Abstract

Aspect-oriented programming (AOP) seeks to improve software modularity via the separation of cross-cutting concerns. AOP proponents often advocate a development strategy where programmers write the main application (base code), ignoring cross-cutting concerns, and then aspect programmers, domain experts in their specific concerns, weave in the logic for these more specialized cross-cutting concerns. This purely oblivious strategy, however, has empirically been shown to tightly couple aspects to base code in many cases, hindering aspect modularity and reuse. In essence, the more intricate the weaving between the cross-cutting concern and the base code (lexically and/or semantically), the harder it becomes to: (a) robustly specify how to weave the aspects in at the required points, (b) capture interactions between aspects and base code, and (c) preserve the correct weaving as the base code evolves. We propose an alternate methodology, termed cooperative aspect-oriented programming (Co-AOP), where complete lexical separation of concerns is not taken as an absolute requirement. Instead, cross-cutting concerns are explicitly modeled as abstract interfaces through explicit join points (EJPs). Programmers specify where these interfaces interact with base code either through explicit lexical references or via traditional oblivious aspects. This explicit awareness allows base code and aspects to cooperate in ways that were previously not possible: arbitrary blocks of code can be advised, advice can be explicitly parameterized, base code can guide aspects in where to apply advice, and aspects can statically enforce new constraints upon the base code that they advise. These new techniques allow aspect modularity and program safety to increase, and bring us towards a cooperative AOP paradigm. We illustrate our methodology via an example on transactions, and also give an initial evaluation of cooperative AOP through an empirical study on program extensibility comparing both the traditional and cooperative AOP methodologies. Initial results show that cooperative AOP techniques result in code that is less complex with lower overall coupling, facilitating extensibility.

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