@conference {Robles:2014:EDE:2597073.2597107, title = {Estimating Development Effort in Free/Open Source Software Projects by Mining Software Repositories: A Case Study of OpenStack}, booktitle = {Proceedings of the 11th Working Conference on Mining Software Repositories}, series = {MSR 2014}, year = {2014}, pages = {222{\textendash}231}, publisher = {ACM}, organization = {ACM}, address = {New York, NY, USA}, abstract = {Because of the distributed and collaborative nature of free / open source software (FOSS) projects, the development effort invested in a project is usually unknown, even after the software has been released. However, this information is becoming of major interest, especially ---but not only--- because of the growth in the number of companies for which FOSS has become relevant for their business strategy. In this paper we present a novel approach to estimate effort by considering data from source code management repositories. We apply our model to the OpenStack project, a FOSS project with more than 1,000 authors, in which several tens of companies cooperate. Based on data from its repositories and together with the input from a survey answered by more than 100 developers, we show that the model offers a simple, but sound way of obtaining software development estimations with bounded margins of error. }, keywords = {effort estimation, free software, mining software repositories, open source, openstack}, isbn = {978-1-4503-2863-0}, doi = {10.1145/2597073.2597107}, url = {http://doi.acm.org/10.1145/2597073.2597107}, attachments = {https://flosshub.org/sites/flosshub.org/files/robles_0.pdf}, author = {Gregorio Robles and Gonz{\'a}lez-Barahona, Jes{\'u}s M. and Cervig{\'o}n, Carlos and Capiluppi, Andrea and Izquierdo-Cort{\'a}zar, Daniel} } @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} }