Article (Scientific journals)
Polite Combination of Algebraic Datatypes
Sheng, Ying; Zohar, Yoni; Ringeissen, Christophe et al.
2022In Journal of Automated Reasoning, 66 (3), p. 331 - 355
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Keywords :
Algebraic datatypes; Automated reasoning; Polite combination; Satisfiability Modulo Theories; Theory combination; Algebraic data-types; Combination method; Datatypes; Satisfiability modulo Theories; Theory solvers; Computational Theory and Mathematics; Artificial Intelligence
Abstract :
[en] Algebraic datatypes, and among them lists and trees, have attracted a lot of interest in automated reasoning and Satisfiability Modulo Theories (SMT). Since its latest stable version, the SMT-LIB standard defines a theory of algebraic datatypes, which is currently supported by several mainstream SMT solvers. In this paper, we study this particular theory of datatypes and prove that it is strongly polite, showing how it can be combined with other arbitrary disjoint theories using polite combination. The combination method uses a new, simple, and natural notion of additivity that enables deducing strong politeness from (weak) politeness.
Disciplines :
Computer science
Author, co-author :
Sheng, Ying;  Stanford University, Stanford, United States
Zohar, Yoni;  Bar Ilan University, Ramat Gan, Israel
Ringeissen, Christophe;  Université de Lorraine, CNRS, Inria, LORIA, France
Lange, Jane;  MIT, Cambridge, United States
Fontaine, Pascal ;  Université de Liège - ULiège > Département d'électricité, électronique et informatique (Institut Montefiore) > Systèmes informatiques distribués
Barrett, Clark;  Stanford University, Stanford, United States
Language :
English
Title :
Polite Combination of Algebraic Datatypes
Publication date :
August 2022
Journal title :
Journal of Automated Reasoning
ISSN :
0168-7433
eISSN :
1573-0670
Publisher :
Springer Science and Business Media B.V.
Volume :
66
Issue :
3
Pages :
331 - 355
Peer reviewed :
Peer Reviewed verified by ORBi
Funding text :
This project was partially supported by a Grant from the Defense Advanced Research Projects Agency (N66001-18-C-4012), the Stanford CURIS program, and Jasmin Blanchette’s European Research Council (ERC) starting Grant Matryoshka (713999)
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