\documentclass{llncs} \usepackage[utf8]{inputenc} \usepackage{fancyvrb} \fvset{commandchars=\\\{\},baselinestretch=0.98,samepage=true,xleftmargin=5mm} \usepackage{forest} \newcommand\code[1]{\texttt{#1}} \newcommand\red[1]{{\begingroup\color[rgb]{0.8,0.15,0.15}#1\endgroup}} \newcommand\hl[1]{\textbf{#1}} \begin{document} \title{Patterns for debugging student programs} \author{TODO} \institute{University of Ljubljana, Faculty of Computer and Information Science, Slovenia} \maketitle \begin{abstract} We propose new program features to support mining data from student submissions in a programming tutor. We extract syntax-tree patterns from student programs, and use them as features to induce rules for predicting program correctness. Discovered rules allow us to correctly classify a large majority of submissions based only on their structural features. Rules can be used to recognize intent, and provide hints in a programming tutor by pointing out incorrect or missing patterns. Evaluating out approach on past student data, we were able to find errors in over 80\% of incorrect submissions. \\\\ \textbf{Keywords:} Intelligent tutoring systems · Programming · Hint generation \end{abstract} \input{introduction} \input{background} \input{dataset} \input{method} \input{evaluation} \input{conclusion} \bibliographystyle{splncs} \bibliography{aied2017} \end{document}