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Export Reference (APA) 
Goulão, Miguel & Brito e Abreu, F. (2007). Modeling the Experimental Software Engineering Process. In 6th International Conference on the Quality of Information and Communications Technology (QUATIC'2007). (pp.  77-90 ). Lisboa, Portugal:  IEEE Computer Society .
Export Reference (IEEE) 
M. C. Goulão and F. M. Abreu,  "Modeling the Experimental Software Engineering Process", in 6th Int. Conf. on the Quality of Information and Communications Technology (QUATIC'2007), Lisboa, Portugal,  IEEE Computer Society , 2007, vol. 1, pp.  77-90
Export BibTeX 
@inproceedings{goulão2007_1716161019433,
	author = "Goulão, Miguel and Brito e Abreu, F.",
	title = "Modeling the Experimental Software Engineering Process",
	booktitle = "6th International Conference on the Quality of Information and Communications Technology (QUATIC'2007)",
	year = "2007",
	editor = "",
	volume = "1",
	number = "",
	series = "",
	doi = "10.1109/QUATIC.2007.18",
	pages = " 77-90 ",
	publisher = " IEEE Computer Society ",
	address = "Lisboa, Portugal",
	organization = "CS03/IPQ",
	url = "http://2007.quatic.org"
}
Export RIS 
TY  - CPAPER
TI  - Modeling the Experimental Software Engineering Process
T2  - 6th International Conference on the Quality of Information and Communications Technology (QUATIC'2007)
VL  - 1
AU  - Goulão, Miguel
AU  - Brito e Abreu, F.
PY  - 2007
SP  -  77-90 
DO  - 10.1109/QUATIC.2007.18
CY  - Lisboa, Portugal
UR  - http://2007.quatic.org
AB  - Reviews on software engineering literature have shown an insufficient experimental validation of claims, when compared to the standard practice in other well-established sciences. Poor validation of software engineering claims increases the risks of introducing changes in the software process of an organization, as the potential benefits assessment is based on hype, rather than on facts. The community lacks highly disseminated experimental best practices. We contribute with a model of the experimental software engineering process that is aligned with recent proposals for best practices in experimental data dissemination. The model can be used in the definition of software engineering experiments and in comparisons among experimental results.
ER  -