Advanced Data Structures

3 Key excerpts on "Advanced Data Structures"

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  eBook - ePub

  Learn Data Structures and Algorithms with Golang

  Level up your Go programming skills to develop faster and more efficient code

  • Bhagvan Kommadi(Author)
  • 2019(Publication Date)
  • Packt Publishing

    (Publisher)

  Data Structures and Algorithms

  A data structure is the organization of data to reduce the storage space used and to reduce the difficulty while performing different tasks. Data structures are used to handle and work with large amounts of data in various fields, such as database management and internet indexing services.

  In this chapter, we will focus on the definition of abstract datatypes, classifying data structures into linear, nonlinear, homogeneous, heterogeneous, and dynamic types. Abstract datatypes, such as Container, List, Set, Map, Graph, Stack, and Queue, are presented in this chapter. We will also cover the performance analysis of data structures, choosing the right data structures, and structural design patterns.

  T he r eader can start writing basic algorithms using the right data structures in Go.

  Given a problem, choosing the data structure and different algorithms will be the first step. After this, doing performance analysis is the next step. Time and space analysis for different algorithms helps compare them and helps you choose the optimal one

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  eBook - ePub

  Engineering Informatics

  Fundamentals of Computer-Aided Engineering, Second Edition

  • Benny Raphael, Ian F. C. Smith(Authors)
  • 2013(Publication Date)
  • Wiley

    (Publisher)

  In some engineering fields, work has concentrated on standardizing data structures. Data structure standardization helps contribute to better communication between engineers during complex engineering tasks. Such standardization also increases compatibility between software products. Increases in productivity that are linked to such efforts could result in better, faster and cheaper engineering activities.

  This chapter presents and describes fundamental types of data structures. Knowledge of these types is important for understanding the material presented in subsequent chapters on object-oriented programming (Chapter 4), database concepts (Chapter 5) and constraint-based reasoning (Chapter 7), as well as optimization and search (Chapter 8).

  3.2 Definitions

  The term data structure refers to the organization of data within software applications. Properly organized data is easy to understand and maintain. Consider the list of variables shown in Figure 3.1a . Compare it with the structured form of the same data shown in Figure 3.1b . In structured form, logically related data are grouped together. Such structure helps understanding, thereby increasing the reliability of appropriate data use and modifications.

  Figure 3.1

  Data structures group related information together: (a) a flat list of unorganized data; (b) structured data

  Data structures often involve hierarchies, called decomposition hierarchies, where data are organized into attributes of systems, components and subcomponents. In this chapter, the term object will be used informally to refer to a collection of data that is organized into attributes. The term attribute is used in a generic sense to denote characteristic aspects of objects (properties) as well as components of objects. Thus an attribute might itself be an object consisting of subattributes. Figure 3.2 illustrates the decomposition of the data structure in Figure 3.1b

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  eBook - ePub

  40 Algorithms Every Programmer Should Know

  Hone your problem-solving skills by learning different algorithms and their implementation in Python

  • Imran Ahmad(Author)
  • 2020(Publication Date)
  • Packt Publishing

    (Publisher)

  can be ordered left to right in an ascending order in which the nodes at the same level will increase in value while traversing from left to right.

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  Practical examples

  An abstract data type tree is one of the main data structures that are used in developing decision trees as will be discussed in Chapter 7 ,

  Traditional Supervised Learning Algorithms

  . Due to its hierarchical structure, it is also popular in algorithms related to network analysis as will be discussed in detail in Chapter 6 , Unsupervised Machine Learning Algorithms . Trees are also used in various search and sort algorithms where divide and conquer strategies need to be implemente d.

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  Summary

  In this chapter, we discussed data structures that can be used to implement various types of algorithms. After going through this chapter, I expect that you should be able to select the right data structure to be used to store and process data by an algorithm. You should also be able to understand the implications of our choice on the performance of the algorithm.

  The next

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