Goulão, M., and F. B. Abreu,
"Modeling the Experimental Software Engineering Process",
6th International Conference on the Quality of Information and Communications Technology (QUATIC'2007), Lisbon, Portugal, IEEE Computer Society, pp. 77-90, 12-14 Sep., 2007.
AbstractReviews 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.
Monteiro, R., J. Araújo, V. Amaral, M. Goulão, and P. Patrício,
"Model-Driven Development for Requirements Engineering: The Case of Goal-Oriented Approaches",
8th International Conference on the Quality of Information and Communications Technology (QUATIC 2012), Lisbon, Portugal, IEEE CPS, 2012.
AbstractGoal-Oriented Requirements Engineering (GORE) has received increasing attention over the past few years.
There are several goal-oriented approaches, each one using different kinds of models. We argue that it would be useful to relate them or even perform transformations among them automatically, in order to understand their similarities and differences, their advantages and disadvantages, allowing a possible migration or comparison between approaches. This is something that has not received enough attention. In this paper
we propose the definition and implementation of goal model transformations between i* and KAOS. As an immediate contribution, the approach can be used to migrate from one goal model to another through automatic model transformations. This approach also contributes to relate the concepts of i* and KAOS models and will help, for example, a development team in making the decision on which approach to follow, according to the nature of the project and the expressiveness of an approach to represent certain concepts
(e.g., obstacles are represented explicitly in KAOS, but not in i*). Another contribution is to facilitate communication among members of the same team, if they are specialized in different approaches.
Espada, P., M. Goulão, and J. Araújo,
"Measuring Complexity and Completeness of KAOS Goal Models",
International Workshop on Empirical Requirements Engineering (EmpiRE 2011), at the 19th International Requirements Engineering Conference (RE 2011), Trento, Italy, IEEE Computer Society, 30 Aug., 2011.
Abstracthttp://dx.doi.org/10.1109/EmpiRE.2011.6046252
KAOS is one of the most well-known goal-oriented requirements engineering approaches. Nevertheless, building large KAOS models sometimes results in incomplete and/or complex requirements models that are difficult to understand and maintain. These shortcomings often lead to an increase in costs of product development and evolution. Therefore, for large-scale systems, the ability to manage the complexity and completeness of KAOS models is essential. In this paper, we propose a metrics suite for supporting the quantitative assessment of KAOS models complexity and completeness, in order to support their early identification. We apply the metrics to an example taken from a health club system specification.