@conference {Passos:2014:DFA:2597073.2597124,
	title = {A Dataset of Feature Additions and Feature Removals from the Linux Kernel},
	booktitle = {Proceedings of the 11th Working Conference on Mining Software Repositories},
	series = {MSR 2014},
	year = {2014},
	pages = {376{\textendash}379},
	publisher = {ACM},
	organization = {ACM},
	address = {New York, NY, USA},
	abstract = {This paper describes a dataset of feature additions and removals in the Linux kernel evolution history, spanning over seven years of kernel development. Features, in this context, denote configurable system options that users select when creating customized kernel images. The provided dataset is the largest corpus we are aware of capturing feature additions and removals, allowing researchers to assess the kernel evolution from a feature-oriented point-of-view. Furthermore, the dataset can be used to better understand how features evolve over time, and how different artifacts change as a result. One particular use of the dataset is to provide a real-world case to assess existing support for feature traceability and evolution. In this paper, we detail the dataset extraction process, the underlying database schema, and example queries. The dataset is directly available at our Bitbucket repository: https://bitbucket.org/lpassos/kconfigdb
},
	keywords = {evolution, linux, msr data showcase, Traceability, Version Control History},
	isbn = {978-1-4503-2863-0},
	doi = {10.1145/2597073.2597124},
	url = {http://doi.acm.org/10.1145/2597073.2597124},
	attachments = {https://flosshub.org/sites/flosshub.org/files/kernel.pdf},
	author = {Passos, Leonardo and Czarnecki, Krzysztof}
}
@conference {954,
	title = {Clones: What is that smell?},
	booktitle = {2010 7th IEEE Working Conference on Mining Software Repositories (MSR 2010)2010 7th IEEE Working Conference on Mining Software Repositories (MSR 2010)},
	year = {2010},
	pages = {72 - 81},
	publisher = {IEEE},
	organization = {IEEE},
	address = {Cape Town, South Africa},
	abstract = {Clones are generally considered bad programming practice in software engineering folklore. They are identified as a bad smell and a major contributor to project maintenance difficulties. Clones inherently cause code bloat, thus increasing project size and maintenance costs. In this work, we try to validate the conventional wisdom empirically to see whether cloning makes code more defect prone. This paper analyses relationship between cloning and defect proneness. We find that, first, the great majority of bugs are not significantly associated with clones. Second, we find that clones may be less defect prone than non-cloned code. Finally, we find little evidence that clones with more copies are actually more error prone. Our findings do not support the claim that clones are really a "bad smell". Perhaps we can clone, and breathe easy, at the same time.},
	keywords = {apache, bug fix revisions, bugs, clone, evolution, gimp, nautilus, scm, source code},
	isbn = {978-1-4244-6802-7},
	doi = {10.1109/MSR.2010.5463343},
	attachments = {https://flosshub.org/sites/flosshub.org/files/72rahman2010cws.pdf},
	author = {Rahman, Foyzur and Christian Bird and Devanbu, Premkumar}
}
@conference {1258,
	title = {Exploring Complexity in Open Source Software: Evolutionary Patterns, Antecedents, and Outcomes},
	booktitle = {2010 43rd Hawaii International Conference on System Sciences (HICSS 2010)},
	year = {2010},
	note = {"The sample of projects was drawn from SourceForge"
"projects were selected that were built with C++."
"Applying the selection criteria generated a total of 108 projects for analysis"
"Scientific Toolwork{\textquoteright}s Understand (version 1.4)"},
	pages = {1 - 11},
	publisher = {IEEE},
	organization = {IEEE},
	address = {Honolulu, Hawaii, USA},
	abstract = {Software complexity is important to researchers and managers, yet much is unknown about how complexity evolves over the life of a software application and whether different dimensions of software complexity may exhibit similar or different evolutionary patterns. Using cross-sectional and longitudinal data on a sample of 108 open source projects, this research investigated how the complexity of open source project releases varied throughout the life of the project. Functional data analysis was applied to the release histories of the projects and recurring evolutionary patterns were derived. There were projects that saw little evolution, according to their measures of size and structural complexity. However, projects that displayed some evolution often differed on the pattern of evolution depending on whether size or structural complexity was examined. Factors that contribute to and result from the patterns of complexity were evaluated, and implications for research and practice are presented.},
	keywords = {complexity, evolution, fda, life cycle, sourceforge, srda},
	isbn = {978-1-4244-5509-6},
	doi = {10.1109/HICSS.2010.198},
	attachments = {https://flosshub.org/sites/flosshub.org/files/10-07-02.pdf},
	author = {Darcy, David P. and Daniel, Sherae L. and Stewart, Katherine J.}
}
@conference {1217,
	title = {Trends That Affect Temporal Analysis Using SourceForge Data},
	booktitle = {5th Workshop on Public Data about Software Development (WoPDaSD 2010)},
	year = {2010},
	note = {"In this paper we examine some of the limitations of artifact data by specifically addressing the applicability of SourceForge data to the study of project evolution."

"For our analysis we examine 9,997 Production/Stable or Maintenance phase projects stored in CVS on SourceForge and extracted in October of 2006 [5]"},
	abstract = {SourceForge is a valuable source of software artifact data for researchers who study project evolution and developer behavior. However, the data exhibit patterns that may bias temporal analyses. Most notable are cliff walls in project source code repository timelines, which indicate large commits that are out of character for the given project. These cliff walls often hide significant periods of development and developer collaboration{\textemdash}a threat to studies that rely on SourceForge repository data. We demonstrate how to identify these cliff walls, discuss reasons for their appearance, and propose preliminary measures for mitigating their effects in evolution-oriented studies.},
	keywords = {cliff walls, committers, cvs, evolution, growth, source code, sourceforge, time, time series},
	attachments = {https://flosshub.org/sites/flosshub.org/files/wopdasd001.pdf},
	author = {MacLean, Alexander C. and Pratt, Landon J. and Krein, Jonathan L. and Knutson, Charles D.}
}
@conference {941,
	title = {Evolution of the core team of developers in libre software projects},
	booktitle = {2009 6th IEEE International Working Conference on Mining Software Repositories (MSR)2009 6th IEEE International Working Conference on Mining Software Repositories},
	year = {2009},
	pages = {167 - 170},
	publisher = {IEEE},
	organization = {IEEE},
	address = {Vancouver, BC, Canada},
	abstract = {In many libre (free, open source) software projects, most of the development is performed by a relatively small number of persons, the "core team". The stability and permanence of this group of most active developers is of great importance for the evolution and sustainability of the project. In this position paper we propose a quantitative methodology to study the evolution of core teams by analyzing information from source code management repositories. The most active developers in different periods are identified, and their activity is calculated over time, looking for core team evolution patterns.},
	keywords = {core, cvs, cvsanaly, developers, evolution, gimp, scm},
	isbn = {978-1-4244-3493-0},
	doi = {10.1109/MSR.2009.5069497},
	attachments = {https://flosshub.org/sites/flosshub.org/files/167core-evolution.pdf},
	author = {Gregorio Robles and Jesus M. Gonzalez-Barahona and Herraiz, Israel}
}
@conference {1518,
	title = {Studying the use of developer IRC meetings in open source projects},
	booktitle = {2009 IEEE International Conference on Software Maintenance (ICSM)},
	year = {2009},
	pages = {147 - 156},
	publisher = {IEEE},
	organization = {IEEE},
	address = {Edmonton, AB, Canada},
	abstract = {Open source developers communicate with each other via various online outlets. Thus far, mailing lists have been the main coordination mechanism. However, our previous study shows that the use of developer IRC meetings is increasing in recent years. In this paper, we perform a study on the IRC meetings of two large open source projects: the GTK+ and Evolution projects. We explore three dimensions: who participates in the meetings, what do they discuss and how do they run the meetings. We find (1) that a small and stable number of the participants contribute the majority of messages in meetings, (2) that there are commonly discussed topics as well as project specific topics (3) that meeting styles vary across different projects.},
	keywords = {evolution, gtk, irc},
	isbn = {978-1-4244-4897-5},
	doi = {10.1109/ICSM.2009.5306333},
	url = {http://sail.cs.queensu.ca/publications/pubs/icsm2009_shihab.pdf},
	author = {Shihab, Emad and Zhen Ming Jiang and Hassan, Ahmed E.}
}
@article {10.1109/HICSS.2009.1014,
	title = {Using Software Archaeology to Measure Knowledge Loss in Software Projects Due to Developer Turnover},
	journal = {2009 42nd Hawaii International Conference on System Sciences (HICSS 2009)},
	year = {2009},
	pages = {1-10},
	publisher = {IEEE Computer Society},
	address = {Los Alamitos, CA, USA},
	abstract = {Developer turnover can result in a major problem when developing software. When senior developers abandon a software project, they leave a knowledge gap that has to be managed. In addition, new (junior) developers require some time in order to achieve the desired level of productivity. In this paper, we present a methodology to measure the effect of knowledge loss due to developer turnover in software projects. For a given software project, we measure the quantity of code that has been authored by developers that do not belong to the current development team, which we define as orphaned code. Besides, we study how orphaned code is managed by the project. Our methodology is based on the concept of software archaeology, a derivation of software evolution. As case studies we have selected four FLOSS (free, libre, open source software) projects, from purely driven by volunteers to company-supported. The application of our methodology to these case studies will give insight into the turnover that these projects suffer and how they have managed it and shows that this methodology is worth being augmented in future research.},
	keywords = {attrition, case study, developers, evince, evolution, gimp, growth, knowledge collaboration, lines of code, nautilus, quality, sloc, turnover},
	isbn = {978-0-7695-3450-3},
	doi = {http://doi.ieeecomputersociety.org/10.1109/HICSS.2009.1014},
	attachments = {https://flosshub.org/sites/flosshub.org/files/07-07-08.pdf},
	author = {Izquierdo-Cortazar, Daniel and Gregorio Robles and Ortega, Felipe and Jesus M. Gonzalez-Barahona}
}
@conference {970,
	title = {Determinism and evolution},
	booktitle = {Proceedings of the 2008 international workshop on Mining software repositories  - MSR {\textquoteright}08},
	year = {2008},
	month = {05/2008},
	pages = {1-9},
	publisher = {ACM Press},
	organization = {ACM Press},
	address = {New York, New York, USA},
	abstract = {It has been proposed that software evolution follows a Self-Organized Criticality (SOC) dynamics. This fact is supported by the presence of long range correlations in the time series of the number of changes made to the source code over time. Those long range correlations imply that the current state of the project was determined time ago. In other words, the evolution of the software project is governed by a sort of determinism. But this idea seems to contradict intuition. To explore this apparent contradiction, we have performed an empirical study on a sample of 3,821 libre (free, open source) software projects, finding that their evolution projects is short range correlated. This suggests that the dynamics of software evolution may not be SOC, and therefore that the past of a project does not determine its future except for relatively short periods of time, at least for libre software.},
	keywords = {changes, evolution, source code, sourceforge},
	isbn = {9781605580241},
	doi = {10.1145/1370750.1370752},
	attachments = {https://flosshub.org/sites/flosshub.org/files/p1-herraiz.pdf},
	author = {Gonz{\'a}lez-Barahona, Jes{\'u}s M. and Gregorio Robles and Herraiz, Israel}
}
@conference {973,
	title = {On the relation of refactorings and software defect prediction},
	booktitle = {Proceedings of the 2008 international workshop on Mining software repositories  - MSR {\textquoteright}08},
	year = {2008},
	month = {05/2008},
	pages = {35-38},
	publisher = {ACM Press},
	organization = {ACM Press},
	address = {New York, New York, USA},
	abstract = {This paper analyzes the influence of evolution activities such as refactoring on software defects. In a case study of five open source projects we used attributes of software evolution to predict defects in time periods of six months. We use versioning and issue tracking systems to extract 110 data mining features, which are separated into refactoring and non-refactoring related features. These features are used as input into classification algorithms that create prediction models for software defects. We found out that refactoring related features as well as non-refactoring related features lead to high quality prediction models. Additionally, we discovered that refactorings and defects have an inverse correlation: The number of software defects decreases, if the number of refactorings increased in the preceding time period. As a result, refactoring should be a significant part of both bug fixes and other evolutionary changes to reduce software defects.},
	keywords = {argouml, bug fixing, bug reports, defects, evolution, jboss, liferay, prediction, refactoring, spring, weka, xdoclet},
	isbn = {9781605580241},
	doi = {10.1145/1370750.1370759},
	attachments = {https://flosshub.org/sites/flosshub.org/files/p35-ratzinger.pdf},
	author = {Sigmund, Thomas and Gall, Harald C. and Ratzinger, Jacek}
}
@article {1392,
	title = {Self-organization process in open-source software: An empirical study},
	journal = {Information and Software Technology},
	volume = {50},
	year = {2008},
	month = {4/2008},
	pages = {361 - 374},
	abstract = {Software systems must continually evolve to adapt to new functional requirements or quality requirements to remain competitive in the marketplace. However, different software systems follow different strategies to evolve, affecting both the release plan and the quality of these systems. In this paper, software evolution is considered as a self-organization process and the difference between closed-source software and open-source software is discussed in terms of self-organization. In particular, an empirical study of the evolution of Linux from version 2.4.0 to version 2.6.13 is reported. The study shows how open-source software systems self-organize to adapt to functional requirements and quality requirements.},
	keywords = {Empirical study;, evolution, linux, requirements, Self-organization, software evolution},
	issn = {09505849},
	doi = {10.1016/j.infsof.2007.02.018},
	url = {http://www.sciencedirect.com/science/article/pii/S0950584907000225},
	author = {Yu, Liguo}
}
@conference {Hindle:2008:LCT:1370750.1370773,
	title = {What do large commits tell us?: a taxonomical study of large commits},
	booktitle = {Proceedings of the 2008 international working conference on Mining software repositories},
	series = {MSR {\textquoteright}08},
	year = {2008},
	month = {05/2008},
	pages = {99{\textendash}108},
	publisher = {ACM},
	organization = {ACM},
	address = {New York, NY, USA},
	abstract = {Research in the mining of software repositories has frequently ignored commits that include a large number of files (we call these large commits). The main goal of this paper is to understand the rationale behind large commits, and if there is anything we can learn from them. To address this goal we performed a case study that included the manual classification of large commits of nine open source projects. The contributions include a taxonomy of large commits, which are grouped according to their intention. We contrast large commits against small commits and show that large commits are more perfective while small commits are more corrective. These large commits provide us with a window on the development practices of maintenance teams.},
	keywords = {boost, bug fixing, egroupware, enlightenment, evolution, firebird, large commits, maintenance, mysql, postgresql, samba, software evolution, source control system, spring},
	isbn = {978-1-60558-024-1},
	doi = {http://doi.acm.org/10.1145/1370750.1370773},
	url = {http://doi.acm.org/10.1145/1370750.1370773},
	attachments = {https://flosshub.org/sites/flosshub.org/files/p99-hindle.pdf},
	author = {Hindle, Abram and Daniel M. German and Holt, Ric}
}
@article {Wang:2007:MEO:1317471.1317479,
	title = {Measuring the evolution of open source software systems with their communities},
	journal = {SIGSOFT Softw. Eng. Notes},
	volume = {32},
	year = {2007},
	note = {"1. M1: The number of modules in software system at a series of specific moment.
2. CD: The number of developers (code contributors) at a series of specific moment.
3. MC: The correlation of M1 and CD."
"We get the information of Modules from the Launchpad[1] which is a distributed collaborative infrastructure for Ubuntu and other open source software development. Ubuntu mainly grows though a manner of adding new packages. So, we treat packages as the modules we mention before. In Ubuntu community, some members are in charge of auditing the packages and add them to Ubuntu, here developers are refers them."},
	month = {November},
	publisher = {ACM},
	address = {New York, NY, USA},
	abstract = {Open Source Software (OSS) has become the subject of much commercial and academic interest in last few years. As traditional software, OSS also evolves to fulfill the need of stakeholders. Therefore, providing quantitative metrics for OSS evolution has also become an urgent issue. However, most existing studies of software evolution have been performed on systems developed within a single company using traditional management techniques. These metrics models are inadequate to measure OSS evolution. In this paper, we describe a preliminary evolution metrics set for evaluating OSS. The most significant novelty of this model is that it takes specific properties of Open Source Community (OSC) into consideration. In another word, we measure the evolution of OSS and OSC together. We also provide a lightweight case study on Ubuntu project using this metrics set. We find out that the Open Source Community and its members also play essential role in OSS evolution. We expect this metrics model can bring better understandings and explanations of phenomena in open source development and evolution.},
	keywords = {evolution, launchpad, metrics, open source community, open source software, Ubuntu},
	issn = {0163-5948},
	doi = {http://doi.acm.org/10.1145/1317471.1317479},
	url = {http://doi.acm.org/10.1145/1317471.1317479},
	author = {Yi Wang and Defeng Guo and Shi, Huihui}
}
@conference {994,
	title = {Recommending Emergent Teams},
	booktitle = {Fourth International Workshop on Mining Software Repositories (MSR{\textquoteright}07:ICSE Workshops 2007)},
	year = {2007},
	pages = {5 - 5},
	publisher = {IEEE},
	organization = {IEEE},
	address = {Minneapolis, MN, USA},
	abstract = {To build successful complex software systems, developers must collaborate with each other to solve issues. To facilitate this collaboration, specialized tools, such as chat and screen sharing, are being integrated into development environments. Currently, these tools require a developer to maintain a list of other developers with whom they may wish to communicate and to determine who within this list has expertise for a specific situation. For large, dynamic projects, like several successful open-source projects, these requirements place an unreasonable burden on the developer. In this paper, we show how the structure of a team emerges from how developers change software artifacts. We introduce the Emergent Expertise Locator (EEL) that uses emergent team information to propose experts to a developer within their development environment as the developer works. We found that EEL produces, on average, results with higher precision and higher recall than an existing heuristic for expertise recommendation.},
	keywords = {bugzilla, developers, eclipse, evolution, expertise, Firefox, teams},
	isbn = {0-7695-2950-X},
	doi = {10.1109/MSR.2007.27},
	attachments = {https://flosshub.org/sites/flosshub.org/files/28300005.pdf},
	author = {Minto, Shawn and Murphy, Gail C.}
}
@conference {1004,
	title = {Release Pattern Discovery via Partitioning: Methodology and Case Study},
	booktitle = {Fourth International Workshop on Mining Software Repositories (MSR{\textquoteright}07:ICSE Workshops 2007)},
	year = {2007},
	pages = {19 - 19},
	publisher = {IEEE},
	organization = {IEEE},
	address = {Minneapolis, MN, USA},
	abstract = {The development of Open Source systems produces a variety of software artifacts such as source code, version control records, bug reports, and email discussions. Since the development is distributed across different tool environments and developer practices, any analysis of project behavior must be inferred from whatever common artifacts happen to be available. In this paper, we propose an approach to characterizing a project{\textquoteright}s behavior around the time of major and minor releases; we do this by partitioning the observed activities, such as artifact check-ins, around the dates of major and minor releases, and then look for recognizable patterns. We validate this approach by means of a case study on the MySQL database system; in this case study, we found patterns which suggested MySQL was behaving consistently within itself. These patterns included testing and documenting that took place more before a release than after and that the rate of source code changes dipped around release time.},
	keywords = {bitkeeper, bt2csv, cvs, evolution, mysql, releases, revision history, scm, softchange, version control},
	isbn = {0-7695-2950-X},
	doi = {10.1109/MSR.2007.28},
	attachments = {https://flosshub.org/sites/flosshub.org/files/28300019.pdf},
	author = {Hindle, Abram and Godfrey, Michael W. and Holt, Richard C.}
}
@conference {1006,
	title = {Towards a Theoretical Model for Software Growth},
	booktitle = {Fourth International Workshop on Mining Software Repositories (MSR{\textquoteright}07:ICSE Workshops 2007)},
	year = {2007},
	pages = {21 - 21},
	publisher = {IEEE},
	organization = {IEEE},
	address = {Minneapolis, MN, USA},
	abstract = {Software growth (and more broadly, software evolution) is usually considered in terms of size or complexity of source code. However in different studies, usually different metrics are used, which make it difficult to compare approaches and results. In addition, not all metrics are equally easy to calculate for a given source code, which leads to the question of which one is the easiest to calculate without losing too much information. To address both issues, in this paper present a comprehensive study, based on the analysis of about 700,000 C source code files, calculating several size and complexity metrics for all of them. For this sample, we have found double Pareto statistical distributions for all metrics considered, and a high correlation between any two of them. This would imply that any model addressing software growth should produce this Pareto distributions, and that analysis based on any of the considered metrics should show a similar pattern, provided the sample of files considered is large enough.},
	keywords = {C, complexity, evolution, freebsd, growth, halstead, lines of code, loc, mccabe, metrics, scm, size, sloc, sloccount, source code},
	isbn = {0-7695-2950-X},
	doi = {10.1109/MSR.2007.31},
	attachments = {https://flosshub.org/sites/flosshub.org/files/28300021.pdf},
	author = {Herraiz, Israel and Jesus M. Gonzalez-Barahona and Gregorio Robles}
}
@conference {1009,
	title = {Using Software Distributions to Understand the Relationship among Free and Open Source Software Projects},
	booktitle = {Fourth International Workshop on Mining Software Repositories (MSR{\textquoteright}07:ICSE Workshops 2007)},
	year = {2007},
	pages = {24 - 24},
	publisher = {IEEE},
	organization = {IEEE},
	address = {Minneapolis, MN, USA},
	abstract = {Success in the open source software world has been measured in terms of metrics such as number of downloads, number of commits, number of lines of code, number of participants, etc. These metrics tend to discriminate towards applications that are small and tend to evolve slowly. A problem is, however, how to identify applications in these latter categories that are important. Software distributions specify the dependencies needed to build and to run a given software application. We use this information to create a dependency graph of the applications contained in such a distribution. We explore the characteristics of this graph, and use it to define some metrics to quantify the dependencies (and dependents) of a given software application. We demonstrate that some applications that are invisible to the final user (such as libraries) are widely used by end-user applications. This graph can be used as a proxy to measure success of small, slowly evolving free and open source software.},
	keywords = {dependencies, evolution, fink, metrics},
	isbn = {0-7695-2950-X},
	doi = {10.1109/MSR.2007.32},
	attachments = {https://flosshub.org/sites/flosshub.org/files/28300024.pdf},
	author = {Daniel M. German}
}
@conference {D{\textquoteright}Ambros:2006:AER:1137983.1138029,
	title = {Applying the evolution radar to PostgreSQL},
	booktitle = {Proceedings of the 2006 international workshop on Mining software repositories},
	series = {MSR {\textquoteright}06},
	year = {2006},
	pages = {177{\textendash}178},
	publisher = {ACM},
	organization = {ACM},
	address = {New York, NY, USA},
	keywords = {cvs, documentation, evolution, evolution radar, logical coupling, makefile, mining challenge, msr challenge, postgresql, re-engineering, refactoring, release history, rhdb, source code, version control, visualization},
	isbn = {1-59593-397-2},
	doi = {http://doi.acm.org/10.1145/1137983.1138029},
	url = {http://doi.acm.org/10.1145/1137983.1138029},
	attachments = {https://flosshub.org/sites/flosshub.org/files/177ApplyingEvolution.pdf},
	author = {D{\textquoteright}Ambros, Marco and Lanza, Michele}
}
@conference {686,
	title = {Contributor Turnover in Libre Software Projects},
	booktitle = {OSS2006: Open Source Systems (IFIP 2.13)},
	series = {IFIP International Federation for Information Processing},
	year = {2006},
	pages = {273 - 286},
	publisher = {Springer},
	organization = {Springer},
	abstract = {A common problem that management faces in software companies is the high instability of their staff. In libre (free, open source) software projects, the permanence of developers is also an open issue, with the potential of causing problems amplified by the self-organizing nature that most of them exhibit. Hence, human resources in libre software projects are even more difficult to manage: developers are in most cases not bound by a contract and, in addition, there is not a real management structure concerned about this problem. This raises some interesting questions with respect to the composition of development teams in libre software projects, and how they evolve over time. There are projects lead by their original founders (some sort of {\textquotedblleft}code gods{\textquotedblright}), while others are driven by several different developer groups over time (i.e. the project {\textquotedblleft}regenerates{\textquotedblright} itself). 
In this paper, we propose a quantitative methodology, based on the analysis of the activity in the source code management repositories, to study how these processes (developers leaving, developers joining) affect libre software projects. The basis of it is the analysis of the composition of the core group, the group of developers most active in a project, for several time lapses. We will apply this methodology to several large, well-known libre software projects, and show how it can be used to characterize them. In addition, we will discuss the lessons that can be learned, and the validity of our proposal.
},
	keywords = {apache, committers, core, cvs, cvsanaly, developers, evolution, freebsd, gimp, gnome, kde, mono, mozilla},
	doi = {http://dx.doi.org/10.1007/0-387-34226-5_28},
	attachments = {https://flosshub.org/sites/flosshub.org/files/Contributor\%20Turnover\%20in\%20Libre\%20Software\%20Projects.pdf},
	author = {Gregorio Robles and Gonzalez-Barahona, Jesus}
}
@conference {D{\textquoteright}Ambros:2006:ERV:1137983.1137992,
	title = {The evolution radar: visualizing integrated logical coupling information},
	booktitle = {Proceedings of the 2006 international workshop on Mining software repositories},
	series = {MSR {\textquoteright}06},
	year = {2006},
	pages = {26{\textendash}32},
	publisher = {ACM},
	organization = {ACM},
	address = {New York, NY, USA},
	abstract = {In software evolution research logical coupling has extensively been used to recover the hidden dependencies between source code artifacts. They would otherwise go lost because of the file-based nature of current versioning systems. Previous research has dealt with low-level couplings between files, leading to an explosion of data to be analyzed, or has abstracted the logical couplings to module level, leading to a loss of detailed information. In this paper we propose a visualization-based approach which integrates both file-level and module-level logical coupling information. This not only facilitates an in-depth analysis of the logical couplings at all granularity levels, it also leads to a precise characterization of the system modules in terms of their logical coupling dependencies.},
	keywords = {change management, cvs, evolution, logical coupling, mozilla, scm, source code, thunderbird, tinderbox, visualization},
	isbn = {1-59593-397-2},
	doi = {http://doi.acm.org/10.1145/1137983.1137992},
	url = {http://doi.acm.org/10.1145/1137983.1137992},
	attachments = {https://flosshub.org/sites/flosshub.org/files/26TheEvolutionRadar.pdf},
	author = {D{\textquoteright}Ambros, Marco and Lanza, Michele and Lungu, Mircea}
}
@conference {Jiang:2006:EEC:1137983.1138030,
	title = {Examining the evolution of code comments in PostgreSQL},
	booktitle = {Proceedings of the 2006 international workshop on Mining software repositories},
	series = {MSR {\textquoteright}06},
	year = {2006},
	pages = {179{\textendash}180},
	publisher = {ACM},
	organization = {ACM},
	address = {New York, NY, USA},
	abstract = {It is common, especially in large software systems, for developers to change code without updating its associated comments due to their unfamiliarity with the code or due to time constraints. This is a potential problem since outdated comments may confuse or mislead developers who perform future development. Using data recovered from CVS, we study the evolution of code comments in the PostgreSQL project. Our study reveals that over time the percentage of commented functions remains constant except for early fluctuation due to the commenting style of a particular active developer.},
	keywords = {code comments, comments, cvs, evolution, functions, maintenance, mining challenge, msr challenge, postgresql, software evolution, software maintenance, source code},
	isbn = {1-59593-397-2},
	doi = {http://doi.acm.org/10.1145/1137983.1138030},
	url = {http://doi.acm.org/10.1145/1137983.1138030},
	attachments = {https://flosshub.org/sites/flosshub.org/files/179ExaminingTheEvolution.pdf},
	author = {Zhen Ming Jiang and Hassan, Ahmed E.}
}
@conference {Kim:2006:MPE:1137983.1137995,
	title = {Micro pattern evolution},
	booktitle = {Proceedings of the 2006 international workshop on Mining software repositories},
	series = {MSR {\textquoteright}06},
	year = {2006},
	pages = {40{\textendash}46},
	publisher = {ACM},
	organization = {ACM},
	address = {New York, NY, USA},
	abstract = {When analyzing the evolution history of a software project, we wish to develop results that generalize across projects. One approach is to analyze design patterns, permitting characteristics of the evolution to be associated with patterns, instead of source code. Traditional design patterns are generally not amenable to reliable automatic extraction from source code, yet automation is crucial for scalable evolution analysis. Instead, we analyze {\textquotedblleft}micro pattern{\textquotedblright} evolution; patterns whose abstraction level is closer to source code, and designed to be automatically extractable from Java source code or bytecode. We perform micro-pattern evolution analysis on three open source projects, ArgoUML, Columba, and jEdit to identify micro pattern frequencies, common kinds of pattern evolution, and bug-prone patterns. In all analyzed projects, we found that the micro patterns of Java classes do not change often. Common bug- prone pattern evolution kinds are {\textquoteleft}Pool {\textrightarrow} Pool{\textquoteright}, {\textquoteleft}Implementor {\textrightarrow} NONE{\textquoteright}, and {\textquoteleft}Sampler {\textrightarrow} Sampler{\textquoteright}. Among all pattern evolution	kinds,{\textquoteleft}Box{\textquoteright},{\textquoteleft}CompoundBox{\textquoteright},	{\textquoteleft}Pool{\textquoteright}, {\textquoteleft}CommonState{\textquoteright}, and {\textquoteleft}Outline{\textquoteright} micro patterns have high bug rates, but they have low frequencies and a small number of changes. The pattern evolution kinds that are bug-prone are somewhat similar across projects. The bug-prone pattern evolution kinds of two different periods of the same project are almost identical.},
	keywords = {argouml, bugs, columba, design patterns, evolution, extraction, java, jedit, source code},
	isbn = {1-59593-397-2},
	doi = {http://doi.acm.org/10.1145/1137983.1137995},
	url = {http://doi.acm.org/10.1145/1137983.1137995},
	attachments = {https://flosshub.org/sites/flosshub.org/files/40MicroPattern.pdf},
	author = {Kim, Sunghun and Pan, Kai and Whitehead,Jr., E. James}
}
@conference {Robles:2006:MLS:1137983.1137986,
	title = {Mining large software compilations over time: another perspective of software evolution},
	booktitle = {Proceedings of the 2006 international workshop on Mining software repositories},
	series = {MSR {\textquoteright}06},
	year = {2006},
	pages = {3{\textendash}9},
	publisher = {ACM},
	organization = {ACM},
	address = {New York, NY, USA},
	abstract = {With the success of libre (free, open source) software, a new type of software compilation has become increasingly common. Such compilations, often referred to as {\textquoteright}distributions{\textquoteright}, group hundreds, if not thousands, of software applications and libraries written by independent parties into an integrated system. Software compilations raise a number of questions that have not been targeted so far by software evolution, which usually focuses on the evolution of single applications. Undoubtedly, the challenges that software compilations face differ from those found in single software applications. Nevertheless, it can be assumed that both, the evolution of applications and that of software compilations, have similarities and dependencies.In this sense, we identify a dichotomy, common to that in economics, of software evolution in the small (micro-evolution) and in the large (macro-evolution). The goal of this paper is to study the evolution of a large software compilation, mining the publicly available repository of a well-known Linux distribution, Debian. We will therefore investigate changes related to hundreds of millions of lines of code over seven years. The aspects that will be covered in this paper are size (in terms of number of packages and of number of lines of code), use of programming languages, maintenance of packages and file sizes.},
	keywords = {debian, distributions, evolution, large software collections, lines of code, loc, metrics, mining software repositories, size, sloc, sloccount, software evolution, software integrators},
	isbn = {1-59593-397-2},
	doi = {http://doi.acm.org/10.1145/1137983.1137986},
	url = {http://doi.acm.org/10.1145/1137983.1137986},
	attachments = {https://flosshub.org/sites/flosshub.org/files/3miningLarge.pdf},
	author = {Gregorio Robles and Jesus M. Gonzalez-Barahona and Martin Michlmayr and Amor, Juan Jose}
}
@conference {WeiBgerber:2006:MRA:1137983.1138028,
	title = {Mining refactorings in ARGOUML},
	booktitle = {Proceedings of the 2006 international workshop on Mining software repositories},
	series = {MSR {\textquoteright}06},
	year = {2006},
	note = {"To see if refactorings in ARGOUML have an effect on the occurrence of new bugs and on communication between the developers, we relate the refactorings to bug reports in ISSUEZILLA respectively to mails on the developer mailing list. "},
	pages = {175{\textendash}176},
	publisher = {ACM},
	organization = {ACM},
	address = {New York, NY, USA},
	abstract = {In this paper we combine the results of our refactoring reconstruc- tion technique with bug, mail and release information to perform process and bug analyses of the ARGOUML CVS archive.},
	keywords = {argouml, bug tracking, bugs, cvs, email, evolution, mining challenge, msr challenge, re-engineering, refactoring, release history},
	isbn = {1-59593-397-2},
	doi = {http://doi.acm.org/10.1145/1137983.1138028},
	url = {http://doi.acm.org/10.1145/1137983.1138028},
	attachments = {https://flosshub.org/sites/flosshub.org/files/175MiningRefactorings.pdf},
	author = {Wei{\ss}gerber, Peter and Diehl, Stephan and G{\"o}rg, Carsten}
}
@conference {Voinea:2006:MSR:1137983.1138024,
	title = {Mining software repositories with CVSgrab},
	booktitle = {Proceedings of the 2006 international workshop on Mining software repositories},
	series = {MSR {\textquoteright}06},
	year = {2006},
	pages = {167{\textendash}168},
	publisher = {ACM},
	organization = {ACM},
	address = {New York, NY, USA},
	keywords = {argouml, cvs, cvsgrab, evolution, mining challenge, msr challenge, postgresql, software visualization, source code, team, visualization},
	isbn = {1-59593-397-2},
	doi = {http://doi.acm.org/10.1145/1137983.1138024},
	url = {http://doi.acm.org/10.1145/1137983.1138024},
	attachments = {https://flosshub.org/sites/flosshub.org/files/167MiningSoftware.pdf},
	author = {Voinea, Lucian and Telea, Alexandru}
}
@article {2006,
	title = {Opportunities and Challenges Applying Functional Data Analysis to the Study of Open Source Software Evolution},
	journal = {Statistical Science},
	volume = {21},
	number = {2},
	year = {2006},
	note = {"As part of a larger project, data were collected on 105 OSS	projects hosted online at Sourceforge (sf.net)." "...we limited our data collection to projects that use only the Java programming language and were listed in the Internet and System Networking domains." "... only including these projects that use an OSI approved license..." "had to have posted at least one file on the Sourceforge site as of the time of our initial project selection Fall 2002" "Data were collected on the published release history of each project thatmet the screening criteria. Each release of each project was
analyzed to calculate CplXLCoh. The size of each release was measured using a calculation of the number of lines of code (LOC)"},
	pages = {167-178},
	publisher = {Institute of Mathematical Statistics},
	abstract = {This paper explores the application of functional data analysis (FDA) as a means to study the dynamics of software evolution in the open source context. Several challenges in analyzing the data from software projects are discussed, an approach to overcoming those challenges is described, and preliminary results from the analysis of a sample of open source software (OSS) projects are provided. The results demonstrate the utility of FDA for uncovering and categorizing multiple distinct patterns of evolution in the complexity of OSS projects. These results are promising in that they demonstrate some patterns in which the complexity of software decreased as the software grew in size, a particularly novel result. The paper reports preliminary explorations of factors that may be associated with decreasing complexity patterns in these projects. The paper concludes by describing several next steps for this research project as well as some questions for which more sophisticated analytical techniques may be needed.},
	keywords = {complexity, evolution, fda, java, lines of code, loc, release history, scm, size, sourceforge},
	issn = {08834237},
	url = {http://www.jstor.org/stable/27645747},
	author = {Stewart, Katherine J. and Darcy, David P. and Daniel, Sherae L.}
}
@conference {Antoniol:2005:LPC:1083142.1083156,
	title = {Linear predictive coding and cepstrum coefficients for mining time variant information from software repositories},
	booktitle = {Proceedings of the 2005 international workshop on Mining software repositories},
	series = {MSR {\textquoteright}05},
	year = {2005},
	pages = {74-78},
	publisher = {ACM},
	organization = {ACM},
	address = {New York, NY, USA},
	abstract = {This paper presents an approach to recover time variant information from software repositories. It is widely accepted that software evolves due to factors such as defect removal, market opportunity or adding new features. Software evolution details are stored in software repositories which often contain the changes history. On the other hand there is a lack of approaches, technologies and methods to efficiently extract and represent time dependent information. Disciplines such as signal and image processing or speech recognition adopt frequency domain representations to mitigate differences of signals evolving in time. Inspired by time-frequency duality, this paper proposes the use of Linear Predictive Coding (LPC) and Cepstrum coefficients to model time varying software artifact histories. LPC or Cepstrum allow obtaining very compact representations with linear complexity. These representations can be used to highlight components and artifacts evolved in the same way or with very similar evolution patterns. To assess the proposed approach we applied LPC and Cepstral analysis to 211 Linux kernel releases (i.e., from 1.0 to 1.3.100), to identify files with very similar size histories. The approach, the preliminary results and the lesson learned are presented in this paper.},
	keywords = {change history, data mining, evolution, files, kernel, linear predictive coding, linux, lpc, size, software evolution, source code},
	isbn = {1-59593-123-6},
	doi = {http://doi.acm.org/10.1145/1082983.1083156},
	url = {http://doi.acm.org/10.1145/1082983.1083156},
	attachments = {https://flosshub.org/sites/flosshub.org/files/74LinearPredictive.pdf},
	author = {Antoniol, Giuliano and Rollo, Vincenzo Fabio and Venturi, Gabriele}
}
@conference {Fischer:2005:MED:1083142.1083145,
	title = {Mining evolution data of a product family},
	booktitle = {Proceedings of the 2005 international workshop on Mining software repositories},
	series = {MSR {\textquoteright}05},
	year = {2005},
	pages = {12-16},
	publisher = {ACM},
	organization = {ACM},
	address = {New York, NY, USA},
	abstract = {Diversification of software assets through changing requirements impose a constant challenge on the developers and maintainers of large software systems. Recent research has addressed the mining for data in software repositories of single products ranging from fine- to coarse grained analyses. But so far, little attention has been payed to mining data about the evolution of product families. In this work, we study the evolution and commonalities of three variants of the BSD (Berkeley Software Distribution), a large open source operating system. The research questions we tackle are concerned with how to generate high level views of the system discovering and indicating evolutionary highlights. To process the large amount of data, we extended our previously developed approach for storing release history information to support the analysis of product families. In a case study we apply our approach on data from three different code repositories representing about 8.5GB of data and 10 years of active development.},
	keywords = {bsd, change analysis, change history, cvs, evolution, freebsd, netbsd, openbsd, release history, source code, text mining},
	isbn = {1-59593-123-6},
	doi = {http://doi.acm.org/10.1145/1082983.1083145},
	url = {http://doi.acm.org/10.1145/1082983.1083145},
	attachments = {https://flosshub.org/sites/flosshub.org/files/12MiningEvolution.pdf},
	author = {Fischer, Michael and Oberleitner, Johann and Ratzinger, Jacek and Gall, Harald}
}
@conference {Hindle:2005:SFM:1083142.1083161,
	title = {SCQL: a formal model and a query language for source control repositories},
	booktitle = {Proceedings of the 2005 international workshop on Mining software repositories},
	series = {MSR {\textquoteright}05},
	year = {2005},
	pages = {100-104},
	publisher = {ACM},
	organization = {ACM},
	address = {New York, NY, USA},
	abstract = {Source Control Repositories are used in most software projects to store revisions to source code files. These repositories operate at the file level and support multiple users. A generalized formal model of source control repositories is described herein. The model is a graph in which the different entities stored in the repository become vertices and their relationships become edges. We then define SCQL, a first order, and temporal logic based query language for source control repositories. We demonstrate how SCQL can be used to specify some questions and then evaluate them using the source control repositories of five different large software projects.},
	keywords = {evolution, file, gnumeric, modperl, openssl, revision, samba, scm, source code},
	isbn = {1-59593-123-6},
	doi = {http://doi.acm.org/10.1145/1082983.1083161},
	url = {http://doi.acm.org/10.1145/1082983.1083161},
	attachments = {https://flosshub.org/sites/flosshub.org/files/100scql.pdf},
	author = {Hindle, Abram and Daniel M. German}
}
@conference {Neamtiu:2005:USC:1083142.1083143,
	title = {Understanding source code evolution using abstract syntax tree matching},
	booktitle = {Proceedings of the 2005 international workshop on Mining software repositories},
	series = {MSR {\textquoteright}05},
	year = {2005},
	pages = {2-6},
	publisher = {ACM},
	organization = {ACM},
	address = {New York, NY, USA},
	abstract = {Mining software repositories at the source code level can provide a greater understanding of how software evolves. We present a tool for quickly comparing the source code of different versions of a C program. The approach is based on partial abstract syntax tree matching, and can track simple changes to global variables, types and functions. These changes can characterize aspects of software evolution useful for answering higher level questions. In particular, we consider how they could be used to inform the design of a dynamic software updating system. We report results based on measurements of various versions of popular open source programs, including BIND, OpenSSH, Apache, Vsftpd and the Linux kernel.},
	keywords = {abstract syntax trees, apache, bind, evolution, linux, openssh, software evolution, source code, source code analysis, vsftpd},
	isbn = {1-59593-123-6},
	doi = {http://doi.acm.org/10.1145/1082983.1083143},
	url = {http://doi.acm.org/10.1145/1082983.1083143},
	attachments = {https://flosshub.org/sites/flosshub.org/files/2Understanding.pdf},
	author = {Neamtiu, Iulian and Foster, Jeffrey S. and Hicks, Michael}
}
@conference {Kim:2005:UCG:1083142.1083146,
	title = {Using a clone genealogy extractor for understanding and supporting evolution of code clones},
	booktitle = {Proceedings of the 2005 international workshop on Mining software repositories},
	series = {MSR {\textquoteright}05},
	year = {2005},
	pages = {17-23},
	publisher = {ACM},
	organization = {ACM},
	address = {New York, NY, USA},
	abstract = {Programmers often create similar code snippets or reuse existing code snippets by copying and pasting. Code clones {\textemdash}syntactically and semantically similar code snippets{\textemdash}can cause problems during software maintenance because programmers may need to locate code clones and change them consistently. In this work, we investigate (1) how code clones evolve, (2) how many code clones impose maintenance challenges, and (3) what kind of tool or engineering process would be useful for maintaining code clones.
Based on a formal definition of clone evolution, we built a clone genealogy tool that automatically extracts the history of code clones from a source code repository (CVS). Our clone genealogy tool enables several analyses that reveal evolutionary characteristics of code clones. Our initial results suggest that aggressive refactoring may not be the best solution for all code clones; thus, we propose alternative tool solutions that assist in maintaining code clones using clone genealogy information.},
	keywords = {clone, clone detection, cvs, developers, evolution, maintenance, refactoring, source code},
	isbn = {1-59593-123-6},
	doi = {http://doi.acm.org/10.1145/1082983.1083146},
	url = {http://doi.acm.org/10.1145/1082983.1083146},
	attachments = {https://flosshub.org/sites/flosshub.org/files/17Using.pdf},
	author = {Kim, Miryung and Notkin, David}
}
@conference {Sliwerski:2005:CIF:1083142.1083147,
	title = {When do changes induce fixes?},
	booktitle = {Proceedings of the 2005 international workshop on Mining software repositories},
	series = {MSR {\textquoteright}05},
	year = {2005},
	pages = {24-28},
	publisher = {ACM},
	organization = {ACM},
	address = {New York, NY, USA},
	abstract = {As a software system evolves, programmers make changes that sometimes cause problems. We analyze CVS archives for fix-inducing changes{\textemdash}changes that lead to problems, indicated by fixes. We show how to automatically locate fix-inducing changes by linking a version archive (such as CVS) to a bug database (such as BUGZILLA). In a first investigation of the MOZILLA and ECLIPSE history, it turns out that fix-inducing changes show distinct patterns with respect to their size and the day of week they were applied.},
	keywords = {bugzilla, change analysis, cvs, eclipse, evolution, mozilla},
	isbn = {1-59593-123-6},
	doi = {http://doi.acm.org/10.1145/1082983.1083147},
	url = {http://doi.acm.org/10.1145/1082983.1083147},
	attachments = {https://flosshub.org/sites/flosshub.org/files/24WhenDoChanges.pdf},
	author = {Sliwerski, J and Zimmermann, Thomas and Zeller, Andreas}
}
@conference {Xinyi04fourinteresting,
	title = {Four Interesting Ways in Which History Can Teach Us About Software},
	booktitle = {Proceedings of the 2004 international workshop on Mining software repositories  - MSR {\textquoteright}04},
	year = {2004},
	month = {05/2004},
	pages = {58-62},
	abstract = {In this position paper, we outline four kinds of studies that we have undertaken in trying to understand various aspects of a software system{\textquoteright}s evolutionary history. In each instance, the studies have involved detailed examination of real software systems based on {\textquotedblleft}facts{\textquotedblright} extracted from various kinds of source artifact repositories, as well as the development of accompanying tools to aid in the extraction, abstraction, and comprehension processes. We briefly discuss the goals, results, and methodology of each approach.},
	keywords = {ant, apache, change analysis, clone, clone detection, cvs, evolution, gcc, growth, kepler, linux, midworld, mycore, postgresql, source code, version control},
	attachments = {https://flosshub.org/sites/flosshub.org/files/58FourInterestingWays.pdf},
	author = {Michael Godfrey and Xinyi Dong and Cory Kapser and Lijie Zou}
}
@article {1077,
	title = {Profiling an Open Source Project Ecology and Its Programmers},
	journal = {Electronic Markets},
	volume = {14},
	year = {2004},
	month = {6/2004},
	pages = {77 - 88},
	abstract = {While many successful and well-known open source projects produce output of high quality, a general assessment of this development paradigm is still missing. In this paper, an online community of both small and large, successful and failed projects and their programmers is analysed mainly using the version-control data of each project, also according to their productivity and estimation of expended effort. As the results show, there are indeed significant differences between this cooperative development model and the commercial organization of work in the areas explored. Both open source software projects in their size and their programmers{\textquoteright} effort differ significantly, and the evolution of projects{\textquoteright} size over time seems in part to contradict the laws of software evolution proposed for commercial systems. Both the inequality of effort distribution between programmers and an increasing number of developers in a project do not lead to a decrease in productivity, opposing Brooks{\textquoteright}s Law. Effort estimation based on the COCOMO model for commercial organizations shows a large amount of effort expended for the projects, while a more general Norden-Rayleigh modeling shows a distinctly smaller expenditure. This proposes that either a highly efficient development is achieved by this self-organizing cooperative and highly decentralized form of work, or that the participation of users besides programming tasks is enormous and constitutes an economic factor of large proportions. },
	keywords = {affiliation network, brooks law, cocomo, effort estimation, evolution, productivity, project success, scm, size, time, version control},
	issn = {1422-8890},
	doi = {10.1080/10196780410001675031},
	author = {Koch, Stefan}
}
@conference {German03automatingthe,
	title = {Automating the measurement of open source projects},
	booktitle = {Proceedings of the 3rd Workshop on Open Source Software Engineering},
	year = {2003},
	note = {"We have chosen to use Evolution to illustrate some of the capabilities of SoftChange. We focus on the data provided by CVS logs and the CVS commit mailing list. Our data includes changes to the CVS repository from April 1998 to January 2003."},
	pages = {63{\textendash}67},
	abstract = {The proliferation of open source projects raises a number of vital economic, social, and software engineering questions that are subject of intense research. Based on experience analyzing numerous open source and commercial projects we propose a set of tools to support extraction and validation of software project data. Such tools would streamline empirical investigation of open source projects and make it possible to test existing and new theories about the nature of open source projects. Our soft- ware includes tools to extract and summarize information from mailing lists, CVS logs, ChangeLog files, and defect tracking databases. More importantly, it cross-links records from various data sources and identifies all contributors for a software change. We illustrate some of the capabilities by analyzing data from Ximian Evolution project.},
	keywords = {bug reports, bug tracking, changelog, cvs, defects, evolution, log files, logs, mailing list, scm, softchange, source code, ximian, ximian evolution},
	attachments = {https://flosshub.org/sites/flosshub.org/files/germanMockus2003.pdf},
	author = {German, Daniel and Audris Mockus}
}
@conference {DBLP:conf/csmr/CapiluppiLM03,
	title = {Characteristics of Open Source Projects},
	booktitle = {7th European Conference on Software Maintenance and Reengineering (CSMR{\textquoteright}03)},
	year = {2003},
	note = {"We analyze a sample of around 400 projects from a popular OS project repository. "
no pdf to confirm what projects these are or what the repository is.[ms]},
	pages = {317-},
	abstract = {Most empirical studies about Open Source (OS)projects or products are vertical and usually deal with the flagship, successful projects. There is a substantial lack of horizontal studies to shed light on the whole population of projects, including failures. This paper presents a horizontal study aimed at characterizing OS projects. We analyze a sample of around 400 projects from a popular OS project repository. Each project is characterized by a number of attributes. We analyze these attributes statically and over time. The main results show that few projects are capable of attracting a meaningful community of developers. The majority of projects is made by few (in many cases one) person with a very slow pace of evolution.},
	keywords = {evolution, project success, repository},
	author = {Capiluppi, Andrea and Patricia Lago and Maurizio Morisio}
}
@conference {Ye:2003:TUM:776816.776867,
	title = {Toward an understanding of the motivation Open Source Software developers},
	booktitle = {Proceedings of the 25th International Conference on Software Engineering},
	series = {ICSE {\textquoteright}03},
	year = {2003},
	note = {"Analyzing the emails sent to the mailing fist is one way of understanding the structure of the community."
"Table 2 displays the number of code contributions made by members to the GIMP system and the defined roles of those contributing members. We counted the number of contributions made by each person by analyzing the change log of the system."},
	pages = {419{\textendash}429},
	publisher = {IEEE Computer Society},
	organization = {IEEE Computer Society},
	address = {Washington, DC, USA},
	abstract = {An Open Source Software (OSS) project is unlikely to be successful unless there is an accompanied community that provides the platform for developers and users to collaborate. Members of such communities are volunteers whose motivation to participate and contribute is of essential importance to the success of OSS projects. In this paper, we aim to create an understanding of what motivates people to participate in OSS communities. We theorize that learning is one of the motivational forces. Our theory is grounded in the learning theory of Legitimate Peripheral Participation, and is supported by analyzing the social structure of OSS communities and the co-evolution between OSS systems and communities. We also discuss practical implications of our theory for creating and maintaining sustainable OSS communities as well as for software engineering research and education.},
	keywords = {change log, COMMUNITY, contributions, contributors, developers, email, email archives, evolution, gimp, log files, mailing list, roles, source code},
	isbn = {0-7695-1877-X},
	url = {http://portal.acm.org/citation.cfm?id=776816.776867},
	attachments = {https://flosshub.org/sites/flosshub.org/files/YeKishida.pdf},
	author = {Ye, Yunwen and Kishida, Kouichi}
}
@conference {Godfrey:2001:GES:602461.602482,
	title = {Growth, evolution, and structural change in open source software},
	booktitle = {Proceedings of the 4th International Workshop on Principles of Software Evolution (IWPSE 2001)},
	series = {IWPSE {\textquoteright}01},
	year = {2001},
	note = {"We measured [linux] system size in uncommented LOC"
"We also examined the growth of several other open source systems, including the VIM text editor, Eric Raymond{\textquoteright}s fetchmail utility, and the GCC compiler suite. "},
	pages = {103{\textendash}106},
	publisher = {ACM},
	organization = {ACM},
	address = {New York, NY, USA},
	abstract = {Our recent work has addressed how and why software systems evolve over time, with a particular emphasis on software architecture and open source software systems [2, 3, 6]. In this position paper, we present a short summary of two recent projects. First, we have performed a case study on the evolution of the Linux kernel [3], as well as some other open source software (OSS) systems. We have found that several OSS systems appear not to obey some of "Lehman{\textquoteright}s laws" of software evolution [5, 7], and that Linux in particular is continuing to grow at a geometric rate. Currently, we are working on a detailed study of the evolution of one of the subsystems of the Linux kernel: the SCSI drivers subsystem. We have found that cloning, which is usually considered to be an indicator of lazy development and poor process, is quite common and is even considered to be a useful practice. Second, we are developing a tool called Beagle to aid software maintainers in understanding how large systems have changed over time. Beagle integrates data from various static analysis and metrics tools and provides a query engine as well as navigable visualizations. Of particular note, Beagle aims to provide help in modelling long term evolution of systems that have undergone architectural and structural change.},
	keywords = {agile methods, beagle, cloning, evolution, fetchmail, gcc, growth, kernel, lehman{\textquoteright}s laws, lines of code, linux, linux kernel, loc, open source software, software architecture, software evolution, source code, structural change, supporting environments, vim},
	isbn = {1-58113-508-4},
	doi = {http://doi.acm.org/10.1145/602461.602482},
	url = {http://doi.acm.org/10.1145/602461.602482},
	attachments = {https://flosshub.org/sites/flosshub.org/files/tu2001.pdf},
	author = {Michael Godfrey and Tu, Qiang}
}
@conference {Godfrey:2000:EOS:850948.853411,
	title = {Evolution in Open Source Software: A Case Study},
	booktitle = {Proceedings of the International Conference on Software Maintenance (ICSM{\textquoteright}00)},
	series = {ICSM {\textquoteright}00},
	year = {2000},
	note = {"We examined 96 kernel versions..."
.c files, .h files only
loc, lines of code
number of functions
number of modules},
	pages = {131{\textendash}},
	publisher = {IEEE Computer Society},
	organization = {IEEE Computer Society},
	address = {Washington, DC, USA},
	abstract = {Most studies of software evolution have been performed on systems developed within a single company using traditional management techniques. With the widespread availability of several large software systems that have been developed using an {\textquoteright}open source{\textquoteright} development approach, we now have a chance to examine these systems in detail, and see if their evolutionary narratives are significantly different from commercially developed systems. This paper summarizes our preliminary investigations into the evolution of the best known open source system: the Linux operating system kernel. Because Linux is large (over two million lines of code in the most recent version) and because its development model is not as tightly planned and managed as most industrial software processes, we had expected to find that Linux was growing more slowly as it got bigger and more complex. Instead, we have found that Linux has been growing at a super-linear rate for several years. In this paper, we explore the evolution of the Linux kernel both at the system level and within the major subsystems, and we discuss why we think Linux continues to exhibit such strong growth.},
	keywords = {evolution, functions, growth, lines of code, linux, linux kernel, loc, source code},
	isbn = {0-7695-0753-0},
	url = {http://portal.acm.org/citation.cfm?id=850948.853411},
	attachments = {https://flosshub.org/sites/flosshub.org/files/godfrey00.pdf},
	author = {Godfrey, Michael W. and Tu, Qiang}
}
