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Making Data Structures Persistent
, 1989
"... This paper is a study of persistence in data structures. Ordinary data structures are ephemeral in the sense that a change to the structure destroys the old version, leaving only the new version available for use. In contrast, a persistent structure allows access to any version, old or new, at any t ..."
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Cited by 250 (6 self)
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This paper is a study of persistence in data structures. Ordinary data structures are ephemeral in the sense that a change to the structure destroys the old version, leaving only the new version available for use. In contrast, a persistent structure allows access to any version, old or new, at any time. We develop simple, systematic, and effiient techniques for making linked data structures persistent. We use our techniques to devise persistent forms of binary search trees with logarithmic access, insertion, and deletion times and O(1) space bounds for insertion and deletion.
Reactive search: machine learning for memorybased heuristics
 Teofilo F. Gonzalez (Ed.), Approximation Algorithms and Metaheuristics, Taylor & Francis Books (CRC Press
, 2005
"... 1 Introduction: the role of the user in heuristics Most stateoftheart heuristics are characterized by a certain number of choices and free parameters, whose appropriate setting is a subject that raises issues of research methodology [5, 41, 51]. In some cases, these parameters are tuned through a ..."
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Cited by 13 (5 self)
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1 Introduction: the role of the user in heuristics Most stateoftheart heuristics are characterized by a certain number of choices and free parameters, whose appropriate setting is a subject that raises issues of research methodology [5, 41, 51]. In some cases, these parameters are tuned through a feedback loop that includes the user as a crucial learning component: depending on preliminary algorithm tests some parameter values are changed by the
Binary Search Trees of Almost Optimal Height
 ACTA INFORMATICA
, 1990
"... First we present a generalization of symmetric binary Btrees, SBB(k) trees. The obtained structure has a height of only \Sigma (1 + 1k) log(n + 1)\Upsilon, where k may be chosen to be any positive integer. The maintenance algorithms require only a constant number of rotations per updating operati ..."
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Cited by 11 (1 self)
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First we present a generalization of symmetric binary Btrees, SBB(k) trees. The obtained structure has a height of only \Sigma (1 + 1k) log(n + 1)\Upsilon, where k may be chosen to be any positive integer. The maintenance algorithms require only a constant number of rotations per updating operation in the worst case. These properties together with the fact that the structure is relatively simple to implement makes it a useful alternative to other search trees in practical applications. Then, by using an SBB(k)tree with a varying k we achieve a structure with a logarithmic amortized cost per update and a height of log n + o(log n). This result is an improvement of the upper bound on the height of a dynamic binary search tree. By maintaining two trees simultaneously the amortized cost is transformed into a worstcase cost. Thus, we have improved the worstcase complexity of the dictionary problem.
Optimal Finger Search Trees in the Pointer Machine
, 2002
"... We develop a new finger search tree with worst case constant update time in the Pointer Machine (PM) model of computation. This was a major problem in the field of Data Structures and was tantalizingly open for over twenty years, while many attempts by researchers were made to solve it. The result c ..."
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Cited by 10 (3 self)
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We develop a new finger search tree with worst case constant update time in the Pointer Machine (PM) model of computation. This was a major problem in the field of Data Structures and was tantalizingly open for over twenty years, while many attempts by researchers were made to solve it. The result comes as a consequence of the innovative mechanism that guides the rebalancing operations, combined with incremental multiple splitting and fusion techniques over nodes.
Partially Persistent Dynamic Sets for HistorySensitive Heuristics
"... Effective heuristic algorithmsfor combinatorial problems are based on integrating local neighborhood search with historysensitive schemes, where the information collected during the previous search phase is used to direct the future effort. In particular, some algorithms (like Strict Tabu Search ..."
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Cited by 3 (3 self)
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Effective heuristic algorithmsfor combinatorial problems are based on integrating local neighborhood search with historysensitive schemes, where the information collected during the previous search phase is used to direct the future effort. In particular, some algorithms (like Strict Tabu Search and Reactive Tabu Search) need to detect whether a configuration has already been encountered during the previous phase of the search, either to prohibit repetitions or to determine a prohibition parameter in an adaptive way. This paper analyzes the use of persistent dynamic sets for storing and retrieving states and discusses the advantages of this option with respect to popular but less efficient realizations. If the search space is given by Lbit binary strings, the method complexity is O(L) averagecase time per search iteration when hashing is used, while the total space for a sequence of t iterations is O(t).
A New Weight Balanced Binary Search Tree
"... We develop a new class of weight balanced binary search trees called/?balanced binary search trees (/?BBSTs). /?BBSTs are designed to have reduced internal path length. As a result, they are expected to exhibit good search time characteristics. ..."
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Cited by 1 (0 self)
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We develop a new class of weight balanced binary search trees called/?balanced binary search trees (/?BBSTs). /?BBSTs are designed to have reduced internal path length. As a result, they are expected to exhibit good search time characteristics.
Proceedings of the 3rd DIKUIST Joint Workshop on Foundations of Software
 THE 3RD DIKUIST JOINT WORKSHOP ON FOUNDATIONS OF SOFTWARE
, 2007
"... These proceedings contain the contributions presented at the 3rd DIKUIST Joint Workshop on Foundations of Software held at Roskilde, Denmark, October 56, 2007. The workshop featured talks and discussions on domainspecific languages, logic and model checking, program complexity and optimization, r ..."
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These proceedings contain the contributions presented at the 3rd DIKUIST Joint Workshop on Foundations of Software held at Roskilde, Denmark, October 56, 2007. The workshop featured talks and discussions on domainspecific languages, logic and model checking, program complexity and optimization, reversible and bidirectional computing, and demonstrations of software prototypes.
Optimal Finger Search Trees in the Pointer Machine
"... We develop a new finger search tree with worstcase constant update time in the Pointer Machine (PM) model of computation. This was a major problem in the field of Data Structures and was tantalizingly open for over twenty years while many attempts by researchers were made to solve it. The result co ..."
Abstract
 Add to MetaCart
We develop a new finger search tree with worstcase constant update time in the Pointer Machine (PM) model of computation. This was a major problem in the field of Data Structures and was tantalizingly open for over twenty years while many attempts by researchers were made to solve it. The result comes as a consequence of the innovative mechanism that guides the rebalancing operations combined with incremental multiple splitting and fusion techniques over nodes.