Strategic programming is a generic programming idiom for processing compound data such as terms or object structures. At the heart of the approach is the separation of two concerns: basic dataprocessing computations vs. traversal schemes. Actual traversals are composed by passing the former as arguments to the latter. Traversal schemes can be defined by the strategic programmer using a combinator style that relies on primitives for layered traversal. In this paper, we take a look at strategic programming from an aspect-oriented programming perspective. Throughout the paper, we compare strategic programming with adaptive programming, which is a well-established aspectual approach to the traversal of object structures. We start from the observation that aspect-oriented programming terms, e.g., crosscutting, join point, and advice can be instantiated for aspectual traversal approaches.

Abstract. Strategic programming is generic programming with the use of strategies. A strategy is a generic data-processing action which can traverse into heterogeneous data structures while mixing uniform and type-specific behaviour. With strategic programming, one gains full control over the application of basic actions, most notably full traversal control. Using a combinator style, traversal schemes can be defined, and actual traversals are obtained by passing the problem-specific ingredients as parameters to suitable schemes. The prime application domain for strategic programming is program transformation and analysis. In this paper, we provide a language-independent definition that generalises over existing incarnations of this idiom in term rewriting, functional programming, and object-oriented programming.