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A Simple Linear Time Algorithm for . . .
"... A circulararc model M = (C, A) is a circle C together with a collection A of arcs of C. If no arc is contained in any other then M is a proper circulararc model, and if some point of C is not covered by any arc then M is an interval model. A (proper) (interval) circulararc graph is the intersecti ..."
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is the intersection graph of a (proper) (interval) circulararc model. Circulararc graphs and their subclasses have been the object of a great deal of attention in the literature. Linear time recognition algorithms have been described both for the general class and for some of its subclasses. For the isomorphism
A simple linear time algorithm for cograph recognition
 Discrete Applied Mathematics
, 2005
"... www.elsevier.com/locate/dam ..."
A simple linear time algorithm for cograph recognition
, 2005
"... All intext references underlined in blue are linked to publications on ResearchGate, letting you access and read them immediately. ..."
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All intext references underlined in blue are linked to publications on ResearchGate, letting you access and read them immediately.
Simple LinearTime Algorithms for Minimal Fixed Points (Extended Abstract)
, 1998
"... We present global and local algorithms for evaluating minimal fixed points of dependency graphs, a general problem in fixedpoint computation and model checking. Our algorithms run in lineartime, matching the complexity of the best existing algorithms for similar problems, and are simple to unders ..."
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Cited by 30 (0 self)
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We present global and local algorithms for evaluating minimal fixed points of dependency graphs, a general problem in fixedpoint computation and model checking. Our algorithms run in lineartime, matching the complexity of the best existing algorithms for similar problems, and are simple
A Simple Linear Time Algorithm for Embedding Maximal Planar Graphs
, 1993
"... All existing algorithms for planarity testing/planar embedding can be grouped into two principal classes. Either, they run in linear time, but to the expense of complex algorithmic concepts or complex datastructures, or they are easy to understand and implement, but require more than linear time [ ..."
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Cited by 2 (1 self)
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[2]. In this paper, a new lineartime algorithm for embedding maximal planar graphs is proposed. This algorithm is both easy to understand and easy to implement. The algorithm consists of three phases which use only simple, local graphmodifications. In addition to planar embedding, the new algorithm
A Simple LinearTime Algorithm for Finding PathDecompositions of Small Width
 also University of Victoria manuscript
, 1996
"... We described a simple algorithm running in linear time for each fixed constant k, that either establishes that the pathwidth of a graph G is greater than k, or finds a pathdecomposition of G of width at most O(2^k). This provides a simple proof of the result by Bodlaender that many families of grap ..."
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Cited by 3 (2 self)
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We described a simple algorithm running in linear time for each fixed constant k, that either establishes that the pathwidth of a graph G is greater than k, or finds a pathdecomposition of G of width at most O(2^k). This provides a simple proof of the result by Bodlaender that many families
A Simple Linear Time Algorithm for Proper Box Rectangular Drawing of Plane Graphs
 Journal of Algorithms
, 2000
"... In this paper we introduce a new drawing style of a plane graph G, called proper box rectangular (PBR ) drawing. It is defined to be a drawing of G such that every vertex is drawn as a rectangle, called a box, each edge is drawn as either a horizontal or a vertical line segment, and each face is dra ..."
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Cited by 6 (0 self)
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is drawn as a rectangle. We establish necessary and sufficient conditions for G to have a PBR drawing. We also give a simple linear time algorithm for finding such drawings. The PBR drawing is closely related to the box rectangular (BR ) drawing defined by Rahman, Nakano and Nishizeki [17]. Our method can
Page 1 of 5A Simple, LinearTime Algorithm for x86 Jump Encoding
, 2008
"... The problem of spaceoptimal jump encoding in the x86 instruction set, also known as branch displacement optimization, is described, and a lineartime algorithm is given that uses no complicated data structures, no recursion, and no randomization. The only assumption is that there are no array decla ..."
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The problem of spaceoptimal jump encoding in the x86 instruction set, also known as branch displacement optimization, is described, and a lineartime algorithm is given that uses no complicated data structures, no recursion, and no randomization. The only assumption is that there are no array
A simple linear time algorithm for computing a (2k − 1)spanner of O(n 1+1/k ) size in weighted graphs
 In Proceedings of the 30th International Colloquium on Automata, Languages and Programming
, 2003
"... ) edges are required in the worst case for any (2k \Gamma 1)spanner, which has been proved for k = 1; 2; 3; 5. There exist polynomial time algorithms that can construct spanners with the size that matches this conjectured lower bound, and the best known algorithm takes O(mn 1=k) expected running ti ..."
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Cited by 43 (5 self)
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time. In this paper, we present an extremely simple linear time randomized algorithm that computes a (2k \Gamma 1)spanner of size matching the conjectured lower bound. An important feature of our algorithm is its local approach. Unlike all the previous algorithms which require computation of shortest
Linear pattern matching algorithms
 IN PROCEEDINGS OF THE 14TH ANNUAL IEEE SYMPOSIUM ON SWITCHING AND AUTOMATA THEORY. IEEE
, 1972
"... In 1970, Knuth, Pratt, and Morris [1] showed how to do basic pattern matching in linear time. Related problems, such as those discussed in [4], have previously been solved by efficient but suboptimal algorithms. In this paper, we introduce an interesting data structure called a bitree. A linear ti ..."
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Cited by 549 (0 self)
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In 1970, Knuth, Pratt, and Morris [1] showed how to do basic pattern matching in linear time. Related problems, such as those discussed in [4], have previously been solved by efficient but suboptimal algorithms. In this paper, we introduce an interesting data structure called a bitree. A linear
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