This thesis is concerned with the use of Software Engineering abstraction constructs to help in the process of understanding computer programs that are built as part of experiments in the Symbolic Paradigm. It is also concerned with developing and testing a method to analyse these programs in an organised and structured way. In a series of three experiments, the use of abstraction constructs to help the process of transforming a program to a more abstract form, and how to do this in a structured way, was incrementally investigated. This involved first exploring the use of abstraction constructs to achieve higher degrees of abstraction in a small example; the next step was to use the understanding of their use and of how to transform a program in a bigger exanple, from which a more clearly defined role of the abstraction constructs, and an initial scheme for transforming a program, was achieved; the last step involved investigating a complete form of an analysis procedure to analyse experimental programs built by incremental prototying, and that is supported by the use of abstraction constructs. The result is the Prototype Analysis Method (PAM): a static analysis method to help in the understanding of incrementally built experimental computer programs in AI. An essential part of this method is a transformation process that is supported by the use of Software Engineering abstraction constructs, and of test sets from dynamic analysis for validation. This research clearly demonstrates the successful application of Software Engineering abstraction constructs is an important aspect of AI research. Results from this research also point to further interesting issues such as the relation between Knowledge Level descriptions and abstract Symbol Level descriptions.