Anurag Mendhekar

Open implementation design guidelines

Designing reusable software modules can be extremely difficult. The design must be balanced between being general enough to address the needs of a wide range of clients and being focused enough to truly satisfy the requirements of each specific client. One area where it can be particularly difficult to strike this balance is in the implementation strategy of the module. The problem is that general-purpose implementation strategies, tuned for a wide range of clients, aren’t necessarily optimal for each specific client— this is especially an issue for modules that are intended to be reusable and yet provide highperformance. An examination of existing software systems shows that an increasingly important technique for handling this problem is to design the module’s interface in such a way that the client can assist or participate in the selection of the module’s implementation strategy. We call this approach open implementation. When designing the interface to a module that allows its clients some control over its implementation strategy, it is important to retain, as much as possible, the advantages of traditional closed implementation modules. This paper explores issues in the design of interfaces to open implementation modules. We identify key design choices, and present guidelines for deciding which choices are likely to work best in particular situations.

Aspect-Oriented Programming of Sparse Matrix Code

The expressiveness conferred by high-level and object-oriented languages is often impaired by concerns that cross-cut a programs basic functionality. Execution time, data representation, and numerical stability are three such concerns that are of great interest to numerical analysts. Using aspect-oriented programming we have created AML, a system for sparse matrix computation that deals with these concerns separately and explicitly while preserving the expressiveness of the original functional language. The resulting code maintains the efficiency of highly tuned low-level code, yet is ten times shorter.