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  <id>06076914</id>
  <dt>a</dt>
  <an>06076914</an>
  <augroup>
    <au>Gao, Sicun</au>
    <au>Avigad, Jeremy</au>
    <au>Clarke, Edmund M.</au>
  </augroup>
  <ti>$\delta $-complete decision procedures for satisfiability over the reals.</ti>
  <so>Gramlich, Bernhard (ed.) et al., Automated reasoning. 6th international joint conference, IJCAR 2012, Manchester, UK, June 26--29, 2012. Proceedings. Berlin: Springer (ISBN 978-3-642-31364-6/pbk). Lecture Notes in Computer Science 7364. Lecture Notes in Artificial Intelligence, 286-300 (2012).</so>
  <py>2012</py>
  <pu>Berlin: Springer</pu>
  <lagroup>
    <la>EN</la>
  </lagroup>
  <ccgroup>
  </ccgroup>
  <utgroup>
  </utgroup>
  <cigroup>
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  <ligroup>
    <li>doi:10.1007/978-3-642-31365-3_23</li>
  </ligroup>
  <abgroup>
    <ab>Summary: We introduce the notion of ``$\delta $-complete decision procedures'' for solving SMT problems over the real numbers, with the aim of handling a wide range of nonlinear functions including transcendental functions and solutions of Lipschitz-continuous ODEs. Given an SMT problem $\varphi $ and a positive rational number $\delta $, a $\delta $-complete decision procedure determines either that $\varphi $ is unsatisfiable, or that the ``$\delta $-weakening'' of $\varphi $ is satisfiable. Here, the $\delta $-weakening of $\varphi $ is a variant of $\varphi $ that allows $\delta $-bounded numerical perturbations on $\varphi $. We establish the existence and complexity of $\delta $-complete decision procedures for bounded SMT over reals with functions mentioned above. We propose to use $\delta $-completeness as an ideal requirement for numerically-driven decision procedures. As a concrete example, we formally analyze the DPLL$\langle $ICP$\rangle $ framework, which integrates Interval Constraint Propagation in DPLL$(T)$, and establish necessary and sufficient conditions for its $\delta $-completeness. We discuss practical applications of $\delta $-complete decision procedures for correctness-critical applications including formal verification and theorem proving.</ab>
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