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@@ -550,7 +550,7 @@ @article{hormann:1993
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year = {1993},
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}
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@article{riehle2012,
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@article{riehle:2012,
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abstract = {The design of software development tools follows from what the developers of such tools believe is true about software development. A key aspect of such beliefs is the size of code contributions (commits) to a software project. In this paper, we show that what tool developers think is true about the size of code contributions is different by more than an order of magnitude from reality. We present this reality, called the commit size distribution, for a large sample of open source and selected closed source projects. We suggest that these new empirical insights will help improve software development tools by aligning underlying design assumptions closer with reality.},
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author = {Dirk Riehle and Carsten Kolassa and Michel A. Salim},
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issn = {1617-5468},
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year = {2012},
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}
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@inproceedings{arafat2009,
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@inproceedings{arafat:2009,
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abstract = {With the growing economic importance of open source, we need to improve our understanding of how open source software development processes work. The analysis of code contributions to open source projects is an important part of such research. In this paper we analyze the size of code contributions to more than 9,000 open source projects. We review the total distribution and distinguish three categories of code contributions using a size-based heuristic: single focused commits, aggregate team contributions, and repository refactorings. We find that both the overall distribution and the individual categories follow a power law. We also suggest that distinguishing these commit categories by size will benefit future analyses.},
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author = {Oliver Arafat and Dirk Riehle},
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booktitle = {Proceedings of the 42nd Hawaii International Conference on System Sciences},
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title = {{The Commit Size Distribution of Open Source Software}},
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year = {2009},
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}
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@inbook{hofmann:2009,
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abstract = {The quantitative analysis of software projects can provide insights that let us better understand open source and other software development projects. An important variable used in the analysis of software projects is the amount of work being contributed, the commit size. Unfortunately, post-facto, the commit size can only be estimated, not measured. This paper presents several algorithms for estimating the commit size. Our performance evaluation shows that simple, straightforward heuristics are superior to the more complex text-analysis-based algorithms. Not only are the heuristics significantly faster to compute, they also deliver more accurate results when estimating commit sizes. Based on this experience, we design and present an algorithm that improves on the heuristics, can be computed equally fast, and is more accurate than any of the prior approaches.},
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address = {Berlin, Heidelberg},
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author = {Philipp Hofmann and Dirk Riehle},
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bookTitle = {{Open Source Ecosystems: Diverse Communities Interacting: 5th IFIP WG 2.13 International Conference on Open Source Systems, OSS 2009, Sk\"{o}vde, Sweden, June 3-6, 2009. Proceedings}},
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doi = {10.1007/978-3-642-02032-2_11},
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editor = {Cornelia Boldyreff and Kevin Crowston and Bj\"{o}rn Lundell and Anthony I. Wasserman},
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isbn = {978-3-642-02032-2},
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pages = {105--115},
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publisher = {Springer Berlin Heidelberg},
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title = {{Estimating Commit Sizes Efficiently}},
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url = {http://dx.doi.org/10.1007/978-3-642-02032-2_11},
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year = {2009},
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}

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