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Handbook of Data Structures and Applications

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SKU:
9780367572006
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  • Product Details

    Author:
    Dinesh P. Mehta, Sartaj Sahni
    Format:
    Paperback
    Pages:
    1120
    Publisher:
    CRC Press (June 30, 2020)
    Language:
    English
    ISBN-13:
    9780367572006
    Weight:
    73.125oz
    Dimensions:
    8.25" x 11"
    File:
    TAYLORFRANCIS-TayFran_260409051915605-20260409.xml
    Folder:
    TAYLORFRANCIS
    List Price:
    $63.99
    Series:
    Chapman & Hall/CRC Computer and Information Science Series
    Case Pack:
    1
    As low as:
    $60.79
    Publisher Identifier:
    P-CRC
    Discount Code:
    H
    Country of Origin:
    United States
    Pub Discount:
    30
    Imprint:
    Chapman and Hall/CRC
  • Overview

    The Handbook of Data Structures and Applications was first published over a decade ago. This second edition aims to update the first by focusing on areas of research in data structures that have seen significant progress. While the discipline of data structures has not matured as rapidly as other areas of computer science, the book aims to update those areas that have seen advances.





    Retaining the seven-part structure of the first edition, the handbook begins with a review of introductory material, followed by a discussion of well-known classes of data structures, Priority Queues, Dictionary Structures, and Multidimensional structures. The editors next analyze miscellaneous data structures, which are well-known structures that elude easy classification. The book then addresses mechanisms and tools that were developed to facilitate the use of data structures in real programs. It concludes with an examination of the applications of data structures.





    Four new chapters have been added on Bloom Filters, Binary Decision Diagrams, Data Structures for Cheminformatics, and Data Structures for Big Data Stores, and updates have been made to other chapters that appeared in the first edition.

    The Handbook is invaluable for suggesting new ideas for research in data structures, and for revealing application contexts in which they can be deployed. Practitioners devising algorithms will gain insight into organizing data, allowing them to solve algorithmic problems more efficiently.