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        <datestamp>2024-03-06T10:07:43Z</datestamp>
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          <dc:title>Implementing RPO and POLO using SAT</dc:title>
          <dc:creator>Schneider-Kamp, Peter</dc:creator>
          <dc:creator>Fuhs, Carsten</dc:creator>
          <dc:creator>Thiemann, René</dc:creator>
          <dc:creator>Giesl, Jürgen</dc:creator>
          <dc:creator>Annov, Elena</dc:creator>
          <dc:creator>Codish, Michael</dc:creator>
          <dc:creator>Middeldorp, Aart</dc:creator>
          <dc:creator>Zankl, Harald</dc:creator>
          <dc:subject>Termination</dc:subject>
          <dc:subject>SAT</dc:subject>
          <dc:subject>recursive path order</dc:subject>
          <dc:subject>polynomial interpretation</dc:subject>
          <dc:description>Well-founded orderings are the most basic, but also most important&#13;
ingredient to virtually all termination analyses. The recursive&#13;
path order with status (RPO) and polynomial interpretations (POLO)&#13;
are the two classes that are the most popular in the termination&#13;
analysis of term rewrite systems. Numerous fully automated search&#13;
algorithms for these classes have therefore been devised and&#13;
implemented in termination tools.&#13;
&#13;
Unfortunately, the performance of these algorithms on all but the&#13;
smallest termination problems has been lacking. E.g., recently&#13;
developed transformations from programming languages like Haskell&#13;
or Prolog allow to apply termination tools for term rewrite systems&#13;
to real programming languages. The results of the transformations&#13;
are often of non-trivial size, though, and cannot be handled&#13;
efficiently by the existing algorithms.&#13;
&#13;
The need for more efficient search algorithms has triggered research&#13;
in reducing these search problems into decision problems for&#13;
which more efficient algorithms already exist. Here, we introduce an&#13;
encoding of RPO and POLO to the satisfiability of propositional logic&#13;
(SAT). We implemented these encodings in our termination tool AProVE.&#13;
Extensive experiments have shown that one can obtain speedups in&#13;
orders of magnitude by this encoding and the application of modern&#13;
SAT solvers.&#13;
&#13;
The talk is based on joint work with Elena Annov, Mike Codish, Carsten Fuhs,&#13;
JÃƒÂ¼rgen Giesl, Aart Middeldorp, RenÃƒÂ© Thiemann, and Harald Zankl.</dc:description>
          <dc:publisher>Schloss Dagstuhl – Leibniz-Zentrum für Informatik</dc:publisher>
          <dc:contributor>Peter Schneider-Kamp and Carsten Fuhs and René Thiemann and Jürgen Giesl and Elena Annov and Michael Codish and Aart Middeldorp and Harald Zankl</dc:contributor>
          <dc:date>2007</dc:date>
          <dc:relation>Is Part Of Dagstuhl Seminar Proceedings, Volume 7401, Deduction and Decision Procedures (2007)</dc:relation>
          <dc:type>InProceedings</dc:type>
          <dc:type>Text</dc:type>
          <dc:type>doc-type:ResearchArticle</dc:type>
          <dc:type>publishedVersion</dc:type>
          <dc:format>application/pdf</dc:format>
          <dc:identifier>doi:10.4230/DagSemProc.07401.5</dc:identifier>
          <dc:identifier>urn:nbn:de:0030-drops-12491</dc:identifier>
          <dc:identifier>https://drops.dagstuhl.de/entities/document/10.4230/DagSemProc.07401.5</dc:identifier>
          <dc:language>eng</dc:language>
          <dc:rights>https://creativecommons.org/licenses/by/4.0/legalcode</dc:rights>
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