@article {1396,
	title = {Studying the impact of social interactions on software quality},
	journal = {Empirical Software Engineering},
	year = {2012},
	note = {bug databases},
	abstract = {Correcting software defects accounts for a significant amount of resources in a software project. To make best use of testing efforts, researchers have studied statistical models to predict in which parts of a software system future defects are likely to occur. By studying the mathematical relations between predictor variables used in these models, researchers can form an increased understanding of the important connections between development activities and software quality. Predictor variables used in past top-performing models are largely based on source code-oriented metrics, such as lines of code or number of changes. However, source code is the end product of numerous interlaced and collaborative activities carried out by developers. Traces of such activities can be found in the various repositories used to manage development efforts. In this paper, we develop statistical models to study the impact of social interactions in a software project on software quality. These models use predictor variables based on social information mined from the issue tracking and version control repositories of two large open-source software projects. The results of our case studies demonstrate the impact of metrics from four different dimensions of social interaction on post-release defects. Our findings show that statistical models based on social information have a similar degree of explanatory power as traditional models. Furthermore, our results demonstrate that social information does not substitute, but rather augments traditional source code-based metrics used in defect prediction models.},
	keywords = {bug tracker, eclipse, Firefox, Human Factors, measurement, metrics, software evolution, Software quality assurance},
	issn = {1573-7616},
	doi = {10.1007/s10664-012-9205-0},
	author = {Bettenburg, Nicolas and Hassan, Ahmed E.}
}
@proceedings {1271,
	title = {Towards a Unified Definition of Open Source Quality},
	year = {2011},
	note = {"In order to answer the research question, how is quality defined in the FLOSS literature, we performed a literature review."

"we searched Google Scholar for journal articles and conference papers containing the terms {\textquotedblleft}open source{\textquotedblright} and {\textquotedblleft}quality{\textquotedblright}"

"This process left us with 24 papers, to which we then added 16 from the quality and defect-fixing categories in [34] that met the above stated criteria.
This left us with 40 papers that defined quality and performed some form of empirical validation of that definition."

"there is little consensus in the FLOSS literature when it comes to defining quality."

defect resolution versus modularity: "Defect resolution rates (amount of defects resolved, speed of resolution) are the best way to measure a community{\textquoteright}s commitment to quality, because they recognize that FLOSS is not a static product, but ever evolving. These rates should be calculated per release, and not cumulatively, because the cycle of FLOSS evolution is the release. Researchers should be careful to only include defects and not new feature requests, duplicates, or poorly reported bugs into their calculations.
Modularity is being touted as the main driver of FLOSS quality success, but it needs to be further defined and studied in order to understand how it works."},
	month = {10/2011},
	pages = {17-33},
	publisher = {Springer},
	abstract = {Software quality needs to be specified and evaluated in order to determine the success of a development project, but this is a challenge with Free/Libre Open Source Software (FLOSS) because of its permanently emergent state. This has not deterred the growth of the assumption that FLOSS is higher quality than traditionally developed software, despite of mixed research results. With this literature review, we found the reason for these mixed results is that that quality is being defined, measured, and evaluated differently. We report the most popular definitions, such as software structure measures, process measures, such as defect fixing, and maturity assessment models. The way researchers have built their samples has also contributed to the mixed results with different project properties being considered and ignored. Because FLOSS projects are evolving, their quality is too, and it must be measured using metrics that take into account its community{\textquoteright}s commitment to quality rather than just its software structure. Challenges exist in defining what constitutes a defect or bug, and the role of modularity in affecting FLOSS quality.},
	keywords = {literature review, measurement, open source, quality, Software},
	author = {Ruiz, Claudia and Robinson, William}
}
