Easy problems for tree-decomposable graphs
Journal of Algorithms
Algorithms on strings, trees, and sequences: computer science and computational biology
Algorithms on strings, trees, and sequences: computer science and computational biology
All structured programs have small tree width and good register allocation
Information and Computation
Linear-time register allocation for a fixed number of registers
Proceedings of the ninth annual ACM-SIAM symposium on Discrete algorithms
A linear space algorithm for computing maximal common subsequences
Communications of the ACM
Treewidth: Algorithmoc Techniques and Results
MFCS '97 Proceedings of the 22nd International Symposium on Mathematical Foundations of Computer Science
The Treewidth of Java Programs
ALENEX '02 Revised Papers from the 4th International Workshop on Algorithm Engineering and Experiments
Tree-partite graphs and the complexity of algorithms
FCT '85 Fundamentals of Computation Theory
Experimental evaluation of a tree decomposition-based algorithm for vertex cover on planar graphs
Discrete Applied Mathematics - Structural decompositions, width parameters, and graph labelings (DAS 5)
Table design in dynamic programming
Information and Computation
Algorithm engineering: bridging the gap between algorithm theory and practice
Algorithm engineering: bridging the gap between algorithm theory and practice
Graph minors and parameterized algorithm design
The Multivariate Algorithmic Revolution and Beyond
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Many dynamic programming algorithms that solve a decision problem can be modified to algorithms that solve the construction variant of the problem by additional bookkeeping and going backwards through stored answers to subproblems. It is also well known that for many dynamic programming algorithms, one can save memory space by throwing away tables of information that is no longer needed, thus reusing the memory. Somewhat surprisingly, the observation that these two modifications cannot be combined is frequently not made. In this paper we consider the case of dynamic programming algorithms on graphs of bounded treewidth. We give algorithms to solve the construction variants of such problems that use only twice the amount of memory space of the decision versions, with only a logarithmic factor increase in running time. Using the concept of strong directed treewidth we then discuss how these algorithms can be applied to dynamic programming in general.