Abstract
Experience using constrain programming to solve real-life problems has shown that finding an efficient solution to a problem often requires experimentation with different constrain solvers or even building a problem-specific solver. HAL is a new constrain logic programming language expressly designed to facilitate this process. In this paper we examine different ways of building solvers in HAL. We explain how type classes can be used to specify solver interfaces, allowing the constrain programmer to support modelling of a constrain problem independently of a particular solver, leading to easy “plug and play” experimentation. We compare a number of different ways of writing a simple solver in HAL: using dynamic scheduling, constrain handling rules and building on an existing solver. We also examine how external solvers may be interfaced with HAL, and approaches for removing interface overhead.
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References
F. Bueno, M. Garcia de la Banda, M. Hermenegildo, K. Marriott, G. Puebla, and P.J. Stuckey. A model for inter-module analysis and optimizing compilation. In Procs of LOPSTR2000, volume 2042 of LNCS, pages 86–102, 2001.
P. Codognet and D. Diaz.Boolean constrain solving using clp(FD). In Procs. of ILPS’1993, pages 525–539. MIT Press,1993.
B. Demoen, M. Garc ía de la Banda, W. Harvey, K. Marriott, and P.J. Stuckey. An overview of HAL. In Procs. of PPCP’ 99, LNCS, pages 174–188, 1999.
A.J. Fernüandez and B.C. Ruiz Jiménez. Una semántica operacional para CProlog. In Proceedings of II Jornadas de Informática, pages 21–30, 1996.
T. Frühwirth. CHR home page.http://www.informatik.uni-muenchen.de/~fruehwir/chr/.
T. Frühwirth. Theory and practice of constrain handling rules. Journal of Logic Programming, 37:95–138, 1998.
W. Harvey and P.J. Stuckey. Constrain representation for propagation. In Procs. of PPCP’98, LNCS, pages 235–249. Springer-Verlag, 1998.
C. Holzbaur, P.J. Stuckey, M. García de la Banda, and D. Jeffery. Optimizing compilation of constrain handling rules. In Procs. of ICLP17, LNCS, 2001.
D. Jeffery, F. Henderson, and Z. Somogyi. Type classes in Mercury. Technical Report 98/13, University of Melbourne, Australia, 1998.
S. Kaes. Parametric overloading in polymorphic programming languages. In ESOP’88 Programming Languages and Systems, volume 300 of LNCS, pages 131–141, 1988.
K. Marriott and P.J. Stuckey. Programming with Constraints:an Introduction. MIT Press, 1998.
Z. Somogyi, F. Henderson, and T. Conway. The execution algorithm of Mercury: an efficient purely declarative logic programming language. JLP, 29:17–64, 1996.
M. Trick. http://mat.gsia.cmu.edu/COLOR/color.html.
P. Wadler and S. Blott. How o make ad-hoc polymorphism less ad-hoc. In Proc. 16th ACM POPL, pages 60–76, 1989.
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de la Banda, M.G., Jeffery, D., Marriott, K., Nethercote, N., Stuckey, P.J., Holzbaur, C. (2001). Building Constraint Solvers with HAL. In: Codognet, P. (eds) Logic Programming. ICLP 2001. Lecture Notes in Computer Science, vol 2237. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-45635-X_14
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DOI: https://doi.org/10.1007/3-540-45635-X_14
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