Algorithms and Data Structure

Topics: Computer, Java, Byte Pages: 129 (41461 words) Published: August 21, 2011

Algorithms and Data Structures
© N. Wirth 1985 (Oberon version: August 2004) Contents Preface 1 Fundamental Data Structures 1.1 Introduction 1.2 The Concept of Data Type 1.3 Primitive Data Types 1.4 Standard Primitive Types 1.4.1 Integer types 1.4.2 The type REAL 1.4.3 The type BOOLEAN 1.4.4 The type CHAR 1.4.5 The type SET 1.5 The Array Structure 1.6 The Record Structure 1.7 Representation of Arrays, Records, and Sets 1.7.1 Representation of Arrays 1.7.2 Representation of Recors 1.7.3 Representation of Sets 1.8 The File (Sequence) 1.8.1 Elementary File Operators 1.8.2 Buffering Sequences 1.8.3 Buffering between Concurrent Processes 1.8.4 Textual Input and Output 1.9 Searching 1.9.1 Linear Search 1.9.2 Binary Search 1.9.3 Table Search 1.9.4 Straight String Search 1.9.5 The Knuth-Morris-Pratt String Search 1.9.6 The Boyer-Moore String Search Exercises 2 Sorting 2.1 Introduction 2.2 Sorting Arrays 2.2.1 Sorting by Straight Insertion 2.2.2 Sorting by Straight Selection 2.2.3 Sorting by Straight Exchange 2.3 Advanced Sorting Methods 2.3.1 Insertion Sort by Diminishing Increment 2.3.2 Tree Sort 2.3.3 Partition Sort 2.3.4 Finding the Median 2.3.5 A Comparison of Array Sorting Methods 2.4 Sorting Sequences 2.4.1 Straight Merging 2.4.2 Natural Merging 2.4.3 Balanced Multiway Merging 2.4.4 Polyphase Sort 2.4.5 Distribution of Initial Runs Exercises

3 Recursive Algorithms 3.1 Introduction 3.2 When Not to Use Recursion 3.3 Two Examples of Recursive Programs 3.4 Backtracking Algorithms 3.5 The Eight Queens Problem 3.6 The Stable Marriage Problem 3.7 The Optimal Selection Problem Exercises 4 Dynamic Information Structures 4.1 Recursive Data Types 4.2 Pointers 4.3 Linear Lists 4.3.1 Basic Operations 4.3.2 Ordered Lists and Reorganizing Lists 4.3.3 An Application: Topological Sorting 4.4 Tree Structures 4.4.1 Basic Concepts and Definitions 4.4.2 Basic Operations on Binary Trees 4.4.3 Tree Search and Insertion 4.4.4 Tree Deletion 4.4.5 Analysis of Tree Search and Insertion 4.5 Balanced Trees 4.5.1 Balanced Tree Insertion 4.5.2 Balanced Tree Deletion 4.6 Optimal Search Trees 4.7 B-Trees 4.7.1 Multiway B-Trees 4.7.2 Binary B-Trees 4.8 Priority Search Trees Exercises 5 Key Transformations (Hashing) 5.1 Introduction 5.2 Choice of a Hash Function 5.3 Collision handling 5.4 Analysis of Key Transformation Exercises Appendices A B Index The ASCII Character Set The Syntax of Oberon


In recent years the subject of computer programming has been recognized as a discipline whose mastery is fundamental and crucial to the success of many engineering projects and which is amenable to scientific treatement and presentation. It has advanced from a craft to an academic discipline. The initial outstanding contributions toward this development were made by E.W. Dijkstra and C.A.R. Hoare. Dijkstra's Notes on Structured Programming [1] opened a new view of programming as a scientific subject and intellectual challenge, and it coined the title for a "revolution" in programming. Hoare's Axiomatic Basis of Computer Programming [2] showed in a lucid manner that programs are amenable to an exacting analysis based on mathematical reasoning. Both these papers argue convincingly that many programmming errors can be prevented by making programmers aware of the methods and techniques which they hitherto applied intuitively and often unconsciously. These papers focused their attention on the aspects of composition and analysis of programs, or more explicitly, on the structure of algorithms represented by program texts. Yet, it is abundantly clear that a systematic and scientific approach to program construction primarily has a bearing in the case of large, complex programs which involve complicated sets of data. Hence, a methodology of programming is also bound to include all aspects of data structuring. Programs, after all, are concrete formulations of abstract algorithms based on particular representations and structures of data. An...
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