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Data structures with dynamical random transitions

Random Structures & Algorithms, 2005
AbstractWe present a (non‐standard) probabilistic analysis of dynamic data structures whose sizes are considered dynamic random walks. The basic operations (insertion, deletion, positive and negative queries, batched insertion, lazy deletion, etc.) are time‐dependent random variables. This model is a (small) step toward the analysis of these structures
Clément Dombry   +3 more
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Succinct Dynamic Data Structures

2001
We develop succinct data structures to represent (i) a sequence of values to support partial sum and select queries and update (changing values) and (ii) a dynamic array consisting of a sequence of elements which supports insertion, deletion and access of an element at any given index.
Rajeev Raman   +2 more
openaire   +1 more source

Dynamic data structure mapping

Software: Practice and Experience, 1974
AbstractThis paper describes a high‐level language construct representing two facilities: dynamic absolute addressing and dynamic overlaying of variables. Its implementation in the programming language PASCAL is described in some detail. It is shown to provide simple and effective ways of increasing the effeciency of in‐core data access and transfer ...
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Dynamic Data Structures

1978
The types of variable in Pascal programs have been classified (in chapter 7) as unstructured and structured. The structured types have been further subdivided into elementary structured types and advanced structured types. The variables themselves may also be divided into two groups, depending on the manner of their creation.
I. R. Wilson, A. M. Addyman
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DDE

Proceedings of the first ACM asia-pacific workshop on Workshop on systems, 2010
Dynamic Datastructure Excavation (DDE) is a new approach to extract datastructures from C binaries without any need for debugging symbols. Unlike most existing tools, DDE uses dynamic analysis (on a QEMU-based emulator) and detects data structures by tracking how a program uses memory. Its results are much more accurate than those of previous methods.
Asia Slowinska   +2 more
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Heuristics That Dynamically Organize Data Structures

SIAM Journal on Computing, 1979
We first consider heuristics that dynamically alter linked lists, causing more frequently accessed keys to move nearer the “top” of the list. We show that the move to front rule reduces the access time much more quickly than the transposition rule, then give a “hybrid” of these two rules which decreases the access time quickly and has low asymptotic ...
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Dynamic Data Structures

1995
The primary aims of the chapter are to introduce the facilities offered by Fortran 95 for the construction and use of dynamic data types. These additional features enable us to solve a much wider range of problems using simple and straightforward algorithms.
Ian David Chivers, Jane Sleightholme
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Dynamic data structures and pointers

1982
Array, record and set structures share the common property that they are static. This implies that variables of such a structure maintain the same structure during the whole time of their existence. In many applications, this is an intolerable restriction; they require data which do not only change their value, but also their composition, size, and ...
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Dynamic Data Structures

1991
In previous chapters, we have seen lists implemented using consecutive entries in an array. There are three problems with this. Firstly, if items are deleted from the middle of the list, all following items must be moved up to fill the gap. Secondly, if the items are held in a specified order, the addition of a new item to the middle of the list also ...
Carl Bamford, Paul Curran
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Dynamic data structures

1996
These are all static data structures in the sense that their structure and storage requirements must be specified when the program is coded. For arrays, however, this size can vary within the limits prescribed by the language environment. Arrays also have a certain dynamic aspect due to the indexed access to its elements.
László Böszörményi, Carsten Weich
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