Reverse Engineering Architectural Feature Models

Reverse engineering the variability of an existing system is a challenging activity. The architect knowledge is essential to identify variation points and explicit constraints between features, for instance in feature models (FMs), but the manual creation of FMs is both time-consuming and error-prone. On a large scale, it is very difficult for an architect to guarantee that the resulting FM is consistent with the architecture it is associated with. In this paper, we present a comprehensive, tool supported process for reverse engineering architectural FMs. We develop automated techniques to extract and combine different variability descriptions of an architecture. Then, alignment and reasoning techniques are applied to integrate the architect knowledge and reinforce the extracted FM. We illustrate the process when applied to a representative software system and we report on our experience in this context.