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NET Framework library, as well as those developed by the programmer. The approach is very practical, using timing tests rather than Big O nota- tion to analyze the efficiency of an approach. Coverage includes array and ArrayLists, linked lists, hash tables, dictionaries, trees, graphs, and sorting and searching algorithms, as well as more advanced algorithms such as prob- abilistic algorithms and dynamic programming. This is the perfect resource for C professionals and students alike.
Mike has written more than twenty-five trade journal articles on programming and has more than twenty years of experience programming for industry and education. Subject to statutory exception and to the provision of relevant collective licensing agreements, no reproduction of any part may take place without the llausv permission of Cambridge University Press. First published in print format ISBN hardback ISBN hardback ISBN paperback ISBN paperback Cambridge University Press has no responsibility for the persistence or accuracy of urls for external or third-party internet websites referred to in this publication, and does not guarantee that any content on such websites is, or will remain, accurate or appropriate.
C is becoming a very popular language and this book provides the C programmer with the opportunity to study fundamental data structures and algorithms. C exists in a very rich development environment called the. NET Frame- work. Included in the. The data structures and algorithms student can now see how to use a data structure before learning how to implement it. Previously, an instructor had to discuss the concept of, say, a stack, abstractly until the complete data structure was constructed.
Instructors can now show students how to use a stack to perform some computation, such as number base con- versions, demonstrating the utility of the data structure immediately.
With this background, the student can then go back and learn the fundamentals of the data structure or algorithm and even build their own implementation. This book is written primarily as a practical overview of the data struc- tures and algorithms all serious computer programmers need to know and understand.
Given this, there is no formal analysis of the data structures and algorithms covered in the book. Instead, the various data structures and algorithms are presented as problem-solving tools.
The concepts of linear and nonlinear collections are intro- duced. The Collection class is demonstrated. This chapter also introduces the concept of generic programming, which allows the programmer to write one class, or one method, and have it work for a multitude of data types.
Generic programming is an important new addition to C available in C 2. Generic namespace. When a data structure has a generic implementation found in this library, its use is discussed. The chapter ends with an introduction to methods of measuring the performance of the data structures and algorithms discussed in the book.
Chapter 2 provides a review of how arrays are constructed, along with demonstrating the features of the Array class. The Array class encapsulates many of the functions associated with arrays UBound, LBound, and so on into a single package.
ArrayLists are special types of arrays that provide dynamic resizing capabilities. Chapter 3 is an introduction to the basic sorting algorithms, such as the bubble sort and the insertion sort, and Chapter 4 examines the most funda- mental algorithms for searching memory, the sequential and binary searches.
Two classic data structures are examined in Chapter 5: the stack and the queue. The emphasis in this chapter is on the practical use of these data structures in solving everyday problems in data processing. Chapter 6 covers the BitArray class, which can be used to efficiently represent a large number of integer values, such as test scores.
Strings are not usually covered in a data structures book, but Chapter 7 covers strings, the String class, and the StringBuilder class. Chapter 8 examines the use of regular expressions for text processing and pattern matching. Regular expressions often provide more power and efficiency than can be had with more traditional string functions and methods. Chapter 9 introduces the reader to the use of dictionaries as data structures.
This chapter shows the reader how to create his or her own classes based on the DictionaryBase class, which is an abstract class. Chap- ter 10 covers hash tables and the HashTable class, which is a special type of dictionary that uses a hashing algorithm for storing data internally. Another classic data structure, the linked list, is covered in Chapter Chapter 12 introduces the reader to yet another classic data structure— the binary tree.
A specialized type of binary tree, the binary search tree, is the primary topic of the chapter. Other types of binary trees are covered in Chapter Chapter 13 shows the reader how to store data in sets, which can be useful in situations in which only unique data values can be stored in the data structure.
Chapter 14 covers more advanced sorting algorithms, including the popular and efficient QuickSort, which is the basis for most of the sorting procedures implemented in the.
NET Framework library. Chapter 15 looks at three data structures that prove useful for searching when a binary search tree is not called for: the AVL tree, the red-black tree, and the skip list. Chapter 16 discusses graphs and graph algorithms. Graphs are useful for representing many different types of data, especially networks. Finally, Chap- ter 17 introduces the reader to what algorithm design techniques really are: dynamic algorithms and greedy algorithms. First, thanks to a certain group of students who first sat through my lectures on developing data structures and algorithms.
I also have to thank my department dean, David Durr, and my department chair, Bernica Tackett, for supporting my writing endeavors. I also need to thank my family for putting up with me while I was preoccupied with research and writing.
Finally, many thanks to my editors at Cambridge, Lauren Cowles and Heather Bergman, for putting up with my many questions, topic changes, and habitual lateness. The data structures we use in this book are found in the. NET Framework class library System.
In this chapter, we develop the concept of a collection by first discussing the implementation of our own Collection class using the array as the basis of our implementation and then by covering the Collection classes in the. NET Framework. An important addition to C 2. Generics allow the C pro- grammer to write one version of a function, either independently or within a class, without having to overload the function many times to allow for differ- ent data types. Generic, that implements generics for several of the System.
Collections data structures. This chapter will introduce the reader to generic programming. Collections can be broken down into two types: linear and nonlinear. A linear collection is a list of elements where one element follows the previous element. Elements in a linear collection are normally ordered by position first, second, third, etc.
In the real world, a grocery list is a good example of a linear collection; in the computer world which is also real , an array is designed as a linear collection.
Nonlinear collections hold elements that do not have positional order within the collection. An organizational chart is an example of a nonlinear collection, as is a rack of billiard balls. In the computer world, trees, heaps, graphs, and sets are nonlinear collections. Collections, be they linear or nonlinear, have a defined set of properties that describe them and operations that can be performed on them.
An example of a collection property is the collections Count, which holds the number of items in the collection. Collection operations, called methods, include Add for adding a new element to a collection , Insert for adding a new element to a collection at a specified index , Remove for removing a specified element from a collection , Clear for removing all the elements from a collection , Contains for determining if a specified element is a member of a collec- tion , and IndexOf for determining the index of a specified element in a collection.
Linear collections can be either direct access collections or sequential access collections, whereas nonlinear collections can be either hierarchical or grouped. This section describes each of these collection types. Direct Access Collections The most common example of a direct access collection is the array.
We define an array as a collection of elements with the same data type that are directly accessed via an integer index, as illustrated in Figure 1. Arrays can be static so that the number of elements specified when the array is declared is fixed for the length of the program, or they can be dynamic, where the number of elements can be increased via the ReDim or ReDim Preserve statements.
In C , arrays are not only a built-in data type, they are also a class. Later in this chapter, when we examine the use of arrays in more detail, we will discuss how arrays are used as class objects. We can use an array to store a linear collection. Adding new elements to an array is easy since we simply place the new element in the first free position at the rear of the array.
Inserting an element into an array is not as easy or efficient , since we will have to move elements of the array down in order to make room for the inserted element. Deleting an element from the end of an array is also efficient, since we can simply remove the value from the last element.
Deleting an element in any other position is less efficient because, just as with inserting, we will probably have to adjust many array elements up one position to keep the elements in the array contiguous. We will discuss these issues later in the chapter. NET Framework provides a specialized array class, ArrayList, for making linear collection programming easier. We will examine this class in Chapter 3.
Another type of direct access collection is the string. A string is a collection of characters that can be accessed based on their index, in the same manner we access the elements of an array.
The concept of abstract data types and the advantages of data abstraction are introduced. Various commonly used abstract data types including vector, list, stack, queue, tree, and set and their implementations using different data structures array, pointer based structures, linked list, tree, B-tree, etc. Sample applications such as searching, sorting, etc. Analysis of the performance of searching and sorting algorithms. Application of data structure pinciples. Note: This class will be taught in English. Homework assignments and examinations will also be in English.
Data Structures and Algorithm Analysis in C++, 4th Edition. Mark A. Weiss. © |Pearson | Available. Share this page. Data Structures and Algorithm Analysis.
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It is aimed at helping the students to understand the reasons for choosing data structures. The main objective of the course is to teach the students how to select and design data structures and algorithms that are appropriate for problems they might encounter. Reference books available in the library 1. Learning Resources The instructor will post regularly the learning resources available on the web related to the concerned topics. Understand various data structures that serve as building blocks for creating efficient programs.
Classes I Classes are an expanded concept of data structures: like data structures, they can contain data members, but they can also contain functions as members. An object is an instantiation of a class. In terms of variables, a class would be the type, and an object would be the variable. Classes are defined using either keyword class or keyword struct, with the following syntax. The book focuses on abstract data types as viewed from three different perspectives: their specification, their application, and their implementation. The authors stress computer science theory and software engineering principles.
Chapter 0 Introduction 0. Interpreted Code 0. Chapter 1 Basic Types and Control Structures 1. Chapter 3 Pointers and Reference Variables 3. Chapter 4 Object-Based Programming: Classes 4. Mutators 4. Class Operators 5.
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