Papers

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longitudinal study
Y. Long and Siau, K., Social network structures in open source software development teams, Journal of Database Management, vol. 18, pp. 25-40, 2007.
A. “E. ” Azarbakht and Jensen, C., Longitudinal Analysis of the Run-up to a Decision to Break-up (Fork) in a Community, Open Source Systems: Towards Robust Practices 13th International Conference on Open Source Systems, vol. 496. Springer, pp. 204-217, 2017.
C. Subramaniam, Sen, R., and Nelson, M. L., Determinants of open source software project success: A longitudinal study, Decis. Support Syst., vol. 46, pp. 576–585, 2009.
loose coupling
R. T. Fielding, Software architecture in an open source world, in Proceedings of the 27th international conference on Software engineering, New York, NY, USA, 2005, pp. 43–43.
lower barrier to entry
R. Dyer, Nguyen, H. A., Rajan, H., and Nguyen, T. N., Boa: A Language and Infrastructure for Analyzing Ultra-Large-Scale Software Repositories, 35th Int'l Conference on Software Engineering (ICSE 2013). pp. 422-431, 2013.
lpc
G. Antoniol, Rollo, V. F., and Venturi, G., Linear predictive coding and cepstrum coefficients for mining time variant information from software repositories, in Proceedings of the 2005 international workshop on Mining software repositories, New York, NY, USA, 2005, pp. 74-78.PDF icon 74LinearPredictive.pdf (190.25 KB)
lsedit
O. Baysal and Malton, A. J., Correlating Social Interactions to Release History during Software Evolution, in Fourth International Workshop on Mining Software Repositories (MSR'07:ICSE Workshops 2007), Minneapolis, MN, USA, 2007, pp. 7 - 7.PDF icon 28300007.pdf (180.64 KB)
lsm
G. B. Newby, Greenberg, J., and Jones, P., Open source software development and Lotka's Law: Bibliometric patterns in programming, Journal of the American Society for Information Science and Technology, vol. 54, pp. 169-178, 2003.
lucene
M. Squire, A Replicable Infrastructure for Empirical Studies of Email Archives, 3rd International Workshop on Replication in Empirical Software Engineering Research (RESER2013). IEEE, Baltimore, MD, USA, pp. 43-50, 2013.PDF icon RESERv2.pdf (628.97 KB)
C. Weiss, Premraj, R., Zimmermann, T., and Zeller, A., How Long Will It Take to Fix This Bug?, in Fourth International Workshop on Mining Software Repositories (MSR'07:ICSE Workshops 2007), Minneapolis, MN, USA, 2007, p. 1.PDF icon 28300001.pdf (674.21 KB)
A. Guzzi, Bacchelli, A., Lanza, M., Pinzger, M., and van Deursen, A., Communication in Open Source Software Development Mailing Lists, 10th Working Conference on Mining Software Repositories. pp. 277-286, 2013.PDF icon Guzzi2013msr.pdf (580.06 KB)
M. D'Ambros, Lanza, M., and Robbes, R., An extensive comparison of bug prediction approaches, in 2010 7th IEEE Working Conference on Mining Software Repositories (MSR 2010)2010 7th IEEE Working Conference on Mining Software Repositories (MSR 2010), Cape Town, South Africa, 2010, pp. 31 - 41.PDF icon 31dambrosLanzaRobbes31.pdf (408.78 KB)
machine learning
S. Rastkar, Murphy, G. C., and Murray, G., Summarizing software artifacts: a case study of bug reports, in Proceedings of the 32nd ACM/IEEE International Conference on Software Engineering - Volume 1, New York, NY, USA, 2010, pp. 505–514.
J. Anvik, Hiew, L., and Murphy, G. C., Who should fix this bug?, in Proceedings of the 28th international conference on Software engineering, New York, NY, USA, 2006, pp. 361–370.
J. Brunet, Murphy, G. C., Terra, R., Figueiredo, J., and Serey, D., Do Developers Discuss Design?, in Proceedings of the 11th Working Conference on Mining Software Repositories, New York, NY, USA, 2014, pp. 340–343.PDF icon brunet.pdf (304.26 KB)
C. Vendome, Linares-Vasquez, M., Bavota, G., Di Penta, M., German, D. M., and Poshyvanyk, D., Machine Learning-Based Detection of Open Source License Exceptions, 2017 IEEE/ACM 39th International Conference on Software Engineering. pp. 118-129, 2017.
I. Samoladas, Bibi, S., Stamelos, I., Sowe, S. K., and Deligiannis, I., A Preliminary Analysis of Publicly Available FLOSS Measurements: Towards Discovering Maintainability Trends, in 2nd Workshop on Public Data about Software Development (WoPDaSD 2007), 2007.PDF icon Samolades2007.pdf (119.75 KB)
Magnet
K. Yamashita, McIntosh, S., Kamei, Y., and Ubayashi, N., Magnet or Sticky? An OSS Project-by-project Typology, in Proceedings of the 11th Working Conference on Mining Software Repositories, New York, NY, USA, 2014, pp. 344–347.PDF icon yamashita.pdf (524.42 KB)
mailing list
M. Squire, "Should we move to Stack Overflow?" Measuring the utility of social media for developer support, 37th International Conference on Software Engineering. IEEE, p. 10pp, 2015.PDF icon SEIP2015stackv2.pdf (256.18 KB)
S. L. Toral, Martínez-Torres, M. R., and Barrero, F., Analysis of virtual communities supporting OSS projects using social network analysis, Information and Software Technology, vol. 52, no. 3, pp. 296 - 303, 2010.
L. Prechelt and Oezbek, C., The search for a research method for studying OSS process innovation, Empirical Software Engineering, vol. 16, no. 4, pp. 514 - 537, 2011.
W. Poncin, Serebrenik, A., and van den Brand, M., Process Mining Software Repositories, in 15th European Conference on Software Maintenance and Reengineering (CSMR 2011) , Oldenburg, Germany, 2011, pp. 5 - 14.PDF icon 2011-03_CSMR.pdf (794.15 KB)
C. Jensen, King, S., and Kuechler, V., Joining Free/Open Source Software Communities: An Analysis of Newbies' First Interactions on Project Mailing Lists, in 2011 44th Hawaii International Conference on System Sciences (HICSS 2011), Kauai, HI, 2011, pp. 1 - 10.

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