Measuring developer contribution from software repository data

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Measuring developer contribution from software repository data

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International Conference on Software Engineering archive
Proceedings of the 2008 international working conference on Mining software repositories table of contents

Leipzig, Germany

SESSION: People are people, so ... table of contents

Pages 129-132

Year of Publication: 2008

ISBN:978-1-60558-024-1

Authors

Georgios Gousios	Athens University of Economics and Business, Athens, Greece
Eirini Kalliamvakou	Athens University of Economics and Business, Athens, Greece
Diomidis Spinellis	Athens University of Economics and Business, Athens, Greece

Sponsors

SIGSOFT: ACM Special Interest Group on Software Engineering
ACM: Association for Computing Machinery

Publisher

ACM New York, NY, USA

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ABSTRACT

Apart from source code, software infrastructures supporting agile and distributed software projects contain traces of developer activity that does not directly affect the product itself but is important for the development process. We propose a model that, by combining traditional contribution metrics with data mined from software repositories, can deliver accurate developer contribution measurements. The model creates clusters of similar projects to extract weights that are then applied to the actions a developer performed on project assets to extract a combined measurement of the developer's contribution. We are currently implementing the model in the context of a software quality monitoring system while we are also validating its components by means of questionnaires.

REFERENCES

Note: OCR errors may be found in this Reference List extracted from the full text article. ACM has opted to expose the complete List rather than only correct and linked references.

	1	J. J. Amor, G. Robles, and J. M. Gonzalez-Barahona. Effort estimation by characterizing developer activity. In The 8th international workshop on economics-driven software engineering research. ACM, May 2006.
	2	A. Capiluppi, P. Lago, and M. Morisio. Characteristics of open source projects. In Proceedings of the Seventh European Conference on Software Maintenance and Reengineering, pages 317--327, Mar 2003.
	3	D. N. Card and B. Scalzo. Measurement for object-orienated software projects. In Proceedings of the 6th International Symposium on Software Metrics, Florida, Nov 1999.
	4	R. L. Glass, I. Vessey, and S. A. Conger. Software tasks: intellectual or clerical? Inf. Manage., 23(4):183--191, 1992.
	5	G. Gousios, V. Karakoidas, K. Stroggylos, P. Louridas, V. Vlachos, and D. Spinellis. Software quality assesment of open source software. In Proceedings of the 11th Panhellenic Conference on Informatics, May 2007.
	6	G. Hertel, S. Niedner, and S. Herrmann. Motivation of software developers in open source projects: an internet-based survey of contributors to the linux kernel. Research Policy, 32(7):1159--1177, Jul 2003.
	7	S. H. Kan. Metrics and Models in Software Quality Engineering, chapter 12.3 Productivity Metrics. Addison-Wesley, 2003.
	8	C. Kaner and W. Bond. Software engineering metrics: What do they measure and how do we know? In 10th International Software Metrics Symposium (METRICS 2004). IEEE, IEEE CS Press, Sep 2004.
	9	S. Koch and G. Schneider. Results from software engineering research into open source development projects using public data. Diskussionspapiere zum tätigkeitsfeld informationsverarbeitung und informationswirtschaft, Wirtschaftsuniversität Wien, 2000.
	10	A. Mockus, R. T. Fielding, and J. Herbsleb. A case study of open source software development: the apache server. In ICSE '00: Proceedings of the 22nd international conference on Software engineering, pages 263--272, New York, NY, USA, 2000. ACM.
	11	H. Sackman, W. J. Erikson, and E. E. Grant. Exploratory experimental studies comparing online and offline programming performance. Commun. ACM, 11(1):3--11, 1968.