@proceedings {1492,
	title = {Using Developer Interaction Data to Compare Expertise Metrics},
	year = {2013},
	month = {05/2013},
	abstract = {The expertise of a software developer is said to be
a crucial factor for the development time required to complete
a task. Even if this hypothesis is intuitive, research has not yet
quantified the effect of developer expertise on development time.
A related problem is that the design space for expertise metrics is
large; out of the various automated expertise metrics proposed,
we do not know which metric most reliably captures expertise.
What prevents a proper evaluation of expertise metrics and
their relation with development time is the lack of data on
development tasks, such as their precise duration. Fortunately,
this data is starting to become available in the form of growing
developer interaction repositories. We show that applying MSR
techniques to these developer interaction repositories gives us the
necessary tools to perform such an evaluation.},
	url = {http://users.dcc.uchile.cl/~rrobbes/p/MSR2013-expertise.pdf},
	attachments = {https://flosshub.org/sites/flosshub.org/files/MSR2013-expertise.pdf},
	author = {Robbes, Romain and Rothlisberger, David}
}
@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 {1359,
	title = {Linking e-mails and source code artifacts},
	booktitle = {Proceedings of the 32nd ACM/IEEE International Conference on Software Engineering - ICSE {\textquoteright}10},
	volume = {1},
	year = {2010},
	note = {"we devised a set of lightweight methods, based on regular expressions, to establish the link between e-mails and software artifacts. We evaluated them in terms of precision and recall considering one single Java system. In this paper we overcome a number of limitations of our previous work, resulting in the following contributions:
{\textbullet} An extensive and publicly available1 benchmark and toolset for recovering traceability links between e-mails and source code artifacts. We created our benchmark by analyzing the mailing lists of six different software systems written in four different programming languages. For each system we manually annotated a statistically significant number of e-mails.
{\textbullet} A comprehensive evaluation of linking techniques. We evaluated and compared, in terms of precision and recall, different linking methods, ranging from lightweight grep-style approaches to more complex approa- ches from the information retrieval (IR) field."},
	month = {05/2010},
	pages = {375-384},
	publisher = {ACM Press},
	organization = {ACM Press},
	address = {Cape Town, South Africa},
	abstract = {E-mails concerning the development issues of a system constitute an important source of information about high-level design decisions, low-level implementation concerns, and the social structure of developers.

Establishing links between e-mails and the software artifacts they discuss is a non-trivial problem, due to the inherently informal nature of human communication. Different approaches can be brought into play to tackle this traceability issue, but the question of how they can be evaluated remains unaddressed, as there is no recognized benchmark against which they can be compared.

In this article we present such a benchmark, which we created through the manual inspection of a statistically significant number of e-mails pertaining to six unrelated software systems. We then use our benchmark to measure the effectiveness of a number of approaches, ranging from lightweight approaches based on regular expressions to full-fledged information retrieval approaches.},
	isbn = {9781605587196},
	doi = {10.1145/1806799.1806855},
	url = {http://www.inf.usi.ch/phd/bacchelli/publications.php},
	author = {Bacchelli, Alberto and Lanza, Michele and Robbes, Romain}
}
@conference {966,
	title = {Replaying IDE interactions to evaluate and improve change 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 = {161 - 170},
	publisher = {IEEE},
	organization = {IEEE},
	address = {Cape Town, South Africa},
	abstract = {Change prediction helps developers by recommending program entities that will have to be changed alongside the entities currently being changed. To evaluate their accuracy, current change prediction approaches use data from versioning systems such as CVS or SVN. These data sources provide a coarse-grained view of the development history that flattens the sequence of changes in a single commit. They are thus not a valid basis for evaluation in the case of development-style prediction, where the order of the predictions has to match the order of the changes a developer makes. We propose a benchmark for the evaluation of change prediction approaches based on fine-grained change data recorded from IDE usage. Moreover, the change prediction approaches themselves can use the more accurate data to fine-tune their prediction. We present an evaluation procedure and use it on several change prediction approaches, both novel and from the literature, and report on the results.},
	keywords = {cbse, change based software evolution, change prediction, changes, commit, cvs, development history, eclipseeye, ide, mylyn, spyware, svn},
	isbn = {978-1-4244-6802-7},
	doi = {10.1109/MSR.2010.5463278},
	attachments = {https://flosshub.org/sites/flosshub.org/files/161Robbes2010changePrediction.pdf},
	author = {Robbes, Romain and Pollet, Damien 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}
}
