# Digital Access to Comparison-Based Tree Data Structures and Algorithms

@article{Roura2001DigitalAT, title={Digital Access to Comparison-Based Tree Data Structures and Algorithms}, author={Salvador Roura}, journal={J. Algorithms}, year={2001}, volume={40}, pages={1-23} }

This paper presents a simple method of building tree data structures, which only requires visiting O(log N) nodes and comparing O(D) digits per search or update, where N is the number of keys and D is the length of the keys. These bounds hold independently of the order of the updates and of the digits of the keys. The additional space required by the method is asymptotically dismissable when compared to the space used by the keys and pointers. The proposed method applies either to fixed-length…

## 11 Citations

On the number of string lookups in BSTs (and related algorithms) with digital access

- Computer Science
- 2009

The number of string lookups in so-augmented BSTs, quicksort and quickselect is haracterized analytically and a variant proposed in this paper is proposed to reduce further the number ofstring lookups.

Managing Unbounded-Length Keys in Comparison-Driven Data Structures with Applications to Online Indexing

- Computer ScienceSIAM J. Comput.
- 2014

This paper presents a general technique for optimally transforming any dynamic data structure that operates on atomic and indivisible keys by constant-time comparisons, into a data structure that…

The number of bit comparisons used by Quicksort: an average-case analysis

- Computer ScienceSODA '04
- 2004

The prospect of a fair comparison between algorithms of the two types is introduced by providing an averagecase analysis of the number of bit comparisons required by Quicksort, and a new algorithm, "BitsQuick", that reduces this factor to constant order by eliminating needless bit comparisons.

A General Technique for Managing Strings in Comparison-Driven Data Structures

- Computer ScienceICALP
- 2004

This paper presents a general technique for optimally transforming any dynamic data structure \(\mathcal{D}\) that operates on atomic and indivisible keys by constant-time comparisons, into a data…

Combining digital access and parallel partition for quicksort and quickselect

- Computer Science2009 ICSE Workshop on Multicore Software Engineering
- 2009

This paper combines digital access to strings with parallel partition to enhance parallel quicksort and quickselect implementations and presents broadly the approach, not only algorithmically but from the design and implementation point of view.

Parallelization of Modified Merge Sort Algorithm

- Computer ScienceSymmetry
- 2017

The claim is that the parallelization of the sorting method is faster and beneficial for multi-core systems and is compared to other sorting methods like quick sort, heap sort, and merge sort to show potential efficiency.

Multikey Quickselect

- Computer ScienceAlgorithmica
- 2013

A binary variant of the multikey quickselect algorithm is derived, which is more efficient when the range of values for the alphabet is known, and can be applied to multikesy quicksort.

Parallel Fast Sort Algorithm for Secure Multiparty Computation

- Computer ScienceJ. Univers. Comput. Sci.
- 2018

Results of the experimental tests confirm the effectiveness of the proposed flexible division of tasks between logical processors and show that this proposition is a valuable method that can find many practical applications in high performance computing.

Fully Flexible Parallel Merge Sort for Multicore Architectures

- Computer ScienceComplex.
- 2018

A fully flexible sorting method designed for parallel processing based on modified merge sort that can be implemented for a number of processors and shows that with each newly added processor sorting becomes faster and more efficient.

Benchmark Tests on Improved Merge for Big Data Processing

- Computer Science2015 Asia-Pacific Conference on Computer Aided System Engineering
- 2015

There is need to improve sorting methods applied for big data computation as the computer architectures are more efficient with each release and the software is more complex with each version.

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