@conference {1357,
	title = {Content classification of developer emails},
	booktitle = {Proceedings of the 34th IEEE/ACM International Conference On Software Engineering (ICSE 2012)},
	year = {2012},
	note = {We created a web application to manually classify email content in the chosen categories. We classified a statistically significant set of emails from four java open source software (OSS) systems, used to evaluate the accuracy of our approach.
The contributions of this paper are:
1) a novel approach that fuses parsing and ML techniques
for classification of email lines;
2) a web application to manually classify email content; 3) the manual classification of a statistically significant
sample set of emails (for a total of 67,792 lines) from mailing lists of four different software systems{\textendash}in the form of a freely available benchmark; and
4) the empirical evaluation of our approach against the benchmark},
	month = {06/2012},
	abstract = {Emails related to the development of a software system contain information about design choices and issues encountered during the development process. Exploiting the knowledge embedded in emails with automatic tools is challenging, due to the unstructured, noisy and mixed language nature of this communication medium. Natural language text is often not well-formed and is interleaved with languages with other syntaxes, such as code or stack traces.

We present an approach to classify email content at line level. Our technique classifies email lines in five categories (i.e., text, junk, code, patch, and stack trace) to allow one to subsequently apply ad hoc analysis techniques for each category. We evaluated our approach on a statistically significant set of emails gathered from mailing lists of four unrelated open source systems.},
	keywords = {email, Emails, Empirical software engineering, mailing list, natural language, Unstructured Data Mining},
	url = {http://www.inf.usi.ch/phd/bacchelli/publications.php},
	attachments = {https://flosshub.org/sites/flosshub.org/files/icse2012.pdf},
	author = {Bacchelli, Alberto and Dal Sasso, Tommaso and D{\textquoteright}Ambros, Marco and Lanza, Michele}
}
@conference {950,
	title = {An extensive comparison of bug prediction approaches},
	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 = {31 - 41},
	publisher = {IEEE},
	organization = {IEEE},
	address = {Cape Town, South Africa},
	abstract = {Reliably predicting software defects is one of software engineering{\textquoteright}s holy grails. Researchers have devised and implemented a plethora of bug prediction approaches varying in terms of accuracy, complexity and the input data they require. However, the absence of an established benchmark makes it hard, if not impossible, to compare approaches. We present a benchmark for defect prediction, in the form of a publicly available data set consisting of several software systems, and provide an extensive comparison of the explanative and predictive power of well-known bug prediction approaches, together with novel approaches we devised. Based on the results, we discuss the performance and stability of the approaches with respect to our benchmark and deduce a number of insights on bug prediction models.},
	keywords = {apache, bug reports, eclipse, famix, lucene, mylyn, prediction, scm},
	isbn = {978-1-4244-6802-7},
	doi = {10.1109/MSR.2010.5463279},
	attachments = {https://flosshub.org/sites/flosshub.org/files/31dambrosLanzaRobbes31.pdf},
	author = {D{\textquoteright}Ambros, Marco and Lanza, Michele and Robbes, Romain}
}
@conference {1358,
	title = {Extracting source code from e-mails},
	booktitle = {Proceedings of ICPC 2010 (18th IEEE International Conference on Program Comprehension)},
	year = {2010},
	note = {"We want to extract source code fragments from e-mail messages. To do this, we first need to select e-mails that contain source code fragments, and then we extract such fragments from the content in which they are enclosed."

"we manually build a statistically significant benchmark taking sample e- mails from five unrelated open source Java software systems."

},
	pages = {24-33},
	abstract = {E-mails, used by developers and system users to communicate over a broad range of topics, offer a valuable source of information. If archived, e-mails can be mined to support program comprehension activities and to provide views of a software system that are alternative and complementary to those offered by the source code.

However, e-mails are written in natural language, and therefore contain noise that makes it difficult to retrieve the important data. Thus, before conducting an effective system analysis and extracting data for program comprehension, it is necessary to select the relevant messages, and to expose only the meaningful information.

In this work we focus both on classifying e-mails that hold fragments of the source code of a system, and on extracting the source code pieces inside the e-mail. We devised and analyzed a number of lightweight techniques to accomplish these tasks. To assess the validity of our techniques, we manually inspected and annotated a statistically significant number of e-mails from five unrelated open source software systems written in Java. With such a benchmark in place, we measured the effectiveness of each technique in terms of precision and recall.},
	keywords = {argouml, email, freenet, jmeter, mailing lists, mina, natural language, openjpa, source code},
	url = {http://www.inf.usi.ch/phd/bacchelli/publications.php},
	attachments = {https://flosshub.org/sites/flosshub.org/files/icpc2010.pdf},
	author = {Bacchelli, Alberto and D{\textquoteright}Ambros, Marco and Lanza, Michele}
}
@conference {1360,
	title = {Benchmarking Lightweight Techniques to Link E-Mails and Source Code},
	booktitle = {2009 16th Working Conference on Reverse Engineering},
	year = {2009},
	note = {"We present different lightweight approaches that, exploiting the specific characteristics of e-mails and the ones of the source code, are capable of establishing a bi-directional link between source code entities and e-mails"

"We analyzed ArgoUML1, a UML modelling tool written in Java, developed over the course of approximately 9 years, and made available under the BSD Open Source License. We consider the release 0.28 (March 2009) that comprehends 2,197 classes. We employed the lightweight approaches to map such classes to the related e-mails in ArgoUML mailing lists.
ArgoUML e-mails are stored in six mailing lists (see Table I), for a total amount of 79,175 messages"

Figure 4 is helpful to understand what this does.},
	pages = {205 - 214},
	publisher = {IEEE},
	organization = {IEEE},
	address = {Lille, France},
	abstract = {During the evolution of a software system, a large amount of information, which is not always directly related to the source code, is produced. Several researchers have provided evidence that the contents of mailing lists represent a valuable source of information: Through e-mails, developers discuss design decisions, ideas, known problems and bugs, etc. which are otherwise not to be found in the system.

A technical challenge in this context is how to establish the missing link between free-form e-mails and the system artifacts they refer to. Although the range of approaches is vast, establishing their accuracy remains a problem, as there is no benchmark against which to compare their performance.

To overcome this issue, we manually inspected a statistically significant number of e-mails pertaining to the ArgoUML system. Based on this benchmark, we present a variety of lightweight techniques to assign e-mails to software artifacts and measure their effectiveness in terms of precision and recall.},
	keywords = {argouml, email, mailing lists},
	isbn = {978-0-7695-3867-9},
	doi = {10.1109/WCRE.2009.44},
	attachments = {https://flosshub.org/sites/flosshub.org/files/wcre2009.pdf},
	author = {Bacchelli, Alberto and D{\textquoteright}Ambros, Marco and Lanza, Michele and Robbes, Romain}
}
@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 {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}
}
