open Source Software Development Processes , 2005 .

[11]  Barry W. Boehm,et al.  Cost models for future software life cycle processes: COCOMO 2.0 , 1995, Ann. Softw. Eng..

[12]  Franz Wotawa,et al.  Program File Bug Fix Effort Estimation Using Machine Learning Methods for OSS , 2009, SEKE.

[13]  Roger S. Pressman,et al.  Software Engineering: A Practitioner's Approach , 1982 .

[14]  Stéphane Ducasse,et al.  Understanding software evolution using a combination of software visualization and software metrics , 2002, Obj. Logiciel Base données Réseaux.

[15]  Eric S. Raymond,et al.  The Cathedral & the Bazaar , 1999 .

[16]  Eirini Kalliamvakou,et al.  Mediterranean Conference on Information Systems ( MCIS ) 2009 Measuring Developer Contribution From Software Repository Data , 2017 .

[17]  Chen Zhang,et al.  Impact of Social Ties on Open Source Project Team Formation , 2006, OSS.

[18]  Stefan Koch,et al.  Effort modeling and programmer participation in open source software projects , 2008, Inf. Econ. Policy.

[19]  Akif Günes Koru,et al.  An Exploratory Study on the Evolution of OSS Developer Communities , 2008, Proceedings of the 41st Annual Hawaii International Conference on System Sciences (HICSS 2008).

[20]  Liguo Yu Indirectly predicting the maintenance effort of open-source software , 2006, J. Softw. Maintenance Res. Pract..

[21]  Daniel M. Germán,et al.  Towards a simplification of the bug report form in eclipse , 2008, MSR '08.

[22]  Harvey Siy,et al.  If your ver-sion control system could talk , 1997 .