Donald Bren School of Information and Computer Sciences

This research concerns the problem of specifying the information relationships and their transformations included, explicitly and implicitly, in any problem-solving procedure. Our view of data representation is that problem representations (in a problem domain) are mapped to a machine representation (in an implementation domain) through various modelling representations (in modelling domains). Modelling domain representations make easier the discovery of acceptable implementation representations. We propose to focus on the study of mappings of data representations and their transformations from the modelling to implementation domains. Specifically, our goal is to answer four questions:

1) what are appropriate formalisms for describing modelling domains and implenentation domains,

2) what knowledge exists of each of these domains and how can this knowledge be represented in our formalisms,

3) how do we map specific representations from one domain to the other, and

4) how can we test the completeness of our formalisms and mapping process.

In answering the fourth question, we propose to construct an interactive system for generating alternative implementation domain representations from a modelling domain representation and selecting that which comes closest to the user's desired program performance criteria in an actual programming context.