1. Analysis & Design of Algorithms (CSCE 321)
Prof. Amr Goneid
Department of Computer Science, AUC
Part 0. Course Outline
Prof. Amr Goneid, AUC

2. Analysis & Design of Algorithms
Prof. Amr Goneid, AUC

3. Course Resources Instructor: Prof. Amr Goneid
Office: Rm 2152 SSE
Text Books:
“Introduction to the Design and Analysis of Algorithms “,
by Anany V. Levitin
Pearson Higher Education, International Edition, 2/E, 2007
“Computer Algorithms/C++”, by Horowitz, Sahni and Rajasekaran, Computer Science Press, 1997
Other References:
“The Algorithm Design Manual”, by S. Skiena,
Springer-Verlag, 1998
“Algorithms in C++”, by R. Sedgewick, Addison-Wesley, 1992
Language: C++
Web Site:
Prof. Amr Goneid, AUC

4. Analysis & Design of Algorithms
Algorithm analysis
Analysis of resource usage of given algorithms (time , space)
Efficient algorithms
Algorithms that make an efficient usage of resources
Algorithm design
Methods for designing efficient algorithms
Prof. Amr Goneid, AUC

5. Analysis & Design of Algorithms
Why study this subject?
Efficient algorithms lead to efficient programs.
Efficient programs sell better.
Efficient programs make better use of hardware.
Programmers who write efficient programs are preferred.
Prof. Amr Goneid, AUC

6. Objectives
To gain experience in fundamental techniques used for algorithm analysis.
To gain experience in the main methodologies used for the design of efficient algorithms.
To study the most important computer algorithms of current practical use.
Prof. Amr Goneid, AUC

7. Contents
Material for Revision and Reference (Mainly from CSCE 210)
R1. Elementary Data Structures
R2. Binary Search Trees
R3. Priority Queues
R4. Disjoint Sets
R5. Graphs
Basics
Complexity Bounds
Types of Complexities
Time Complexity Calculations
Prof. Amr Goneid, AUC

8. Contents Analysis of Iterative and Recursive Algorithms
Brute Force Algorithms
Recursive Algorithms
Major Algorithm Design Methodologies
Transform & Conquer Algorithms
Divide & Conquer Algorithms
Greedy Algorithms
Intermezzo
Dynamic Programming
Backtracking Algorithms
Graph Algorithms
Branch & Bound
Other Strategies (Heuristics, String & Numerical Algorithms)
Prof. Amr Goneid, AUC

9. Grading
25 % Assignments
5 % Quizzes, class participation and attendance
20 % 1st Midterm Exam
20 % 2nd Midterm Exam
30 % Final Exam
All exams are closed book
Prof. Amr Goneid, AUC

10. Course Outcomes
After completing the CSCE 321, students should be able to:
Use big O, omega, and theta notation to give asymptotic upper, lower, and tight bounds on time and space complexity of algorithms.
Determine the time and space complexity of simple algorithms.
Recognize the difference between mathematical modeling and empirical analysis of algorithms, and the difference between deterministic and randomized algorithms.
Deduce recurrence relations that describe the time complexity of recursively defined algorithms and work out their particular and general solutions.
Prof. Amr Goneid, AUC

11. Course Outcomes
Practice the main algorithm design strategies of Brute Force, Exclude & Conquer, Transform & Conquer, Divide & Conquer, Greedy methods, Dynamic Programming, Backtracking and Branch & Bound and implement examples of each.
Identify examples of everyday human behavior that exemplifies the basic concepts of the main design strategies.
Implement the most common quadratic and O(N log N) sorting algorithms and perform their complexity analysis.
Solve problems using the fundamental graph algorithms including depth-first and breadth-first search, single-source and all-pairs shortest paths, transitive closure, topological sort, and the minimum spanning tree algorithms.
Evaluate, select and implement algorithms in programming context.
Prof. Amr Goneid, AUC