@article {1324,
	title = {Are Developers Fixing Their Own Bugs?},
	journal = {International Journal of Open Source Software and Processes},
	volume = {3},
	year = {2011},
	note = {"The analysis is focused at the level of lines of code and it uses the information stored in the source code management system"},
	pages = {23 - 42},
	abstract = {The process of fixing software bugs plays a key role in the maintenance activities of a software project. Ideally, code ownership and responsibility should be enforced among developers working on the same artifacts, so that those introducing buggy code could also contribute to its fix. However, especially in FLOSS projects, this mechanism is not clearly understood: in particular, it is not known whether those contributors fixing a bug are the same introducing and seeding it in the first place. This paper analyzes the comm-central FLOSS project, which hosts part of the Thunderbird, SeaMonkey, Lightning extensions and Sunbird projects from the Mozilla community. The analysis is focused at the level of lines of code and it uses the information stored in the source code management system. The results of this study show that in 80\% of the cases, the bug-fixing activity involves source code modified by at most two developers. It also emerges that the developers fixing the bug are only responsible for 3.5\% of the previous modifications to the lines affected; this implies that the other developers making changes to those lines could have made that fix. In most of the cases the bug fixing process in comm-central is not carried out by the same developers than those who seeded the buggy code.},
	keywords = {bug fixing, developers, loc, scm},
	issn = {1942-3934},
	doi = {10.4018/jossp.2011040102},
	author = {Izquierdo-Cortazar, Daniel and Capiluppi, Andrea and Jesus M. Gonzalez-Barahona}
}
@conference {1308,
	title = {Social interactions around cross-system bug fixings},
	booktitle = {Proceedings of the 8th working conference on Mining software repositories - MSR {\textquoteright}11},
	year = {2011},
	note = {"We rely on information stored in versioning database and mailing lists of both systems and develop methods to reconstruct and integrate different historical database"},
	month = {05/2011},
	pages = {143-152},
	publisher = {ACM Press},
	organization = {ACM Press},
	address = {New York, New York, USA},
	abstract = {Cross-system bug fixing propagation is frequent among systems having similar characteristics, using a common framework, or, in general, systems with cloned source code fragments. While previous studies showed that clones tend to be properly maintained within a single system, very little is known about cross-system bug management.

This paper describes an approach to mine explicitly documented cross-system bug fixings, and to relate their occurrences to social characteristics of contributors discussing through the project mailing lists--e.g., degree, betweenness, and brokerage--as well as to the contributors{\textquoteright} activity on source code.

The paper reports results of an empirical study carried out on FreeBSD and OpenBSD kernels. The study shows that the phenomenon of cross-system bug fixing between these two projects occurs often, despite the limited overlap of contributors. The study also shows that cross-system bug fixings mainly involve contributors with the highest degree, betweenness and brokerage level, as well as contributors that change the source code more than others.},
	keywords = {bug fixing, bug tracking system, committers, email, email archives, freebsd, mailing list, openbsd},
	isbn = {9781450305747},
	doi = {10.1145/1985441.1985463},
	author = {Cerulo, Luigi and Cimitile, Marta and Di Penta, Massimiliano and Canfora, Gerardo}
}
@conference {961,
	title = {Do stack traces help developers fix bugs?},
	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 = {118 - 121},
	publisher = {IEEE},
	organization = {IEEE},
	address = {Cape Town, South Africa},
	abstract = {A widely shared belief in the software engineering community is that stack traces are much sought after by developers to support them in debugging. But limited empirical evidence is available to confirm the value of stack traces to developers. In this paper, we seek to provide such evidence by conducting an empirical study on the usage of stack traces by developers from the ECLIPSE project. Our results provide strong evidence to this effect and also throws light on some of the patterns in bug fixing using stack traces. We expect the findings of our study to further emphasize the importance of adding stack traces to bug reports and that in the future, software vendors will provide more support in their products to help general users make such information available when filing bug reports.},
	keywords = {bug fixing, bug report, debugging, eclipse, stack trace},
	isbn = {978-1-4244-6802-7},
	doi = {10.1109/MSR.2010.5463280},
	attachments = {https://flosshub.org/sites/flosshub.org/files/118-10-msr.pdf},
	author = {Schroter, Adrian and Schr{\"o}ter, Adrian and Bettenburg, Nicolas and Premraj, Rahul}
}
@conference {1218,
	title = {A Longitudinal Study on Collaboration Networks and Decision to Participate in a FLOSS Community},
	booktitle = {5th Workshop on Public Data about Software Development (WoPDaSD 2010)},
	year = {2010},
	note = {"we chose as a case of study Epiphany, which is the default web browser of the GNOME graphical desktop environment"

"We collected all relevant data by parsing all the bug reports in GNOME Bugzilla repository relative to Epiphany. The data collection and storing was done using Bicho (v. 0.4 rev. 7198), a software part of the FLOSSMetric project [14]."},
	abstract = {In this paper we conjecture that individual decisions of FLOSS (Free/Libre Open Source Software) developers to take on a task are influenced by network relations generated by collaboration among project members. In order to explore our conjecture we collected data on a FLOSS project team consisting of 227 developers committed since 2002 to the development of a web browser. We reconstructed 2-mode co- collaboration networks (software developer by bug) in which a tie represents an action taken by a developer in order to solve a specific bug. Co-collaboration networks were collected at five points in time during a six-month development cycle of the software. We report and discuss results of longitudinal actor-based modeling that we specify to test for the influence of local network structures on developer{\textquoteright}s decision to take action on a specific bug. The study controls for bug-specific and developer-specific characteristics that may also affect developers{\textquoteright} decisions exogenously. We also control for priority and severity levels assigned by the team to bugs in an attempt to manage voluntary contribution.},
	keywords = {bicho, bug fixing, bug reports, bugzilla, COLLABORATION, developers, epiphany, flossmetrics, gnome, social network analysis},
	attachments = {https://flosshub.org/sites/flosshub.org/files/wopdasd002.pdf},
	author = {Guido Conaldi and Tonellato, Marco}
}
@conference {944,
	title = {Learning from defect removals},
	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 = {179 - 182},
	publisher = {IEEE},
	organization = {IEEE},
	address = {Vancouver, BC, Canada},
	abstract = {Recent research has tried to identify changes in source code repositories that fix bugs by linking these changes to reports in issue tracking systems. These changes have been traced back to the point in time when they were previously modified as a way of identifying bug introducing changes. But we observe that not all changes linked to bug tracking systems are fixing bugs; some are enhancing the code. Furthermore, not all fixes are applied at the point in the code where the bug was originally introduced. We flesh out these observations with a manual review of several software projects, and use this opportunity to see how many defects are in the scope of static analysis tools.},
	keywords = {bug fixing, bugzilla, change management, cherry, cvs, eclipse, groovy, launching, source code, svn, text editor},
	isbn = {978-1-4244-3493-0},
	doi = {10.1109/MSR.2009.5069500},
	attachments = {https://flosshub.org/sites/flosshub.org/files/179LearnFromDefects-MSR09.pdf},
	author = {Ayewah, Nathaniel and Pugh, William}
}
@article {Au20099,
	title = {Virtual organizational learning in open source software development projects},
	journal = {Information \& Management},
	volume = {46},
	number = {1},
	year = {2009},
	pages = {9 - 15},
	abstract = {We studied virtual organizational learning in open source software (OSS) development projects. Specifically, our research focused on learning effects of OSS projects and the factors that affect the learning process. The number and percentage of resolved bugs and bug resolution time of 118 SourceForge.net OSS projects were used to measure the learning effects. Projects were characterized by project type, number and experience of developers, number of bugs, and bug resolution time. Our results provided evidence of virtual organizational learning in OSS development projects and support for several factors as determinants of performance. Team size was a significant predictor, with mid-sized project teams functioning best. Teams of three to seven developers exhibited the highest efficiency over time and teams of eight to 15 produced the lowest mean time for bug resolution. Increasing the percentage of bugs assigned to specific developers or boosting developer participation in other OSS projects also improved performance. Furthermore, project type introduced variability in project team performance.},
	keywords = {bug fixing, bugs, learning, Project performance, sourceforge, team size, teams, virtual organization},
	issn = {0378-7206},
	doi = {DOI: 10.1016/j.im.2008.09.004},
	url = {http://www.sciencedirect.com/science/article/B6VD0-4V1D7NT-1/2/a3bbf7652c674f753398160b8f05f6e9},
	author = {Yoris A. Au and Darrell Carpenter and Xiaogang Chen and Jan G. Clark}
}
@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}
}
@conference {Herraiz:2008:TSB:1370750.1370786,
	title = {Towards a simplification of the bug report form in eclipse},
	booktitle = {Proceedings of the 2008 international working conference on Mining software repositories},
	series = {MSR {\textquoteright}08},
	year = {2008},
	pages = {145{\textendash}148},
	publisher = {ACM},
	organization = {ACM},
	address = {New York, NY, USA},
	abstract = {We believe that the bug report form of Eclipse contains too many fields, and that for some fields, there are too many options. In this MSR challenge report, we focus in the case of the severity field. That field contains seven different levels of severity. Some of them seem very similar, and it is hard to distinguish among them. Users assign severity, and developers give priority to the reports depending on their severity. However, if users can not distinguish well among the various severity options, they will probably assign different priorities to bugs that require the same priority. We study the mean time to close bugs reported in Eclipse, and how the severity assigned by users affects this time. The results shows that classifying by time to close, there are less clusters of bugs than levels of severity. We therefore conclude that there is a need to make a simpler bug report form.},
	keywords = {bug fixing, bug report, bug tracking system, classification, eclipse, msr challenge, severity},
	isbn = {978-1-60558-024-1},
	doi = {http://doi.acm.org/10.1145/1370750.1370786},
	url = {http://doi.acm.org/10.1145/1370750.1370786},
	author = {Herraiz, Israel and Daniel M. German and Jesus M. Gonzalez-Barahona and Gregorio Robles}
}
@conference {Sudakrishnan:2008:UBF:1370750.1370761,
	title = {Understanding bug fix patterns in verilog},
	booktitle = {Proceedings of the 2008 international working conference on Mining software repositories},
	series = {MSR {\textquoteright}08},
	year = {2008},
	pages = {39{\textendash}42},
	publisher = {ACM},
	organization = {ACM},
	address = {New York, NY, USA},
	abstract = {Today, many electronic systems are developed using a hardware description language, a kind of software that can be converted into integrated circuits or programmable logic devices. Like traditional software projects, hardware projects have bugs, and significant developer time is spent fixing them. A useful first step toward reducing bugs in hardware is developing an understanding of the frequency of different types of errors. Once the most common types are known, it is then possible to focus attention on eliminating them. As most hardware projects use software configuration management repositories, these can be mined for the textual bug fix changes. In this project, we analyze the bug fix history of four hardware projects written in Verilog and manually define 25 bug fix patterns. The frequency of each bug type is then computed for all projects. We find that 29 -- 55\% of the bug fix pattern instances in Verilog involve assignment statements, while 18 -- 25\% are related to if statements.},
	keywords = {bug fixing, error classification, hdl, verilog, VHDL},
	isbn = {978-1-60558-024-1},
	doi = {http://doi.acm.org/10.1145/1370750.1370761},
	url = {http://doi.acm.org/10.1145/1370750.1370761},
	attachments = {https://flosshub.org/sites/flosshub.org/files/p39-sudakrishnan.pdf},
	author = {Sudakrishnan, Sangeetha and Madhavan, Janaki and Whitehead,Jr., E. James and Renau, Jose}
}
@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 {springerlink:10.1007/s10588-006-9006-3,
	title = {Correlating temporal communication patterns of the Eclipse open source community with performance and creativity},
	journal = {Computational \&amp; Mathematical Organization Theory},
	volume = {13},
	year = {2007},
	note = {"Social network data was collected from the Eclipse component development groups{\textquoteright} online mailing lists by using the online process tool (Gloor and Zhao, 2004). Data on bugs and enhancements for each group was collected from the Eclipse bugzilla database (Eclipse bugzilla, 2004). The social network data was analyzed with the TeCFlow tool (Gloor and Zhao, 2004)."
"The study is based on data from the three main projects of the Eclipse open source development community, namely {\textquotedblleft}eclipse{\textquotedblright}, {\textquotedblleft}tools{\textquotedblright} and {\textquotedblleft}technology{\textquotedblright}. We have chosen thirty-three different component development groups for analysis."
"The online process tool (online process tool, 2004) was utilized to collect communication data from their mailing list archives. The online process tool runs a robot that searches for URLs in the projects{\textquoteright} mailing list archives to compile a list of the possible URL links. It then extracts communication data as tuples in the form of {\textquotedblleft}sender, receiver, communication type, timestamp, communication contents{\textquotedblright} and stores it in the database. Further, bugs and enhancement data were collected from the Eclipse bugzilla database."},
	pages = {17-27},
	publisher = {Springer Netherlands},
	abstract = {This paper studies the temporal communication patterns of online communities of developers and users of the open source Eclipse Java development environment. It measures the productivity of each community and seeks to identify correlations that exist between group communication characteristics and productivity attributes. The study uses the TeCFlow (Temporal Communication Flow) visualizer to create movie maps of the knowledge flow by analyzing the publicly accessible Eclipse developer mailing lists as an approximation of the social networks of developers and users. Thirty-three different Eclipse communities discussing development and use of components of Eclipse such as the Java Development Tools, the different platform components, the C/C++ Development Tools and the AspectJ extension have been analyzed over a period of six months. The temporal evolution of social network variables such as betweenness centrality, density, contribution index, and degree have been computed and plotted. Productivity of each development group is measured in terms of two indices, namely performance and creativity. Performance of a group is defined as the ratio of new bugs submitted compared with bugs fixed within the same period of time. Creativity is calculated as a function of new features proposed and implemented. Preliminary results indicate that there is a correlation between attributes of social networks such as density and betweenness centrality and group productivity measures in an open source development community. We also find a positive correlation between changes over time in betweenness centrality and creativity, and a negative correlation between changes in betweenness centrality and performance.},
	keywords = {bug fixing, bugs, bugzilla, communication, creativity, developers, eclipse, email, email archives, feature requests, mailing lists, performance, productivity},
	issn = {1381-298X},
	url = {http://dx.doi.org/10.1007/s10588-006-9006-3},
	attachments = {https://flosshub.org/sites/flosshub.org/files/16.pdf},
	author = {Kidane, Yared and Gloor, Peter}
}
@conference {991,
	title = {How Long Will It Take to Fix This Bug?},
	booktitle = {Fourth International Workshop on Mining Software Repositories (MSR{\textquoteright}07:ICSE Workshops 2007)},
	year = {2007},
	pages = {1},
	publisher = {IEEE},
	organization = {IEEE},
	address = {Minneapolis, MN, USA},
	abstract = {Predicting the time and effort for a software problem has long been a difficult task. We present an approach that automatically predicts the fixing effort, i.e., the person-hours spent on fixing an issue. Our technique leverages existing issue tracking systems: given a new issue report, we use the Lucene framework to search for similar, earlier reports and use their average time as a prediction. Our approach thus allows for early effort estimation, helping in assigning issues and scheduling stable releases. We evaluated our approach using effort data from the JBoss project. Given a sufficient number of issues reports, our automatic predictions are close to the actual effort; for issues that are bugs, we are off by only one hour, beating naive predictions by a factor of four.},
	keywords = {bug fixing, bug reports, effort estimation, jboss, lucene, prediction, time},
	isbn = {0-7695-2950-X},
	doi = {10.1109/MSR.2007.13},
	attachments = {https://flosshub.org/sites/flosshub.org/files/28300001.pdf},
	author = {Weiss, Cathrin and Premraj, Rahul and Zimmermann, Thomas and Zeller, Andreas}
}
@conference {1018,
	title = {Local and Global Recency Weighting Approach to Bug Prediction},
	booktitle = {Fourth International Workshop on Mining Software Repositories (MSR{\textquoteright}07:ICSE Workshops 2007)},
	year = {2007},
	pages = {33 - 33},
	publisher = {IEEE},
	organization = {IEEE},
	address = {Minneapolis, MN, USA},
	abstract = {Finding and fixing software bugs is a challenging maintenance task, and a significant amount of effort is invested by software development companies on this issue. In this paper, we use the Eclipse project{\textquoteright}s recorded software bug history to predict occurrence of future bugs. The history contains information on when bugs have been reported and subsequently fixed.},
	keywords = {bug fixing, bug reports, eclipse, maintenance, prediction},
	isbn = {0-7695-2950-X},
	doi = {10.1109/MSR.2007.17},
	attachments = {https://flosshub.org/sites/flosshub.org/files/28300033.pdf},
	author = {Joshi, Hemant and Zhang, Chuanlei and Ramaswamy, S. and Bayrak, Coskun}
}
@conference {1014,
	title = {Predicting Eclipse Bug Lifetimes},
	booktitle = {Fourth International Workshop on Mining Software RepositoriesFourth International Workshop on Mining Software Repositories (MSR{\textquoteright}07:ICSE Workshops 2007)},
	year = {2007},
	pages = {29 - 29},
	publisher = {IEEE},
	organization = {IEEE},
	address = {Minneapolis, MN, USA},
	abstract = {In non-trivial software development projects planning and allocation of resources is an important and difficult task. Estimation of work time to fix a bug is commonly used to support this process. This research explores the viability of using data mining tools to predict the time to fix a bug given only the basic information known at the beginning of a bug{\textquoteright}s lifetime. To address this question, a historical portion of the Eclipse Bugzilla database is used for modeling and predicting bug lifetimes. A bug history transformation process is described and several data mining models are built and tested. Interesting behaviours derived from the models are documented. The models can correctly predict up to 34.9\% of the bugs into a discretized log scaled lifetime class.},
	keywords = {bug fixing, bugzilla, classification, eclipse, effort estimation, mining challenge, msr challenge, prediction, weka},
	isbn = {0-7695-2950-X},
	doi = {10.1109/MSR.2007.25},
	attachments = {https://flosshub.org/sites/flosshub.org/files/28300029.pdf},
	author = {Panjer, Lucas D.}
}
@conference {1012,
	title = {Prioritizing Warning Categories by Analyzing Software History},
	booktitle = {Fourth International Workshop on Mining Software Repositories (MSR{\textquoteright}07:ICSE Workshops 2007)},
	year = {2007},
	pages = {27 - 27},
	publisher = {IEEE},
	organization = {IEEE},
	address = {Minneapolis, MN, USA},
	abstract = {Automatic bug finding tools tend to have high false positive rates: most warnings do not indicate real bugs. Usually bug finding tools prioritize each warning category. For example, the priority of "overflow" is 1 and the priority of "jumbled incremental" is 3, but the tools{\textquoteright} prioritization is not very effective.

In this paper, we prioritize warning categories by analyzing the software change history. The underlying intuition is that if warnings from a category are resolved quickly by developers, the warnings in the category are important. Experiments with three bug finding tools (FindBugs, JLint, and PMD) and two open source projects (Columba and jEdit) indicate that different warning categories have very different lifetimes. Based on that observation, we propose a preliminary algorithm for warning category prioritizing.},
	keywords = {bug fixing, change history, columba, findbugs, jedit, jlint, kenyon, pmd, warning},
	isbn = {0-7695-2950-X},
	doi = {10.1109/MSR.2007.26},
	attachments = {https://flosshub.org/sites/flosshub.org/files/28300027.pdf},
	author = {Kim, Sunghun and Ernst, Michael D.}
}
@article {90,
	title = {Core and periphery in Free/Libre and Open Source software team communications},
	journal = {Proceedings of the 39th Annual Hawaii International Conference on System Sciences-Volume 06},
	year = {2006},
	abstract = {The concept of the core group of developers is important and often discussed in empirical studies of FLOSS projects. This paper examines the question, "how does one empirically distinguish the core?" Being able to identify the core members of a FLOSS development project is important because many of the processes necessary for successful projects likely involve core members differently than peripheral members, so analyses that mix the two groups will likely yield invalid results. 

We compare 3 analysis approaches to identify the core: the named list of developers, a Bradford{\textquoteright}s law analysis that takes as the core the most frequent contributors and a social network analysis of the interaction pattern that identifies the core in a core-and-periphery structure. We apply these measures to the interactions around bug fixing for 116 SourceForge projects. The 3 techniques identify different individuals as core members; examination of which individuals are identified leads to suggestions for refining the measures. All 3 measures though suggest that the core of FLOSS projects is a small fraction of the total number of contributors.},
	keywords = {bug fixing, contributions, contributors, core, developers, social network analysis, sourceforge, team},
	author = {Kevin Crowston and Kangning Wei and Li, Qing and Howison, James}
}
@article {Crowston:2006a,
	title = {Hierarchy and centralization in Free and Open Source Software team communications},
	journal = {Knowledge, Technology \& Policy},
	volume = {18},
	number = {4},
	year = {2006},
	pages = {65{\textendash}85},
	abstract = {Free/Libre Open Source Software (FLOSS) development teams provide an interesting and convenient setting for studying distributed work. We begin by answering perhaps the most basic question: what is the social structure of these teams? Based on a social network analysis of interactions represented in 62,110 bug reports from 122 large and active projects, we find that some OSS teams are highly centralized, but contrary to expectation, others are not. Projects are mostly quite hierarchical on four measures of hierarchy, consistent with past research but contrary to the popular image of these projects. Furthermore, we find that the level of centralization is negatively correlated with project size, suggesting that larger projects become more modular. The paper makes a further methodological contribution by identifying appropriate analysis approaches for interaction data. We conclude by sketching directions for future research.},
	keywords = {apache, bug fixing, bug tracking, FLOSS, project success, savannah, social network analysis, sourceforge, team size, teams},
	attachments = {https://flosshub.org/sites/flosshub.org/files/CrowstonHierarchyAndCentralization.pdf},
	author = {Kevin Crowston and Howison, James}
}
@conference {Kim:2006:LDT:1137983.1138027,
	title = {How long did it take to fix bugs?},
	booktitle = {Proceedings of the 2006 international workshop on Mining software repositories},
	series = {MSR {\textquoteright}06},
	year = {2006},
	pages = {173{\textendash}174},
	publisher = {ACM},
	organization = {ACM},
	address = {New York, NY, USA},
	abstract = {The number of bugs (or fixes) is a common factor used to measure the quality of software and assist bug related analysis. For example, if software files have many bugs, they may be unstable. In comparison, the bug-fix time--the time to fix a bug after the bug was introduced--is neglected. We believe that the bug-fix time is an important factor for bug related analysis, such as measuring software quality. For example, if bugs in a file take a relatively long time to be fixed, the file may have some structural problems that make it difficult to make changes. In this report, we compute the bug-fix time of files in ArgoUML and PostgreSQL by identifying when bugs are introduced and when the bugs are fixed. This report includes bug-fix time statistics such as average bug-fix time, and distributions of bug-fix time. We also list the top 20 bug-fix time files of two projects.},
	keywords = {argouml, bug fixing, bugs, mining challenge, msr challenge, postgresql, quality, time},
	isbn = {1-59593-397-2},
	doi = {http://doi.acm.org/10.1145/1137983.1138027},
	url = {http://doi.acm.org/10.1145/1137983.1138027},
	attachments = {https://flosshub.org/sites/flosshub.org/files/173HowLong.pdf},
	author = {Kim, Sunghun and Whitehead,Jr., E. James}
}
@article {flosswp113,
	title = {The Impact of Ideology on Effectiveness in Open Source Software Development Teams},
	journal = {MIS Quarterly},
	volume = {30},
	number = {2},
	year = {2006},
	note = {"...we collected data related to OSS projects hosted on Sourceforge (www.sourceforge.net)."
"Data was collected using two surveys and from the Sourceforge website."
},
	month = {2006},
	pages = {291-314},
	abstract = {The emerging work on understanding open source software has argued for the importance of understanding what leads to effectiveness in OSS development teams and has pointed to the importance of ideology. This paper develops a framework of the OSS ideology (including specific norms, beliefs, and values) and a theoretical model to show how adherence to components of the ideology impact effectiveness in OSS teams. The model is based on the idea that ideology provides clan control, which is important in OSS development settings because OSS teams generally lack formal behavioral and outcome controls. The paper hypothesizes both direct effects of ideology on OSS team effectiveness and indirect effects via influences on affective trust, cognitive trust, and communication quality. Hypotheses are tested using survey and objective data on OSS projects. Four effectiveness measures are used to capture unique aspects of effectiveness in OSS including both the extent to which a team attracts input from the community and the team{\textquoteright}s success in accomplishing project outcomes. Results support the main thesis that OSS team members{\textquoteright} adherence to the tenets of the OSS community ideology enhances OSS team effectiveness. The study uncovers several differences in the importance of OSS norms, beliefs, and values to different kinds of OSS team effectiveness and discusses implications for theory and practice.},
	keywords = {bug fixing, bug reports, bug tracking, communication, COMMUNITY, effectiveness, feature requests, ideology, metadata, sourceforge, Survey, team effort, team size, trust},
	attachments = {https://flosshub.org/sites/flosshub.org/files/stewartgosain2.pdf},
	author = {Stewart, K. and Gosain, S.}
}
@article {Crowston:2006,
	title = {Information systems success in Free and Open Source Software development: Theory and measures},
	journal = {Software Process{\textendash}Improvement and Practice},
	volume = {11},
	number = {2},
	year = {2006},
	note = {"we continue our examination of success measures using data from Sourceforge..."
"e chose the number of developers (assessed from the records of the project and from bug fixing logs), bug-fixing time, and popularity (assessed from the number of downloads and viewings of project Web pages, and inclusion in distributions). These measures were chosen because they span the reconsidered FLOSS development process discussed above, including inputs (number of developers), process (speed of bug fixing) and output (popularity)."},
	pages = {123{\textendash}148},
	abstract = {Information systems success is one of the most widely used dependent variables in information systems (IS) research, but research on Free/Libre and Open Source software (FLOSS) often fails to appropriately conceptualize this important concept. In this paper, we reconsider what success means within a FLOSS context. We first review existing models of IS success and success variables used in FLOSS research and assess them for their usefulness, practicality and fit to the FLOSS context. Then, drawing on a theoretical model of group effectiveness in the FLOSS development process, as well as an online discussion group with developers, we present additional concepts that are central to an appropriate understanding of success for FLOSS. In order to examine the practicality and validity of this conceptual scheme, the second half of our paper presents an empirical study that demonstrates its operationalization of the chosen measures and assesses their internal validity. We use data from SourceForge to measure the project{\textquoteright}s effectiveness in team building, the speed of the project at responding to bug reports and the project{\textquoteright}s popularity. We conclude by discussing the implications of this study for our proposed extension of IS success in the context of FLOSS development and highlight future directions for research.},
	keywords = {bug fixing, developers, downloads, FLOSS, flossmole, page views, popularity, project success, size, sourceforge, success, team size},
	doi = {10.1002/spip.259},
	attachments = {https://flosshub.org/sites/flosshub.org/files/CrowstonHowisonAnnabi2006.pdf},
	author = {Kevin Crowston and Howison, James and Hala Annabi}
}
@conference {708,
	title = {Social dynamics of free and open source team communications},
	booktitle = {OSS2006: Open Source Systems (IFIP 2.13)},
	series = {IFIP International Federation for Information Processing },
	volume = {203/2006},
	year = {2006},
	month = {06/2006},
	pages = {319 - 330},
	publisher = {Springer},
	organization = {Springer},
	abstract = {This paper furthers inquiry into the social structure of free and open source software (FLOSS) teams by undertaking social network analysis across time. Contrary to expectations, we confirmed earlier findings of a wide distribution of centralizations even when examining the networks over time. The paper also provides empirical evidence that while change at the center of FLOSS projects is relatively uncommon, participation across the project communities is highly skewed, with many participants appearing for only one period. Surprisingly, large project teams are not more likely to undergo change at their centers.
},
	keywords = {bug fixing, bug reports, bug tracker, bug tracking, bugs, communications, Dynamic social networks, FLOSS teams, Human Factors, social network analysis, software development, sourceforge},
	issn = {978-0-387-34225-2},
	doi = {http://dx.doi.org/10.1007/0-387-34226-5_32},
	attachments = {https://flosshub.org/sites/flosshub.org/files/Social\%20dynamics\%20of\%20free\%20and\%20open\%20source\%20team.pdf},
	author = {Howison, James and Inoue, Keisuke and Kevin Crowston}
}
@conference {Anvik:2006:FTB:1134285.1134336,
	title = {Who should fix this bug?},
	booktitle = {Proceedings of the 28th international conference on Software engineering},
	series = {ICSE {\textquoteright}06},
	year = {2006},
	pages = {361{\textendash}370},
	publisher = {ACM},
	organization = {ACM},
	address = {New York, NY, USA},
	abstract = {Open source development projects typically support an open bug repository to which both developers and users can report bugs. The reports that appear in this repository must be triaged to determine if the report is one which requires attention and if it is, which developer will be assigned the responsibility of resolving the report. Large open source developments are burdened by the rate at which new bug reports appear in the bug repository. In this paper, we present a semi-automated approach intended to ease one part of this process, the assignment of reports to a developer. Our approach applies a machine learning algorithm to the open bug repository to learn the kinds of reports each developer resolves. When a new report arrives, the classifier produced by the machine learning technique suggests a small number of developers suitable to resolve the report. With this approach, we have reached precision levels of 57\% and 64\% on the Eclipse and Firefox development projects respectively. We have also applied our approach to the gcc open source development with less positive results. We describe the conditions under which the approach is applicable and also report on the lessons we learned about applying machine learning to repositories used in open source development.},
	keywords = {bug fixing, bug report, bug report assignment, bug triage, eclipse, Firefox, gcc, issue tracking, machine learning, problem tracking},
	isbn = {1-59593-375-1},
	doi = {10.1145/1134285.1134336},
	url = {http://doi.acm.org/10.1145/1134285.1134336},
	author = {Anvik, John and Hiew, Lyndon and Murphy, Gail C.}
}
@conference {Crowston:2004,
	title = {Coordination practices for bug fixing within FLOSS development teams},
	booktitle = {1st International Workshop on Computer Supported Activity Coordination, 6th International Conference on Enterprise Information Systems},
	year = {2004},
	note = {"First, we chose projects for which data we need for our analysis are publicly available (not all projects allow public access to the bug tracking system). Second, we chose teams with more than 8 members...we tried to select more and less suc- cessful development teams. To this aim we used the definitions of success proposed by [9], who suggest that a project is successful if it is active, the resulting software is downloaded and used and the code matures"

"Kicq, Gaim and PhPmyAdmin were chosen" - effective
DynAPI was chosen as an example of a less effective project" 

"We collected data indicative of the success of each project, such as its level of activity, number of downloads and development status. We then collected data from the archives of the bug tracking system, the tool used to support the bug fixing process"},
	address = {Porto, Portugal},
	abstract = {Free/Libre Open Source Software (FLOSS) is primarily developed by distributed teams. Developers contribute from around the world and coordinate their activity almost exclusively by means of email and bulletin boards. FLOSS development teams some how profit from the advantages and evade the challenges of distributed software development. Despite the relevance of the FLOSS both for research and practice, few studies have investigated the work practices adopted by these development teams. In this paper we investigate the structure and the coordination practices adopted by development teams during the bug-fixing process, which is considered one of main areas of FLOSS project success. In particular, based on a codification of the messages recorded in the bug tracking system of four projects, we identify the accomplished tasks, the adopted coordination mechanisms, and the role undertaken by both the FLOSS development team and the FLOSS community. We conclude with suggestions for further research.},
	keywords = {activity, bug fixing, bug reports, bug tracker, coordination, downloads, dynapi, FLOSS, gaim, kicq, phpmyadmin, status},
	attachments = {https://flosshub.org/sites/flosshub.org/files/CrowstonScozzi04coordination.pdf},
	author = {Kevin Crowston and Barbara Scozzi}
}
@conference {flosswp180,
	title = {Towards a Portfolio of FLOSS project Success Measures},
	booktitle = {Workshop on Open Source Software Engineering, International Conference on Software Engineering},
	year = {2004},
	month = {May},
	abstract = {Project success is one of the most widely used dependent variables in information systems research. However, conventional measures of project success are difficult to apply to Free/Libre Open Source Software projects. In this paper, we present an analysis of four measures of success applied to SourceForge projects: number of members of the extended development community, project activity, bug fixing time and number of downloads. We argue that these four measures provide different insights into the collaboration and control mechanisms of the projects.},
	keywords = {bug fixing, developers, downloads, project success, sourceforge, team, team size},
	attachments = {https://flosshub.org/sites/flosshub.org/files/crowston04towards.pdf},
	author = {Kevin Crowston and Hala Annabi and Howison, James and Chengetai Masango}
}
@conference {1109,
	title = {Distributed Collective Practices and F/OSS Problem Management: Perspective and Methods},
	booktitle = {Conference on Cooperation, Innovation \& Technology (CITE 2003)},
	year = {2003},
	note = {"We have begun studying in detail the general issues raised above using a large collection of research data from the Mozilla project"
"Our Bugzilla snapshot contains over 128,000 problem reports, of which about 88,000 have been resolved"},
	abstract = {This paper presents the state of our research on Distributed Collective Practices (DCPs) in Free/Open-Source Software (F/OSS) projects, focusing on sensemaking and resolution of software problems. We are exploring the hypothesis that variations in the content and in the articulation of these socio-technical processes have an impact on the outcome of the activity of F/OSS collectives, and more specifically on problem resolution. Our preliminary techniques for combining qualitative data analysis with automated process extraction result in a scalable analysis method called Computational Amplification (CA). We are applying CA to 128,000 problem reports from the Mozilla F/OSS project. The paper illustrates how CA is used to create multidimensional process models and shows types of conclusions we can reach.},
	keywords = {Automated process extraction, bug fixing, bug reports, bugzilla, Collective knowledge management, Information extraction from natural language texts, mozilla, Software problem management},
	author = {Gasser, Les and Gabriel Ripoche}
}
@article {121,
	title = {Two case studies of open source software development: Apache and Mozilla},
	journal = {ACM Transactions on Software Engineering and Methodology},
	volume = {11},
	number = {3},
	year = {2002},
	note = {apache data sources:
email, cvs, bug database 
regarding email: "We wrote Perl scripts to extract date, sender identity, message subject, and the message body that was further processed to obtain details on code changes and problem reports (see below). Manual inspection was used to resolve such things as multiple email addresses in cases where all automated techniques failed."
(but the rest of the paper does not address this data source at all)

mozilla data sources
bugzilla, cvs

},
	pages = {309-346},
	abstract = {According to its proponents, open source style software development has the capacity to compete successfully, and perhaps in many cases displace, traditional commercial development methods. In order to begin investigating such claims, we examine data from two major open source projects, the Apache web server and the Mozilla browser. By using email archives of source code change history and problem reports we quantify aspects of developer participation, core team size, code ownership, productivity, defect density, and problem resolution intervals for these OSS projects. We develop several hypotheses by comparing the Apache project with several commercial projects. We then test and refine several of these hypotheses, based on an analysis of Mozilla data. We conclude with thoughts about the prospects for high- performance commercial/ open source process hybrids.},
	keywords = {apache, bug fixing, bug reports, bugzilla, change history, core, defect density, email, email archives, mailing list, mozilla, ownership, participation, productivity, scm, source code},
	attachments = {https://flosshub.org/sites/flosshub.org/files/mockusFieldingHerbsleb2002.pdf},
	author = {Audris Mockus and Roy Fielding and Herbsleb, J. D.}
}
