An Accountable Source-To-Source Transformation System

Though one is led to believe that program transformation systems which perform source-to-source transformations enable the user to understand and appreciate the resulting source program, this is not always the case. Transformations are capable of behaving and/or interacting in unexpected ways. The user who is interested in understanding the whats, whys, wheres, and hows of the transformation process is left without tools for discovering them. I provide an initial step towards the solution of this problem in the form of an accountable source-to-source transformation system. It carefully records the information necessary to answer such questions, and provides mechanisms for the retrieval of this information. It is observed that though this accountable system allows the user access to relevant facts from which he may draw conclusions, further study is necessary to make the system capable of analyzing these facts itself.

Switching Between Discrete and Continuous Process Models to Predict Molecular Genetic Activity

Two kinds of process models have been used in programs that reason about change: Discrete and continuous models. We describe the design and implementation of a qualitative simulator, PEPTIDE, which uses both kinds of process models to predict the behavior of molecular energetic systems. The program uses a discrete process model to simulate both situations involving abrupt changes in quantities and the actions of small numbers of molecules. It uses a continuous process model to predict gradual changes in quantities. A novel technique, called aggregation, allows the simulator to switch between theses models through the recognition and summary of cycles. The flexibility of PEPTIDE's aggregator allows the program to detect cycles within cycles and predict the behavior of complex situations.