\documentclass[runningheads]{llncs} \usepackage{amsmath} \usepackage{amssymb} \usepackage{cleveref} \usepackage{csquotes} \usepackage{minted} \usepackage{tikz} \usetikzlibrary{automata,positioning} \let\leq\leqslant \let\le\leqslant \let\geq\geqslant \let\ge\geqslant \DeclareMathOperator{\Uop}{\mathsf{U}} \newcommand{\PRISM}{\texttt{PRISM}} \begin{document} \title{Model Repair in Clean \textbackslash{}o/} \author{Camil Staps \and Erin van der Veen} \authorrunning{C. Staps \and E. van der Veen} \institute{% Radboud University, Nijmegen, The Netherlands\\ \email{\{c.staps,e.vanderveen\}@student.ru.nl}} \maketitle \begin{abstract} We discuss an approach to the repair of parametric models using an SMT solver. To repair a model $\mathcal M$ which does not satisfy a probabilistic CTL formula $\phi$, we add an additional parameter to the probability of each transition in $\mathcal M$, after which we eliminate all non-initial non-absorbing states. The SMT solver gets constraints to ensure that the repaired model remains valid and to satisfy $\phi$. Cost functions for the model repair problem can be formulated as a minimisation goal for the SMT solver. Unfortunately, some technical issues prevent us from using the tool in practice. We provide pointers to future work to resolve these issues. \end{abstract} \input{intro} \input{method} \input{implementation} \input{discussion} \input{future} \bibliography{library} \bibliographystyle{splncs04} \end{document}