Context-oriented programming applied to image processing



Context-oriented programming is a paradigm that addresses crosscutting concerns and context-dependent behavior in a program. This paradigm makes it possible to express aspects of a program behavior that are orthogonal to the object model, while maintaining its abstraction and modularity. In the domain of image processing, for instancecontext-oriented programming may be used to model aspects related to the structure of an image, its content or even its memory representation. We present context-oriented programming, and we analyze the crosscutting concerns existing in Climb, an image processing library written in Common Lisp. We then explain how context-oriented programming solves those concerns. Finally, we analyze the advantages of context-oriented programming in the domain of image processing