Prof. Amr Goneid, AUC 1

CSCE 210CSCE 210Data Structures and AlgorithmsData Structures and Algorithms

Prof. Amr Goneid

AUC

Part 0. Course Outline

Prof. Amr Goneid, AUC 2

Course ResourcesCourse Resources

Instructor: Prof. Amr Goneid E-mail: goneid@aucegypt.edu Office: Rm 2152 SSE Textbook: "ADTs, Data Structures and Problem

Solving with C++" by Larry Nyhoff, 2nd Edition, Pearson Prentice Hall, 2005

Reference: "Problem Solving, Abstraction, and Design using C++" by Friedman and Koffman, Fourth Edition, Addison Wesley, 2005

Lab: To be assigned soon Web Site: www.cse.aucegypt.edu/~csci210/

Prof. Amr Goneid, AUC 3

Course GoalsCourse Goals

To introduce concepts of Data Models, Data Abstraction and ADTs in problem solving and S/W development

To deepen the experience in Object Oriented Programming as an efficient software development methodology.

To gain experience in the design of algorithms for problem solving and to introduce the concepts of algorithm analysis

To gain experience in the design and implementation of various ADTs and their applications to practical problems

Prof. Amr Goneid, AUC 4

Course ContentsCourse Contents

Revision and Expansion on CSCI 110 MaterialR1. ADTs as Classes (Revision of some CSCI 110 material)R2. Elementary Data Structures (Revision of some CSCI 110 material)R3. Dictionaries(1): Key Tables and Lists (Revision of some CSCI 110

material)

Prof. Amr Goneid, AUC 5

Course ContentsCourse Contents

1. Data Modeling and ADT’s

2. Simple Containers: Stacks and Queues

2. Introduction to the Analysis of Algorithms

3. Trees

4. Dictionaries(2): Binary Search Trees

5. Dictionaries(3): Hash Tables

6. Priority Queues

7. Sorting

Sorting (1): Elementary Algorithms

Sorting (2): (n log n) Algorithms

9. The Set Data Structure: Disjoint Sets

10. Graphs

Prof. Amr Goneid, AUC 6

Course ContentsCourse ContentsR1R1 ADTs as Classes (Revision of some CSCE 110 material)

Class Definition: Private & Public Members Constructors & Destructor Data and Function Members Accessors & Mutators Polymorphism and Overloading Example: Rational Numbers Class Example: Simple String Class

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Course ContentsCourse ContentsR2R2 Elementary Data Structures

(Revision of some CSCE 110 material) Static and Dynamic Data Structures Static Arrays Pointers Run-Time Arrays The Linked List Structure Some Linked List Operations Variations on Linked Lists

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Course Contents(continued)Course Contents(continued)R3R3Dictionaries(1):Key Tables and Lists The Key Table

ADT Key Table The Key Table Class Definition Key Table Class implementation Example Application

The Linked List ADT Linked List The Linked List Class Definition Linked List Class implementation Example Application

Prof. Amr Goneid, AUC 9

Course ContentsCourse ContentsPart 1Part 1 Data Modeling and ADTs

Data Modeling Abstract Data types (ADTs) A Classification of Abstract Structures Another Classification Special Data Structures OOP and Classes Examples on Modeling

Prof. Amr Goneid, AUC 10

Course Contents(continued)Course Contents(continued)Part 2Part 2 Simple Containers: Stacks and Queues

Introduction to the Stack data structure Designing a Stack class using dynamic arrays Linked Stacks Some Applications of Stacks Introduction to the Queue data structure Designing a Queue class using dynamic arrays Linked Queues An Application of Queues

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Course Contents(continued)Course Contents(continued)Part 3Part 3 Introduction to the Analysis of Algorithms

Algorithms Analysis of Algorithms Time Complexity Bounds and the Big-O Types of Complexities Rules for Big-O Examples of Algorithm Analysis

Prof. Amr Goneid, AUC 12

Course Contents(continued)Course Contents(continued)Part 4Part 4 Trees

Binary Trees Tree Traversal

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Course Contents(continued)Course Contents(continued)Part 5Part 5 Dictionaries(2): Binary Search Trees

The Dictionary Data Structure The Binary Search Tree (BST) Search, Insertion and Traversal of BST Removal of nodes from a BST Binary Search Tree ADT Template Class Specification Other Search Trees (AVL Trees)

Prof. Amr Goneid, AUC 14

Course Contents(continued)Course Contents(continued)Part 6Part 6 Dictionaries(3): Hash Tables

Hash Tables as Dictionaries Hashing Process Collision Handling: Open Addressing Collision Handling: Chaining Properties of Hash Functions Template Class Hash Table Performance

Prof. Amr Goneid, AUC 15

Course Contents(continued)Course Contents(continued)Part 7Part 7 Priority Queues

Definition of Priority Queue The Binary Heap Insertion and Removal A Priority Queue Class

Prof. Amr Goneid, AUC 16

Course Contents(continued)Course Contents(continued)Part 8aPart 8a Sorting(1): Elementary Algorithms

General Selection Sort Bubble Sort Insertion Sort

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Course Contents(continued)Course Contents(continued)Part 8bPart 8b Sorting(2): (n log n) Algorithms

General Heap Sort Merge Sort Quick Sort

Prof. Amr Goneid, AUC 18

Course Contents(continued)Course Contents(continued)Part 9Part 9 The Set Data Structure: Disjoint Sets

What are Disjoint Sets? Tree Representation Basic Operations Parent Array Representation Simple Find and Simple Union Disjoint Sets Class Some Applications

Prof. Amr Goneid, AUC 19

Course Contents(continued)Course Contents(continued)Part 10Part 10Graphs Basic Definitions Paths and Cycles Connectivity Other Properties Representation Examples of Graph Algorithms:

Graph Traversal Shortest Paths Minimum Cost Spanning Trees

Prof. Amr Goneid, AUC 20

SummarySummary

Part No. SubjectBook

Chapter

R1 ADTs as Classes 4

R2 Elementary Data Structures 2 , 3, 6

R3 Dictionaries(1): key Tables and Lists 6

1 Data Modeling and ADTs 2 , 3

2 Simple Containers: Stacks and Queues 7 , 8

3 Introduction to the Analysis of Algorithms 10

4 Trees 12

5 Dictionaries(2): Binary Search Trees 12

6 Dictionaries(3): Hash Tables 12

7 Priority Queues 13

8a Sorting(1): Elementary Algorithms 13

8b Sorting(2): (n log n) Algorithms 13

9 The Set Data Structure: Disjoint Sets 16

10 Graphs 16

Parts R1,R2,R3 are revisions of CSCE110 material

Prof. Amr Goneid, AUC 21

Lab AssignmentsLab Assignments

Hands-on experience will be gained through programming projectsthat cover the course material. Design documents are required forall the problems given. Design Document:The basic items in the design document will include: Problem Definition Requirement Specifications Solution Strategy S/W Design for the whole problem:

Structured (Top-Down) Design in the form of modules(C++ functions) in which each module is associated with agiven subproblem.

Prof. Amr Goneid, AUC 22

Lab AssignmentsLab Assignments S/W Design for Each Module:

Functional Specifications: the purpose of the module and what it is supposed to do (What to do)

Data Specifications: the data resources needed by the module to achieve it functionality (with what)

Precondition: the state of processing or data before the module is executed (state before)

Postcondition: the state of processing or data after the module is executed (state after)

Algorithm Specification: the algorithm or methodology used by the module (How to do it)

Prof. Amr Goneid, AUC 23

Coursework GradingCoursework Grading

30% Programming Assignments. 5 % Quizzes, class participation and

attendance 20% Midterm Exam (1) 20% Midterm Exam (2) 25% Final Exam

Prof. Amr Goneid, AUC 24

Course OutcomesCourse Outcomes

After completing the CSCE 210, students should be able to:

1. Demonstrate knowledge and understanding of Data Models, Data Abstraction and ADTs and their role in problem solving and S/W development.

2. Choose the appropriate data structure for modeling a given problem.

3. Design and implement various ADTs in a high level language (C++) using Object Oriented Concepts. Topics include Linked lists, Simple Containers (Stacks, Queues), Dictionaries (Key Tables and Lists, Binary Search Trees, Hash tables), Priority Queues and Heaps, Disjoint Sets and Graphs.

Prof. Amr Goneid, AUC 25

Course OutcomesCourse Outcomes

4. Compare alternative implementations of data structures with respect to performance.

5. Demonstrate experience in the design of algorithms for solving problem that use the above data structures.

6. Demonstrate knowledge of common applications for each data structure in the topic list.

7. Practice basic algorithm analysis using complexity bounds (Big-Oh, Big-Theta and Big-Omega). Applications include Quadratic Sorting methods and Divide & Conquer recursive sorting (n log n) examples (Merge Sort and Quick Sort).