Puzzle Solving as Debugging

We analyze existing data of students completing coding puzzles through the lens of a debugging process, in order to study the impact of different types of errors that students make as they solve the puzzle. We develop a scheme for categorizing the errors present in the student code at any given time, and use it to create a taxonomy of the trajectories that students take to arrive at the correct solution. We find that these metrics are expressive enough to capture important distinguishing characteristics of students' puzzle-solving strategies.