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\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.
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\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}
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