Diagnostic of programs for programming learning tools

Abstract

It is not easy for a student to develop programming skills and learn how to construct their own problem solving algorithms. Well designed materials and tools can guide programming students knowledge and skill construction. Such tools may allow students to acquire better and faster, the necessary programming skills. In this paper we show the results of some experiments realized on a set of faulty student's programs using PROPAT_DEBUG, an automatic program debugger, based on the Model Based Diagnosis technique of Artificial Intelligence. The results show that during the interactive debugging process it is possible for a student to learn by answering the questions posed by the AI diagnosis system to discriminate its fault hypotheses. © Springer-Verlag Berlin Heidelberg 2006.