The study presented in this paper forms part of a larger initiative aimed at creating a generic architecture for the development of intelligent programming tutors (IPTs) in an attempt to reduce the costs associated with building IPTs. Thus, instead of requiring the lecturer to provide solution algorithms to the programming problems that students will be tested on by the system, the generic architecture will automatically generate the solutions to these problems. This paper reports on the results of an investigation conducted to test the hypothesis that genetic programming (GP) can be used for this purpose. The paper proposes a genetic programming system for the induction of solutions to arithmetic, character and string manipulation, conditional, iterative, nested iteration, and recursive problems. The paper analyses the results of applying the proposed system to 45 randomly chosen novice procedural programming problems. Extensions made to the proposed system based on this analysis, namely, the implementation of the iterative structure-based algorithm (ISBA), are discussed.
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