1. CSCE 210 Data Structures and Algorithms
Prof. Amr Goneid
AUC
Part 0. Course Outline
Prof. Amr Goneid, AUC

2. Course Resources Instructor: Prof. Amr Goneid
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:
Prof. Amr Goneid, AUC

3. Course 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 Contents Revision and Expansion on CSCI 110 Material
R1. 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 Contents Data Modeling and ADT’s
Simple Containers: Stacks and Queues
Introduction to the Analysis of Algorithms
Trees
Dictionaries(2): Binary Search Trees
Dictionaries(3): Hash Tables
Priority Queues
Sorting
Sorting (1): Elementary Algorithms
Sorting (2): (n log n) Algorithms
The Set Data Structure: Disjoint Sets
Graphs
Prof. Amr Goneid, AUC

6. Course Contents R1 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
Prof. Amr Goneid, AUC

7. Course Contents R2 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
Prof. Amr Goneid, AUC

8. Course Contents(continued) R3
Dictionaries(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
Prof. Amr Goneid, AUC

9. Course Contents Part 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) Part 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
Prof. Amr Goneid, AUC

11. Course Contents(continued) Part 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) Part 4
Trees
Binary Trees
Tree Traversal
Prof. Amr Goneid, AUC

13. Course Contents(continued) Part 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) Part 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) Part 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) Part 8a
Sorting(1): Elementary Algorithms
General
Selection Sort
Bubble Sort
Insertion Sort
Prof. Amr Goneid, AUC

17. Course Contents(continued) Part 8b
Sorting(2): (n log n) Algorithms
General
Heap Sort
Merge Sort
Quick Sort
Prof. Amr Goneid, AUC

18. Course Contents(continued) Part 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) Part 10
Graphs
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. Summary Parts R1,R2,R3 are revisions of CSCE110 material
Part No.
Subject
Book 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
Trees 12 5
Dictionaries(2): Binary Search Trees
Dictionaries(3): Hash Tables 7
Priority Queues 13 8a
Sorting(1): Elementary Algorithms 8b
Sorting(2): (n log n) Algorithms 9
The Set Data Structure: Disjoint Sets 16
Graphs
Parts R1,R2,R3 are revisions of CSCE110 material
Prof. Amr Goneid, AUC

21. Lab Assignments
Hands-on experience will be gained through programming projects
that cover the course material. Design documents are required for
all 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 a
given subproblem.
Prof. Amr Goneid, AUC

22. Lab 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 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 Outcomes
After completing the CSCE 210, students should be able to:
Demonstrate knowledge and understanding of Data Models, Data Abstraction and ADTs and their role in problem solving and S/W development.
Choose the appropriate data structure for modeling a given problem.
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 Outcomes
Compare alternative implementations of data structures with respect to performance.
Demonstrate experience in the design of algorithms for solving problem that use the above data structures.
Demonstrate knowledge of common applications for each data structure in the topic list.
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).
Prof. Amr Goneid, AUC