Solving Horn Clauses on Inductive Data Types Without Induction

EMANUELE DE ANGELIS, FABIO FIORAVANTI, ALBERTO PETTOROSSI, MAURIZIO PROIETTI
<span title="">2018</span> <i title="Cambridge University Press (CUP)"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/yhwvj6mbzza5tfz766tokherka" style="color: black;">Theory and Practice of Logic Programming</a> </i> &nbsp;
AbstractWe address the problem of verifying the satisfiability of Constrained Horn Clauses (CHCs) based on theories of inductively defined data structures, such as lists and trees. We propose a transformation technique whose objective is the removal of these data structures from CHCs, hence reducing their satisfiability to a satisfiability problem for CHCs on integers and booleans. We propose a transformation algorithm and identify a class of clauses where it always succeeds. We also consider
more &raquo; ... extension of that algorithm, which combines clause transformation with reasoning on integer constraints. Via an experimental evaluation we show that our technique greatly improves the effectiveness of applying the Z3 solver to CHCs. We also show that our verification technique based on CHC transformation followed by CHC solving, is competitive with respect to CHC solvers extended with induction.
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1017/s1471068418000157">doi:10.1017/s1471068418000157</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/ovs527z7qjd45odoz2psaybax4">fatcat:ovs527z7qjd45odoz2psaybax4</a> </span>
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