A Conflict-Driven Solving Procedure for Poly-Power Constraints

  • Cheng-Chao Huang
  • Ming Xu
  • Zhi-Bin Li


This paper studies the satisfiability problem of poly-power constraints (conjunctions of poly-power equations and inequalities), in which poly-powers are univariate nonlinear functions that extend integer exponents of polynomials to real algebraic exponents. To solve the poly-power constraint, we present a sound and complete procedure that incorporates conflict-driven learning with the exclusion algorithm for isolating positive roots of poly-powers. Furthermore, we introduce a kind of optimal interval-splitting, based on the Stern–Brocot tree and on binary rational numbers respectively, so that the operands occurring in the execution are chosen to be as simple as possible. The solving procedure, thereby, turns out to be promisingly efficient on randomly generated examples.


Constraint solving Computer algebra Root isolation Satisfiability modulo theories Conflict-driven learning 



The authors thank the reviewers, whose careful and insightful comments improve the presentation of the paper and clarify inconsistencies significantly.


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© Springer Nature B.V. 2018

Authors and Affiliations

  1. 1.Shanghai Key Lab of Multidimensional Information ProcessingEast China Normal UniversityShanghaiChina
  2. 2.Department of Computer Science and TechnologyEast China Normal UniversityShanghaiChina

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