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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 287 (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 efftcient 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.
Range mode and range median queries on lists and trees
 In Proceedings of the 14th Annual International Symposium on Algorithms and Computation (ISAAC
, 2003
"... ABSTRACT. We consider algorithms for preprocessing labelled lists and trees so that, for any two nodes u and v we can answer queries of the form: What is the mode or median label in the sequence of labels on the path from u to v. 1 ..."
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Cited by 28 (3 self)
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ABSTRACT. We consider algorithms for preprocessing labelled lists and trees so that, for any two nodes u and v we can answer queries of the form: What is the mode or median label in the sequence of labels on the path from u to v. 1
Fully persistent lists WITH CATENATION
, 1994
"... This paper considers the problem of represmrtirrg stacks with catenation so that any stack, old or new, is available for access or update operations. Th]s problem arises in the implementation of listbased and functional programming languages. A solution is proposed requiring constant time and spa ..."
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Cited by 23 (5 self)
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This paper considers the problem of represmrtirrg stacks with catenation so that any stack, old or new, is available for access or update operations. Th]s problem arises in the implementation of listbased and functional programming languages. A solution is proposed requiring constant time and space for each stack operation except catenation, which requmes O(log log k) time and space. Here k is the number of stack operations done before the
Confluently Persistent Tries for Efficient Version Control
"... Abstract. We consider a datastructural problem motivated by version control of a hierarchical directory structure in a system like Subversion. The model is that directories and files can be moved and copied between two arbitrary versions in addition to being added or removed in an arbitrary version ..."
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Cited by 2 (2 self)
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Abstract. We consider a datastructural problem motivated by version control of a hierarchical directory structure in a system like Subversion. The model is that directories and files can be moved and copied between two arbitrary versions in addition to being added or removed in an arbitrary version. Equivalently, we wish to maintain a confluently persistent trie (where internal nodes represent directories, leaves represent files, and edge labels represent path names), subject to copying a subtree between two arbitrary versions, adding a new child to an existing node, and deleting an existing subtree in an arbitrary version. Our first data structure represents an nnode degree ∆ trie with O(1) “fingers ” in each version while supporting finger movement (navigation) and modifications near the fingers (including subtree copy) in O(lg ∆) time and space per operation. This data structure is essentially a localitysensitive version of the standard practice—path copying— costing O(d lg ∆) time and space for modification of a node at depth d, which is expensive when performing many deep but nearby updates. Our second data structure supporting finger movement in O(lg ∆) time and no space, while modifications take O(lg n) time and space. This data structure is substantially faster for deep updates, i.e., unbalanced tries. Both of these data structures are functional, which is a stronger property than confluent persistence. Without this stronger property, we show how both data structures can be sped up to support movement in O(lg lg ∆), which is essentially optimal. Along the way, we present a general technique for global rebuilding of fully persistent data structures, which is nontrivial because amortization and persistence do not usually mix. In particular, this technique improves the best previous result for fully persistent arrays and obtains the first efficient fully persistent hash table. 1
Nordic Journal of Computing RANGE MODE AND RANGE MEDIAN QUERIES ON LISTS AND TREES ∗
"... Abstract. We consider algorithms for preprocessing labelled lists and trees so that, for any two nodes u and v we can answer queries of the form: What is the mode or median label in the sequence of labels on the path from u to v. 1. ..."
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Abstract. We consider algorithms for preprocessing labelled lists and trees so that, for any two nodes u and v we can answer queries of the form: What is the mode or median label in the sequence of labels on the path from u to v. 1.
Persistent Linked Structures at Constant WorstCase Cost
"... We present a method for making linked structures with nodes of indegree not exceeding 1 partially persistent at a worstcase time cost of O(1) per access step and a worstcase time and space cost of O(1) per update step. The last two improve the best previous result, which gave O(1) amortized bo ..."
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We present a method for making linked structures with nodes of indegree not exceeding 1 partially persistent at a worstcase time cost of O(1) per access step and a worstcase time and space cost of O(1) per update step. The last two improve the best previous result, which gave O(1) amortized bounds on time and space. Our results extend to full persistence. 1 Introduction Making a change to an ordinary data structure destroys the old version, leaving only the new one. Such a structure is said to be ephemeral. With a persistent data structure, on the other hand, old versions are not destroyed, making it possible to access or modify old versions as well as the newest one. A structure is said to be partially persistent if every version can be accessed but only the newest version can be modified and fully persistent if every version can be both accessed and modified. Researchers have devised partially or fully persistent forms for a number of data structures, including stacks [10],...