@proceedings {export:232407,
	title = {The Uniqueness of Changes: Characteristics and Applications},
	year = {2015},
	month = {05/2015},
	abstract = {Changes in software development come in many forms. Some changes are frequent, idiomatic, or repetitive (e.g. adding checks for nulls or logging important values) while others are unique. We hypothesize that unique changes are different from the more common similar (or non-unique) changes in important ways; they may require more expertise or represent code that is more complex or prone to mistakes. As such, these changes are worthy of study. In this paper, we present a definition of unique changes and provide a method for identifying them in software project history. Based on the results of applying our technique on the Linux kernel and two large projects at Microsoft, we present an empirical study of unique changes. We explore how prevalent unique changes are and characterize where they occur along the architecture of the project. We further investigate developers{\textquoteright} contribution towards uniqueness of changes. We also describe potential applications of leveraging the uniqueness of change and implement two such applications, evaluating the risk of changes based on uniqueness and providing change recommendations for non-unique changes.},
	keywords = {linux kernel},
	url = {http://research.microsoft.com/apps/pubs/default.aspx?id=232407},
	attachments = {https://flosshub.org/sites/flosshub.org/files/MSR-TR-2014-149.pdf},
	author = {Ray, Baishakhi and Meiyappan Nagappan and Christian Bird and Nachiappan Nagappan and Zimmermann, Thomas}
}
@conference {1314,
	title = {Apples vs. oranges?},
	booktitle = {Proceedings of the 8th working conference on Mining software repositories - MSR {\textquoteright}11},
	year = {2011},
	note = {"In this MSR challenge report, we compare the source code of two in- dustrial grade Integrated Development Environments (IDE): Netbeans, developed by Oracle Corporation, and Eclipse, developed by the Eclipse Foundation. In the same spirit as [1], our goal is not to identify how similar or different they are, but to identify differences that, if not taken into consideration, might result in biased, and potentially erroneous conclusions."},
	month = {05/2011},
	pages = {246-249},
	publisher = {ACM Press},
	organization = {ACM Press},
	address = {New York, New York, USA},
	abstract = {We attempt to compare the source code of two Java IDE systems: Netbeans and Eclipse. The result of this experiment shows that many factors, if ignored, could risk a bias in the results, and we posit various observations that should be taken into consideration to minimize such risk.

},
	keywords = {eclipse, netbeans, source code},
	isbn = {9781450305747},
	doi = {10.1145/1985441.1985483},
	author = {Davies, Julius and Daniel M. German}
}
@conference {1313,
	title = {Do comments explain codes adequately?},
	booktitle = {Proceedings of the 8th working conference on Mining software repositories - MSR {\textquoteright}11},
	year = {2011},
	month = {05/2011},
	pages = {242-245},
	publisher = {ACM Press},
	organization = {ACM Press},
	address = {New York, New York, USA},
	abstract = {Comment lines in the software source code include descriptions of codes, usage of codes, copyrights, unused codes, comments, and so on. It is required for comments to explain the content of written code adequately, since the wrong description in the comment may causes further bug and confusion in maintenance.

In this paper, we try to clarify a research question: "In which projects do comments describe the code adequately?" To answer this question, we selected the group 1 of mining challenge and used data obtained from Eclipse and Netbeans. Since it is difficult to answer the above question directly, we define the distance between codes and comments. By utilizing the fault-prone module prediction technique, we can answer the alternative question from the data of two projects. The result shows that Eclipse project has relatively adequate comments.},
	keywords = {comments, eclipse, msr challenge, netbeans, prediction},
	isbn = {9781450305747},
	doi = {10.1145/1985441.1985482},
	author = {Mizuno, Osamu and Hirata, Yukinao}
}
@conference {1309,
	title = {Do time of day and developer experience affect commit bugginess},
	booktitle = {Proceedings of the 8th working conference on Mining software repositories - MSR {\textquoteright}11},
	year = {2011},
	note = {"we study the latest versions of the Linux kernel and PostgreSQL, which have 222,332 and 31,098 commits, respectively. We study the correlation between a commit{\textquoteright}s bugginess and the time of day of the commit, the day of week of the commit, and the experience and commit frequency of the commit authors. In addition, we study several other commit characteristics, such as comment-only fixes and bug lifetimes."},
	month = {05/2011},
	pages = {153-162},
	publisher = {ACM Press},
	organization = {ACM Press},
	address = {New York, New York, USA},
	abstract = {Modern software is often developed over many years with hundreds of thousands of commits. Commit metadata is a rich source of social characteristics, including the commit{\textquoteright}s time of day and the experience and commit frequency of its author. The "bugginess" of a commit is also a critical property of that commit. In this paper, we investigate the correlation between a commit{\textquoteright}s social characteristics and its "bugginess"; such results can be very useful for software developers and software engineering researchers. For instance, developers or code reviewers might be well-advised to thoroughly verify commits that are more likely to be buggy. In this paper, we study the correlation between a commit{\textquoteright}s bugginess and the time of day of the commit, the day of week of the commit, and the experience and commit frequency of the commit authors. We survey two widely-used open source projects: the Linux kernel and PostgreSQL.

Our main findings include: (1) commits submitted between midnight and 4 AM (referred to as late-night commits) are significantly buggier and commits between 7 AM and noon are less buggy, implying that developers may want to double-check their own latenight commits; (2) daily-committing developers produce less-buggy commits, indicating that we may want to promote the practice of daily-committing developers reviewing other developers{\textquoteright} commits; and (3) the bugginess of commits versus day-of-week varies for different software projects.},
	isbn = {9781450305747},
	doi = {10.1145/1985441.1985464},
	author = {Tan, Lin and Lam, Patrick and Eyolfson, Jon}
}
@conference {1304,
	title = {Entering the circle of trust},
	booktitle = {Proceeding of the 8th working conference on Mining software repositories - MSR {\textquoteright}11},
	year = {2011},
	note = {"we started by analyzing 219 projects"
},
	month = {05/2011},
	pages = {133-142},
	publisher = {ACM Press},
	organization = {ACM Press},
	address = {New York, New York, USA},
	abstract = {The success of an open-source project depends to a large degree on the proactive and constructive participation by the developer community. An important role that developers play in a project is that of a code committer. However, code-commit privilege is typically restricted to the core group of a project. In this paper, we study the phenomenon of the induction of external developers as code committers. The trustworthiness of an external developer is one of the key factors that determines the granting of commit privileges. Therefore, we formulate different hypotheses to explain how the trust is established in practice. To investigate our hypotheses, we developed an automated approach based on mining code repositories and bug-tracking systems. We implemented the approach and performed an empirical study, using the Eclipse projects, to test the hypotheses. Our results indicate that, most frequently, developers establish trust and credibility in a project by contributing to the project in a non-committer role. Moreover, the employing organization of a developer is another factor--although a less significant one--that influences trust.},
	keywords = {bug tracking, bug tracking system, commits, committers, core, developers, eclipse, trust},
	isbn = {9781450305747},
	doi = {10.1145/1985441.1985462},
	author = {Mani, Senthil and Sinha, Saurabh and Sinha, Vibha Singhal}
}
@conference {1307,
	title = {How do developers blog?},
	booktitle = {Proceedings of the 8th working conference on Mining software repositories - MSR {\textquoteright}11},
	year = {2011},
	note = {publishing frequency, post structure, word usage, publication patterns, content},
	month = {05/2011},
	pages = {123-132},
	publisher = {ACM Press},
	organization = {ACM Press},
	address = {New York, New York, USA},
	abstract = {We report on an exploratory study, which aims at understanding how software developers use social media compared to conventional development infrastructures. We analyzed the blogging and the committing behavior of 1,100 developers in four large open source communities. We observed that these communities intensively use blogs with one new entry about every 8 hours. A blog entry includes 14 times more words than a commit message. When analyzing the content of the blogs, we found that most popular topics represent high-level concepts such as functional requirements and domain concepts. Source code related topics are covered in less than 15\% of the posts. Our results also show that developers are more likely to blog after corrective engineering and management activities than after forward engineering and re-engineering activities. Our findings call for a hypothesis-driven research to further understand the role of social media in software engineering and integrate it into development processes and tools.},
	keywords = {blog, communication, developer, eclipse, gnome, LDA, postgres, python},
	isbn = {9781450305747},
	doi = {10.1145/1985441.1985461},
	author = {Maalej, Walid and Pagano, Dennis}
}
@conference {1306,
	title = {Java generics adoption},
	booktitle = {Proceedings of the 8th working conference on Mining software repositories - MSR {\textquoteright}11},
	year = {2011},
	note = {"we automatically analyzed 20 open source software projects. We analyzed the top {\textquotedblleft}most used{\textquotedblright} projects according to ohloh.net, including only projects with significant amounts of Java code"

"The 20 selected projects were Ant, Azureus, CheckStyle, Commons Collections, Free- Mind, FindBugs, Jetty, JEdit, JDT, JUnit, Eclipse-cs, Hibernate, Log4j, Lucene, Maven, the Spring Frame- work, Squirrel-SQL, Subclipse, Weka, and Xerces."

"In mining the full version histories of these 20 projects, we analyzed the full content of each version of each Java source file, a total of 548,982,841 lines."},
	month = {05/2011},
	pages = {3-12},
	publisher = {ACM Press},
	organization = {ACM Press},
	address = {New York, New York, USA},
	abstract = {Support for generic programming was added to the Java language in 2004, representing perhaps the most significant change to one of the most widely used programming languages today. Researchers and language designers anticipated this addition would relieve many long-standing problems plaguing developers, but surprisingly, no one has yet measured whether generics actually provide such relief. In this paper, we report on the first empirical investigation into how Java generics have been integrated into open source software by automatically mining the history of 20 popular open source Java programs, traversing more than 500 million lines of code in the process. We evaluate five hypotheses, each based on assertions made by prior researchers, about how Java developers use generics. For example, our results suggest that generics do not significantly reduce the number of type casts and that generics are usually adopted by a single champion in a project, rather than all committers.},
	keywords = {commits, generics, java, source code, version history},
	isbn = {9781450305747},
	doi = {10.1145/1985441.1985446},
	author = {Christian Bird and Murphy-Hill, Emerson and Parnin, Chris}
}
@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 {1303,
	title = {A study of language usage evolution in open source software},
	booktitle = {Proceedings of the 8th working conference on Mining software repositories - MSR {\textquoteright}11},
	year = {2011},
	month = {05/2011},
	pages = {13-22},
	publisher = {ACM Press},
	organization = {ACM Press},
	address = {Waikiki, Honolulu, HI, USA},
	abstract = {The use of programming languages such as Java and C in Open Source Software (OSS) has been well studied. However, many other popular languages such as XSL or XML have received minor attention. In this paper, we discuss some trends in OSS development that we observed when considering multiple programming language evolution of OSS. Based on the revision data of 22 OSS projects, we tracked the evolution of language usage and other artefacts such as documentation files, binaries and graphics files. In these systems several different languages and artefact types including C/C++, Java, XML, XSL, Makefile, Groovy, HTML, Shell scripts, CSS, Graphics files, JavaScript, JSP, Ruby, Phyton, XQuery, OpenDocument files, PHP, etc. have been used. We found that the amount of code written in different languages differs substantially. Some of our findings can be summarized as follows: (1) JavaScript and CSS files most often co-evolve with XSL; (2) Most Java developers but only every second C/C++ developer work with XML; (3) and more generally, we observed a significant increase of usage of XML and XSL during recent years and found that Java or C are hardly ever the only language used by a developer. In fact, a developer works with more than 5 different artefact types (or 4 different languages) in a project on average.},
	isbn = {9781450305747},
	doi = {10.1145/1985441.1985447},
	author = {Gall, Harald and Karus, Siim}
}
@conference {1310,
	title = {System compatibility analysis of Eclipse and Netbeans based on bug data},
	booktitle = {Proceedings of the 8th working conference on Mining software repositories - MSR {\textquoteright}11},
	year = {2011},
	month = {05/2011},
	pages = {230-233},
	publisher = {ACM Press},
	organization = {ACM Press},
	address = {Waikiki, Honolulu, HI, USANew York, New York, USA},
	abstract = {Eclipse and Netbeans are two top of the line Integrated Development Environments (IDEs) for Java development. Both of them provide support for a wide variety of development tasks and have a large user base. This paper provides an analysis and comparison for the compatibility and stability of Eclipse and Netbeans on the three most commonly used operating systems, Windows, Linux and Mac OS. Both IDEs are programmed in Java and use a Bugzilla issue tracker to track reported bugs and feature requests. We looked into the Bugzilla repository databases of these two IDEs, which contains the bug records and histories of these two IDEs. We used some basic data mining techniques to analyze some historical statistics of the bug data. Based on the analysis, we try to answer certain stability-comparison oriented questions in the paper, so that users can have a better idea which of these two IDEs is designed better to work on different platforms.

},
	keywords = {bug tracking system, bugzilla, eclipse, ms challenge, netbeans, version history},
	isbn = {9781450305747},
	doi = {10.1145/1985441.1985479},
	author = {Baik, Eilwoo and Devanbu, Premkar and Wang, Xinlei (Oscar)}
}
@conference {1312,
	title = {A tale of two browsers},
	booktitle = {Proceedings of the 8th working conference on Mining software repositories - MSR {\textquoteright}11},
	year = {2011},
	month = {05/2011},
	pages = {238-241},
	publisher = {ACM Press},
	organization = {ACM Press},
	address = {New York, New York, USA},
	abstract = {We explore the space of open source systems and their user communities by examining the development artifact histories of two popular web browsers -- Firefox and Chrome -- as well as usage data. By examining the data and addressing a number of research questions, two very different profiles emerge: Firefox, as the older and established system, with long product version cycles but short bug fix cycles, and a user base that is slow to adopt newer versions; and Chrome, as the new and fast evolving system, with short version cycles, longer bug fix cycles, and a user base that very quickly adopts new versions as they become available (due largely to Chrome{\textquoteright}s mandatory automatic updates).

},
	keywords = {chrome, development history, Firefox, msr challenge},
	isbn = {9781450305747},
	doi = {10.1145/1985441.1985481},
	author = {Davis, Ian and Godfrey, Michael W. and Baysal, Olga}
}
@conference {1305,
	title = {Visualizing collaboration and influence in the open-source software community},
	booktitle = {Proceedings of the 8th working conference on Mining software repositories - MSR {\textquoteright}11},
	year = {2011},
	note = {"This data set includes the complete social graph of 500,000 follow links as well as over 1,000,000 commits and 50,000 users."

"...a large fraction of [GitHub] users provide a location in their profile, which we can turn into geographic coordinates using a geocoding API like PlaceFinder...

"For each repository, we extract the owner, collaborator, and contributor usernames, plus branch names. New user- names help to find new repositories, while branch names are used to fetch commit metadata. Using this method, the crawler uncovered 40,860 code repositories, representing 33,388 unique project names and 1,219,872 individual commits."

"In addition to crawled data, we use the complete GitHub user follower graph from Jan 19, 2011. This graph includes 452,248 links connecting 106,247 unique users, 47\% (49,500) of which could be geocoded with the PlaceFinder API"},
	month = {05/2011},
	pages = {223-226},
	publisher = {ACM Press},
	organization = {ACM Press},
	address = {New York, New York, USA},
	abstract = {We apply visualization techniques to user profiles and repository metadata from the GitHub source code hosting service. Our motivation is to identify patterns within this development community that might otherwise remain obscured. Such patterns include the effect of geographic distance on developer relationships, social connectivity and influence among cities, and variation in project-specific contribution styles (e.g., centralized vs. distributed). Our analysis examines directed graphs in which nodes represent users{\textquoteright} geographic locations and edges represent (a) follower relationships, (b) successive commits, or (c) contributions to the same project. We inspect this data using a set of visualization techniques: geo-scatter maps, small multiple displays, and matrix diagrams. Using these representations, and tools based on them, we develop hypotheses about the larger GitHub community that would be difficult to discern using traditional lists, tables, or descriptive statistics. These methods are not intended to provide conclusive answers; instead, they provide a way for researchers to explore the question space and communicate initial insights.},
	keywords = {COLLABORATION, data exploration, geography, geoscatter, github, graph, mapping, metadata, open source, social graph, user profiles, visualization},
	isbn = {9781450305747},
	doi = {10.1145/1985441.1985476},
	url = {http://vis.stanford.edu/files/2011-GotHub-MSR.pdf},
	author = {Marschner, Eli and Rosenfeld, Evan and Heer, Jeffrey and Heller, Brandon}
}
@conference {1311,
	title = {What topics do Firefox and Chrome contributors discuss?},
	booktitle = {Proceedings of the 8th working conference on Mining software repositories - MSR {\textquoteright}11},
	year = {2011},
	month = {05/2011},
	pages = {234-237},
	publisher = {ACM Press},
	organization = {ACM Press},
	address = {New York, New York, USA},
	abstract = {Firefox and Chrome are two very popular open source Web browsers, implemented in C/C++. This paper analyzes what topics were discussed in Firefox and Chrome bug reports over time. To this aim, we indexed the text contained in bug reports submitted each semester of the project history, and identified topics using Latent Dirichlet Allocation (LDA). Then, we investigated to what extent Firefox and Chrome developers/contributors discussed similar topics, either in different periods, or over the same period. Results indicate a non-negligible overlap of topics, mainly on issues related to page layouting, user interaction, and multimedia contents.},
	keywords = {bug reports, chrome, Firefox, LDA, msr challenge},
	isbn = {9781450305747},
	doi = {10.1145/1985441.1985480},
	author = {Zagarese, Quirino and Distante, Damiano and Di Penta, Massimiliano and Bernardi, Mario Luca and Sementa, Carmine}
}
@article {10.1109/TSE.2010.63,
	title = {What Makes a Good Bug Report?},
	journal = {IEEE Transactions on Software Engineering},
	volume = {36},
	year = {2010},
	note = {"o find out which matter most, we asked 872 devel-
opers from the APACHE, ECLIPSE, and MOZILLA projects to:
1. Complete a survey on important information in bug reports and the problems they faced with them. We received a total of 156 responses to our survey (Section 2 and 3).
2. Rate the quality of bug reports from very poor to very good on a five-point Likert scale [22]. We received a total of 1,186 votes for 289 randomly selected bug reports (Section 4).
In addition, we asked 1,354 reporters1 from the same projects to complete a similar survey, out of which 310 responded. "},
	pages = {618-643},
	publisher = {IEEE Computer Society},
	address = {Los Alamitos, CA, USA},
	abstract = {In software development, bug reports provide crucial information to developers. However, these reports widely differ in their quality. We conducted a survey among developers and users of APACHE, ECLIPSE, and MOZILLA to find out what makes a good bug report.
The analysis of the 466 responses revealed an information mis- match between what developers need and what users supply. Most developers consider steps to reproduce, stack traces, and test cases as helpful, which are at the same time most difficult to provide for users. Such insight is helpful to design new bug tracking tools that guide users at collecting and providing more helpful information.
Our CUEZILLA prototype is such a tool and measures the quality of new bug reports; it also recommends which elements should be added to improve the quality. We trained CUEZILLA on a sample of 289 bug reports, rated by developers as part of the survey. In our experiments, CUEZILLA was able to predict the quality of 31{\textendash}48\% of bug reports accurately.},
	keywords = {bug report, Survey},
	issn = {0098-5589},
	doi = {http://doi.ieeecomputersociety.org/10.1109/TSE.2010.63},
	url = {http://dl.acm.org/citation.cfm?id=1453146},
	attachments = {https://flosshub.org/sites/flosshub.org/files/bettenburg-fse-2008.pdf},
	author = {Zimmermann, Thomas and Premraj, Rahul and Bettenburg, Nicolas and Sascha Just and Schroter, Adrian and Weiss, Cathrin}
}
@conference {972,
	title = {Extracting structural information from bug reports},
	booktitle = {Proceedings of the 2008 international workshop on Mining software repositories  - MSR {\textquoteright}08},
	year = {2008},
	month = {05/2008},
	pages = {27-30},
	publisher = {ACM Press},
	organization = {ACM Press},
	address = {New York, New York, USA},
	abstract = {In software engineering experiments, the description of bug reports is typically treated as natural language text, although it often contains stack traces, source code, and patches. Neglecting such structural elements is a loss of valuable information; structure usually leads to a better performance of machine learning approaches. In this paper, we present a tool called infoZilla that detects structural elements from bug reports with near perfect accuracy and allows us to extract them. We anticipate that infoZilla can be used to leverage data from bug reports at a different granularity level that can facilitate interesting research in the future.},
	keywords = {bug reports, eclipse, enumerations, infozilla, natural language, patches, source code, stack trace},
	isbn = {9781605580241},
	doi = {10.1145/1370750.1370757},
	attachments = {https://flosshub.org/sites/flosshub.org/files/p27-bettenburg.pdf},
	author = {Premraj, Rahul and Zimmermann, Thomas and Kim, Sunghun and Bettenburg, Nicolas}
}
@conference {Schuler:2008:MUE:1370750.1370779,
	title = {Mining usage expertise from version archives},
	booktitle = {Proceedings of the 2008 international working conference on Mining software repositories},
	series = {MSR {\textquoteright}08},
	year = {2008},
	month = {05/2008},
	pages = {121{\textendash}124},
	publisher = {ACM},
	organization = {ACM},
	address = {New York, NY, USA},
	abstract = {In software development, there is an increasing need to find and connect developers with relevant expertise. Existing expertise recommendation systems are mostly based on variations of the Line 10 Rule: developers who changed a file most often have the most implementation expertise. In this paper, we introduce the concept of usage expertise, which manifests itself whenever developers are using functionality, e.g., by calling API methods. We present preliminary results for the ECLIPSE project that demonstrate that our technique allows to recommend experts for files with no or little history, identify developers with similar expertise, and measure the usage of API methods.},
	keywords = {api, computer-supported cooperative work, eclipse, expertise, recommendation, scm, software repository, source code},
	isbn = {978-1-60558-024-1},
	doi = {http://doi.acm.org/10.1145/1370750.1370779},
	url = {http://doi.acm.org/10.1145/1370750.1370779},
	attachments = {https://flosshub.org/sites/flosshub.org/files/p121-schuler.pdf},
	author = {Schuler, David and Zimmermann, Thomas}
}
@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 {1000,
	title = {Mining Workspace Updates in CVS},
	booktitle = {Fourth International Workshop on Mining Software Repositories (MSR{\textquoteright}07:ICSE Workshops 2007)},
	year = {2007},
	pages = {11 - 11},
	publisher = {IEEE},
	organization = {IEEE},
	address = {Minneapolis, MN, USA},
	abstract = {The version control archive CVS records not only all changes in a project but also activity data such as when developers create or update their workspaces. Furthermore, CVS records when it has to integrate changes because of parallel development. In this paper, we analyze the CVS activity data of four large open-source projects GCC, JBOSS, JEDIT, and PYTHON to investigate parallel development: What is the degree of parallel development? How frequently do conflicts occur during updates and how are they resolved? How do we identify changes that contain integrations?},
	keywords = {change management, cvs, developers, gcc, jboss, jedit, python, workspaces},
	isbn = {0-7695-2950-X},
	doi = {10.1109/MSR.2007.22},
	attachments = {https://flosshub.org/sites/flosshub.org/files/28300011.pdf},
	author = {Zimmermann, Thomas}
}
@conference {Zimmermann:2006:MAM:1137983.1138025,
	title = {Mining additions of method calls in ArgoUML},
	booktitle = {Proceedings of the 2006 international workshop on Mining software repositories},
	series = {MSR {\textquoteright}06},
	year = {2006},
	pages = {169{\textendash}170},
	publisher = {ACM},
	organization = {ACM},
	address = {New York, NY, USA},
	abstract = {In this paper we refine the classical co-change to the addition of method calls. We use this concept to find usage patterns and to identify cross-cutting concerns for ArgoUML.},
	keywords = {argouml, change analysis, eclipse, function calls, mining challenge, msr challenge, pattern, source code, xelopes},
	isbn = {1-59593-397-2},
	doi = {http://doi.acm.org/10.1145/1137983.1138025},
	url = {http://doi.acm.org/10.1145/1137983.1138025},
	attachments = {https://flosshub.org/sites/flosshub.org/files/169MiningAdditions.pdf},
	author = {Zimmermann, Thomas and Breu, Silvia and Lindig, Christian and Livshits, Benjamin}
}
@conference {Breu:2006:MEC:1137983.1138006,
	title = {Mining eclipse for cross-cutting concerns},
	booktitle = {Proceedings of the 2006 international workshop on Mining software repositories},
	series = {MSR {\textquoteright}06},
	year = {2006},
	pages = {94{\textendash}97},
	publisher = {ACM},
	organization = {ACM},
	address = {New York, NY, USA},
	abstract = {Software may contain functionality that does not align with its architecture. Such cross-cutting concerns do not exist from the beginning but emerge over time. By analysing where developers add code to a program, our history-based mining identifies cross-cutting concerns in a two-step process. First, we mine CVS archives for sets of methods where a call to a specific single method was added. In a second step, such simple cross-cutting concerns are combined to complex cross-cutting concerns. To compute these efficiently, we apply formal concept analysis{\textemdash}an algebraic theory. History-based mining scales well: we are the first to report aspects mined from an industrial-sized project like Eclipse. For example, we identified a locking concern that crosscuts 1284 methods.},
	keywords = {aspects, concept analysis, cvs, eclipse, source code},
	isbn = {1-59593-397-2},
	doi = {http://doi.acm.org/10.1145/1137983.1138006},
	url = {http://doi.acm.org/10.1145/1137983.1138006},
	attachments = {https://flosshub.org/sites/flosshub.org/files/94MiningEclipse.pdf},
	author = {Breu, Silvia and Zimmermann, Thomas and Lindig, Christian}
}
@conference {Zimmermann:2006:MVA:1137983.1138001,
	title = {Mining version archives for co-changed lines},
	booktitle = {Proceedings of the 2006 international workshop on Mining software repositories},
	series = {MSR {\textquoteright}06},
	year = {2006},
	pages = {72{\textendash}75},
	publisher = {ACM},
	organization = {ACM},
	address = {New York, NY, USA},
	abstract = {Files, classes, or methods have frequently been investigated in recent research on co-change. In this paper, we present a first study at the level of lines. To identify line changes across several versions, we define the annotation graph which captures how lines evolve over time. The annotation graph provides more fine-grained software evolution information such as life cycles of each line and related changes: "Whenever a developer changed line 1 of version.txt she also changed line 25 of Library.java."},
	keywords = {change, change analysis, change management, graph, lines of code, source code},
	isbn = {1-59593-397-2},
	doi = {http://doi.acm.org/10.1145/1137983.1138001},
	url = {http://doi.acm.org/10.1145/1137983.1138001},
	attachments = {https://flosshub.org/sites/flosshub.org/files/72MiningVersionArchives.pdf},
	author = {Zimmermann, Thomas and Kim, Sunghun and Zeller, Andreas and Whitehead,Jr., E. James}
}
@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}
}
