Understanding feature modularity

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Date

2006

Authors

Lopez Herrejon, Roberto Erick

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Abstract

Features are increments in program functionality. Feature abstraction, the process of abstracting programs into their constituent features, is a relatively common yet informal practice in software design. It is common because it simplifies program understanding. It is also important for software product lines whose essence is the systematic and efficient creation of software products from a shared set of assets or features, where each product exhibits common functionality with other products but also has unique functionalities. Thus, it seems natural to modularize feature abstractions and use such modules as building blocks of programs and product lines. Unfortunately, conventional modularization approaches such as methods, classes and packages are not geared for supporting feature modules. They present two recurrent problems. First, a typical feature implementation is spread over several conventional modules. Second, features are usually more than source code artifacts as they can modularize many different program representations (makefiles, documentation, performance models). An undesirable consequence is that developers must lower their abstractions from features to those provided by the underlying implementation languages, a process that is far from simple let alone amenable to significant automation. The conceptual gap created between feature abstractions and their modularization hinders program understanding and product line development. The root of the problem is the fact that feature modularity is not well understood and thus not well supported in conventional programming languages, modularization mechanisms, and design techniques. In this dissertation, we explore language and modularity support for features founded on an algebraic model geared for program synthesis. Our model integrates ideas from collaboration-based designs, mixin layers, aspect oriented programming, multidimensional separation of concerns, and generative programming. We assess our model with an implementation of a non-trivial product line case study, and evaluate feature support in emerging modularization technologies.

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