Hostname: page-component-78c5997874-g7gxr Total loading time: 0 Render date: 2024-11-10T16:33:31.699Z Has data issue: false hasContentIssue false

(Co-)Inductive semantics for Constraint Handling Rules

Published online by Cambridge University Press:  06 July 2011

RÉMY HAEMMERLÉ*
Affiliation:
Technical University of Madrid, Madrid, Spain

Abstract

In this paper, we address the problem of defining a fixpoint semantics for Constraint Handling Rules (CHR) that captures the behavior of both simplification and propagation rules in a sound and complete way with respect to their declarative semantics. Firstly, we show that the logical reading of states with respect to a set of simplification rules can be characterized by a least fixpoint over the transition system generated by the abstract operational semantics of CHR. Similarly, we demonstrate that the logical reading of states with respect to a set of propagation rules can be characterized by the greatest fixpoint. Then, in order to take advantage of both types of rules without losing fixpoint characterization, we present a new operational semantics with persistent constraints.

We finally establish that this semantics can be characterized by two nested fixpoints, and we show that the resulting language is an elegant framework to program using coinductive reasoning.

Type
Regular Papers
Copyright
Copyright © Cambridge University Press 2011

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

References

Abdennadher, S. 1997. Operational semantics and confluence of Constraint Propagation Rules. In Third International Conference on Principles and Practice of Constraint Programming (CP), LNCS, vol. 1330. Springer, Berlin, 252266.Google Scholar
Abdennadher, S., Frühwirth, T. and Meuss, H. 1999. Confluence and semantics of Constraint Simplification Rules. Constraints 4, 2, 133165.CrossRefGoogle Scholar
Barwise, J. and Moss, L. 1996. Vicious Circles. CSLI, Stanford, CA.Google Scholar
Betz, H., Raiser, F. and Frühwirth, T. 2010. A complete and terminating execution model for Constraint Handling Rules. Theory and Practice of Logic Programming 10, special issues 4–6 (ICLP), 597610.CrossRefGoogle Scholar
Bezem, M. and Coquand, T. 2005. Automating coherent logic. In International Conferences on Logic for Programming, Artificial Intelligence and Reasoning (LPAR), LNCS, vol. 3835. Springer, Berlin, 246260.Google Scholar
Clarke, E. M., Grumberg, O. and Peled, D. A. 2000. Model Checking. MIT Press, Cambridge, MA.Google Scholar
de Koninck, L., Schrijvers, T. and Demoen, B. 2007. User-definable rule priorities for CHR. In 9th International Conference on Principles and Practice of Declarative Programming, July 14–16, Wroclaw, Poland(PPDP). ACM, New York, 2536.Google Scholar
Frühwirth, T. 1998. Theory and practice of Constraint Handling Rules. Journal of Logic Programming 37, 1–3, 95138.CrossRefGoogle Scholar
Frühwirth, T. 2009. Constraint Handling Rules. Cambridge University Press, Cambridge, UK.CrossRefGoogle Scholar
Gabbrielli, M. and Meo, M. 2009. A compositional semantics for CHR. ACM Transactions Computer Logic 10, 2.CrossRefGoogle Scholar
Gabbrielli, M., Meo, M. and Tacchella, P. 2008. A compositional semantics for CHR with propagation rules. In Constraint Handling Rules: Current Research Topics. LNAI, vol. 5388. Springer, Berlin, 119160.CrossRefGoogle Scholar
Goguen, J. A., Lin, K. and Rosu, G. 2000. Circular coinductive rewriting. In Proceedings of the 15th IEEE International Conference on Automated Software Engineering. ASE, Washington, DC, 123132.Google Scholar
Haemmerlé, R. 2011. Toward Logically Complete Fixpoint Semantics for Constraint Hangling Rules. Technical Report CLIP3/2011, Technical University of Madrid, Madrid, Spain.Google Scholar
Haemmerlé, R. and Fages, F. 2007. Abstract critical pairs and confluence of arbitrary binary relations. In Conference on Rewriting Techniques and Applications, LNCS, vol. 4533. Springer, New York, 214228.Google Scholar
Haemmerlé, R., Lopez-Garcia, P. and Hemenegildo, M. V. To appear. CLP projection for constraint handling rules. In Conference on Principles and Practice of Declarative Programming (PPDP). ACM, New York.Google Scholar
Jaffar, J. and Lassez, J.-L. 1987. Constraint logic programming. In Symposium on Principles of Programming Languages (POPL). ACM, New York, 111119.Google Scholar
Lloyd, J. 1987. Foundations of Logic Programming. Springer, Berlin.CrossRefGoogle Scholar
Raiser, F., Betz, H. and Frühwirth, T. 2009. Equivalence of CHR States Revisited. CHR Report CW 555. Katholieke University, Leuven, Belgium, 34–48.Google Scholar
Rutten, J. 1998. Automata and coinduction (an exercise in coalgebra). In Proceedings of the Ninth International Conference on Concurrency Theory (CONCUR), LNCS, vol. 1466. Springer, New York, 194218.Google Scholar
Saraswat, V. A., Rinard, M. C. and Panangaden, P. 1991. Semantic foundations of concurrent constraint programming. In Proceedings of Principles of Programming Languages (POPL). ACM, New York, 333352.Google Scholar
Simon, L., Mallya, A., Bansal, A. and Gupta, G. 2006. Coinductive logic programming. In International Conference on Logic Programming (ICLP), LNCS, vol. 4079. Springer, Berlin, 330345.Google Scholar
Tarski, A. 1955. A lattice-theoretical fixpoint theorem and its applications. Pacific Journal of Mathematics 5 (2), 285309.CrossRefGoogle Scholar
Terese, . 2003. Term Rewriting Systems, Vol. 55. Cambridge University Press, Cambridge, UK.Google Scholar