@article {1418,
	title = {Effort estimation of FLOSS projects: a study of the Linux kernel},
	journal = {Empirical Software Engineering},
	year = {2011},
	pages = {1-29},
	abstract = {Empirical research on Free/Libre/Open Source Software (FLOSS) has shown that developers tend to cluster around two main roles: {\textquotedblleft}core{\textquotedblright} contributors differ from {\textquotedblleft}peripheral{\textquotedblright} developers in terms of a larger number of responsibilities and a higher productivity pattern. A further, cross-cutting characterization of developers could be achieved by associating developers with {\textquotedblleft}time slots{\textquotedblright}, and different patterns of activity and effort could be associated to such slots. Such analysis, if replicated, could be used not only to compare different FLOSS communities, and to evaluate their stability and maturity, but also to determine within projects, how the effort is distributed in a given period, and to estimate future needs with respect to key points in the software life-cycle (e.g., major releases). This study analyses the activity patterns within the Linux kernel project, at first focusing on the overall distribution of effort and activity within weeks and days; then, dividing each day into three 8-hour time slots, and focusing on effort and activity around major releases. Such analyses have the objective of evaluating effort, productivity and types of activity globally and around major releases. They enable a comparison of these releases and patterns of effort and activities with traditional software products and processes, and in turn, the identification of company-driven projects (i.e., working mainly during office hours) among FLOSS endeavors. The results of this research show that, overall, the effort within the Linux kernel community is constant (albeit at different levels) throughout the week, signalling the need of updated estimation models, different from those used in traditional 9am{\textendash}5pm, Monday to Friday commercial companies. It also becomes evident that the activity before a release is vastly different from after a release, and that the changes show an increase in code complexity in specific time slots (notably in the late night hours), which will later require additional maintenance efforts.},
	keywords = {complexity, effort estimation, Effort models, mining software repositories, open source software},
	issn = {1573-7616},
	doi = {10.1007/s10664-011-9191-7},
	url = {http://www.springerlink.com/content/612r616k8t52m867/fulltext.html},
	author = {Capiluppi, Andrea and Izquierdo-Cort{\'a}zar, Daniel}
}
