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On the feasability of feature based composition for programming in the large

Feature-based composition complements object-oriented composition by enabling the coherent extension of multiple entities (objects, classes). This paradigm enables an integral feature to be the subject of composition rather than fragments of features. The conventional object model of state-of-the-art OO programming languages does not incorporate the notion of features. Therefore, in the traditional OO context, feature based development often requires careful coding in order to add feature fragments to a working application. This state of practice is particularly limiting productivity in the development of large software systems. In this position paper, we sketch the Lasagne model for software composition and we argue that it is well-suited for organizing systems with large amounts of objects and classes. In general, we believe that features are the key concept in achieving complex composition scenarios in large software systems though challenges remain to be tackled. We have experienced and articulated some of the limitations of feature oriented programming. We introduce these elements as a basis for further discussion at the PPPL workshop.