Tool selection was performed according to the DESMET [Kitchenham96] guidelines for feature analysis. Since the choice of a good support tool is crucial for the success of the whole project, but the resources for the selection process were limited, the feature analysis was performed so as to be extremely effective, i.e. able to give the maximum discrimination at the minimum cost.
During each step of the feature analysis (feature elicitation, tool assessment and score analysis) several Effective Feature Analysis Strategies (EFAS) were adopted with the purpose of increasing the discrimination between tools and reducing the cost needed to converge to the final choice. This paper reports on that experience and highlights all the lessons learned in terms of acquired EFAS.