@conference {579,
	title = {Estimating Commit Sizes Efficiently},
	booktitle = {OSS2009: Open Source Ecosystems: Diverse Communities Interacting (IFIP 2.13)},
	series = {IFIP Advances in Information and Communication Technology },
	volume = {299/2009},
	year = {2009},
	month = {2009///},
	pages = {105 - 115},
	publisher = {Springer},
	organization = {Springer},
	chapter = {11},
	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.
},
	issn = {978-3-642-02031-5},
	doi = {http://dx.doi.org/10.1007/978-3-642-02032-2_11},
	attachments = {https://flosshub.org/sites/flosshub.org/files/Estimating\%20Commit\%20Sizes\%20Effciently.pdf},
	author = {Hofmann, Philipp and Dirk Riehle}
}
