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Selfadjusting binary search trees
, 1985
"... The splay tree, a selfadjusting form of binary search tree, is developed and analyzed. The binary search tree is a data structure for representing tables and lists so that accessing, inserting, and deleting items is easy. On an nnode splay tree, all the standard search tree operations have an am ..."
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Cited by 435 (19 self)
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The splay tree, a selfadjusting form of binary search tree, is developed and analyzed. The binary search tree is a data structure for representing tables and lists so that accessing, inserting, and deleting items is easy. On an nnode splay tree, all the standard search tree operations have
SELFADJUSTING HEAPS
, 1986
"... In this paper we explore two themes in data structure design: amortized computational complexity and selfadjustment. We are motivated by the following observations. In most applications of data structures, we wish to perform not just a single operation but a sequence of operations, possibly having ..."
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Cited by 51 (2 self)
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. In this paper we develop the skew heap, a selfadjusting form of heap related to the leftist heaps of Crane and Knuth. (What we mean by a heap has also been called a “priority queue” or a “mergeable heap”.) Skew heaps use less space than leftist heaps and similar worstcaseefficient data structures
SKEW HEAPS: SelfAdjusting Heaps
"... In this handout we describe the skew heap data structure, a selfadjusting form of heap related to the leftist heap of Crane and Knuth. Skew heaps, in contrast to leftist heaps, use less space and are easier to implement, and yet in the amortized sense they are as efficient, to within a constant fac ..."
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In this handout we describe the skew heap data structure, a selfadjusting form of heap related to the leftist heap of Crane and Knuth. Skew heaps, in contrast to leftist heaps, use less space and are easier to implement, and yet in the amortized sense they are as efficient, to within a constant
SelfAdjusting Computation
 In ACM SIGPLAN Workshop on ML
, 2005
"... From the algorithmic perspective, we describe novel data structures for tracking the dependences ina computation and a changepropagation algorithm for adjusting computations to changes. We show that the overhead of our dependence tracking techniques is O(1). To determine the effectiveness of change ..."
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Cited by 49 (19 self)
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From the algorithmic perspective, we describe novel data structures for tracking the dependences ina computation and a changepropagation algorithm for adjusting computations to changes. We show that the overhead of our dependence tracking techniques is O(1). To determine the effectiveness
Imperative selfadjusting computation
 In POPL ’08: Proceedings of the 35th annual ACM SIGPLANSIGACT symposium on Principles of programming languages
, 2008
"... Recent work on selfadjusting computation showed how to systematically write programs that respond efficiently to incremental changes in their inputs. The idea is to represent changeable data using modifiable references, i.e., a special data structure that keeps track of dependencies between read an ..."
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Cited by 35 (17 self)
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Recent work on selfadjusting computation showed how to systematically write programs that respond efficiently to incremental changes in their inputs. The idea is to represent changeable data using modifiable references, i.e., a special data structure that keeps track of dependencies between read
Selfadjusting top trees
, 2005
"... The dynamic trees problem is that of maintaining a forest that changes over time through edge insertions and deletions. We can associate data with vertices or edges, and manipulate this data individually or in bulk, with operations that deal with whole paths or trees. Efficient solutions to this pro ..."
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Cited by 23 (3 self)
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The dynamic trees problem is that of maintaining a forest that changes over time through edge insertions and deletions. We can associate data with vertices or edges, and manipulate this data individually or in bulk, with operations that deal with whole paths or trees. Efficient solutions to this problem have numerous applications, particularly in algorithms for network flows and dynamic graphs in general. Several data structures capable of logarithmictime dynamic tree operations have been proposed. The first was Sleator and Tarjan’s STtree [16, 17], which represents a partition of the tree into paths. Although reasonably fast in practice, adapting STtrees to different applications is nontrivial. Topology trees [9], top trees [3], and RCtrees [1] are based on tree contractions: they progressively combine vertices or edges to obtain a hierarchical representation of the tree. This approach is more flexible in theory, but all known implementations assume the trees have bounded degree; arbitrary trees are supported only after ternarization. We show how these two approaches can be combined (with very little overhead) to produce a data structure that is as generic as any other, very easy to adapt, and as practical as STtrees.
Selfadjusting stack machines
, 2011
"... Selfadjusting computation offers a languagebased approach to writing programs that automatically respond to dynamically changing data. Recent work made significant progress in developing sound semantics and associated implementations of selfadjusting computation for highlevel, functional languag ..."
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Cited by 5 (2 self)
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Selfadjusting computation offers a languagebased approach to writing programs that automatically respond to dynamically changing data. Recent work made significant progress in developing sound semantics and associated implementations of selfadjusting computation for highlevel, functional
Programmable SelfAdjusting Computation
, 2010
"... and by donations from Intel Corporation. The views and conclusions contained in this document are those of the author and should not be interpreted as representing the official policies, either expressed or implied, of any sponsoring institution, the U.S. government or any other entity. Keywords: se ..."
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Cited by 2 (0 self)
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: selfadjusting computation, adaptivity, memoization, changepropagation, continuationpassing style, typed compilation, cost semantics, trace distance, traceable Selfadjusting computation is a paradigm for programming incremental computations that efficiently respond to input changes by updating
Published In SelfAdjusting Programming
"... This papers proposes techniques for writing selfadjusting programs that can adjust to any change to their data (e.g., inputs, decisions made during the computation) etc. We show that the techniques are efficient by considering a number of applications including several sorting algorithms, and the ..."
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, and the Graham Scan, and the quick hull algorithm for computing convex hulls. We show that the techniques are flexible by showing that selfadjusting programs can be trivially transformed into a kinetic programs that maintain their property as their input move continuously. We show that the techniques
SelfAdjusting Programming
, 2005
"... This papers proposes techniques for writing selfadjusting programs that can adjust to any change to their data (e.g., inputs, decisions made during the computation) etc. We show that the techniques are e#cient by considering a number of applications including several sorting algorithms, and the Gra ..."
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This papers proposes techniques for writing selfadjusting programs that can adjust to any change to their data (e.g., inputs, decisions made during the computation) etc. We show that the techniques are e#cient by considering a number of applications including several sorting algorithms
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