Data-Driven Program Synthesis for Hint Generation in Programming Tutors

摘要

One of the main functions of intelligent tutoring systems is providing feedback to help students solve problems. We present a novel approach to program synthesis that can be used as a basis for automatic hint generation in programming tutors. Instead of using a state-space representation of the problem-solving process, our method finds a set of textual edits commonly used by students on program code. Given an incorrect program it then synthesizes new programs by applying sequences of edits until a solution is found. The edit sequence can be used to provide hints with varying levels of detail. Experimental results confirm the feasibility of our approach.