Direct methods for sparse matrices
Direct methods for sparse matrices
An algorithm for solving parametric linear systems
Journal of Symbolic Computation
Computer algebra (2nd ed.): systems and algorithms for algebraic computation
Computer algebra (2nd ed.): systems and algorithms for algebraic computation
A Machine-Oriented Logic Based on the Resolution Principle
Journal of the ACM (JACM)
An Assume Facility for CAS, with a Sample Implementation for Maple
DISCO '92 Proceedings of the International Symposium on Design and Implementation of Symbolic Computation Systems
Proceedings of the 2007 ACM SIGPLAN symposium on Partial evaluation and semantics-based program manipulation
Digital workspace for optimal E-business strategies
DNCOCO'08 Proceedings of the 7th conference on Data networks, communications, computers
Science of Computer Programming
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Algorithms in computer algebra are usually designed for a fixed set of domains. For example, algorithms over the domain of polynomials are not applicable to parameters because the inherent assumption that the indeterminate X bears no algebraic relation to other objects is violated.We propose to use a technique from model theory known as constraint programming to gain more flexibility, and we show how it can be applied to the Gaussian algorithm to be used for parametric systems. Our experiments suggest that in practice this leads to results comparable to the algorithm for parametric linear systems by Sit [9] --- at least if the parameters are sparse.