Curriculum Guideline

Data Structures & Algorithms

Effective Date:
Course Code
CSIS 3475
Data Structures & Algorithms
Computing Studies & Information Systems
Commerce & Business Administration
Start Date
End Term
Semester Length
60 hours
Max Class Size
Contact Hours
Number of Contact Hours: (per week for each descriptor) Lecture: 2 Hours per week Seminar/Lab: 2 Hours per week Total: 4 Hours per week
Method Of Instruction
Methods Of Instruction

Lecture, seminars and hands-on exercises in the lab (Group work may be involved)



Course Description
The purpose of this course is to provide the students with solid foundations in the basic concepts of programming: data structures, data abstraction and algorithms. The main objective of the course is to teach the students how to select, design and implement data structures, abstract data types and algorithms that are appropriate for problems that they might encounter. This course offers the students a mixture of theoretical knowledge and practical experience. It also develops skills of the modular approach to produce maintainable, documented and tested Java applications. Java is the programming language used for implementation.
Course Content
  • Review of Java including Classes, Interfaces, Inheritance, Exception handling and Text I/O

  • Introduction to Data Structures and Algorithm using Java

  • Algorithm Analysis

  • Recursion and efficiency

  • Search and Sorting Algorithms

  • Generics, Abstract Data Type and Java Collection Framework

  • List and Linked List

  • Stacks and Queues

  • Trees, Binary Tree, Binary Search Tree and AVL trees

  • Priority Queues and Heap

  • Hashing and Dictionary

  • Graph Algorithms

  • Algorithm Design Techniques

Learning Outcomes

The student will be able to:

  • Discuss the fundamentals of algorithmic complexities;
  • Carry out an elementary analysis of algorithms;
  • Determine the space and time complexity of an algorithm;
  • Identify and select the appropriate abstract data types such as queues, stacks for a small but realistic problem;
  • Demonstrate more in-depth applications of other data types such as trees and graphs;
  • Design and implement different Java programs using appropriate data structures;
  • Apply problem solving approaches such as “divide and conquer” in designing algorithms;
  • Explain and compare some of the fundamental searching and sorting techniques and algorithms;
  • Develop the skills of the modular approach to produce maintainable, documented, and tested software of a realistic size using Java.
Means of Assessment




0% – 15%

Project/Assignments (Group work may be involved)

15% – 25%

Midterm Exam

30% – 35%    

Final Exam

30% – 40%








**In order to pass the course, students must, in addition to receiving an overall course grade of 50%, also achieve a grade of at least 50% on the combined weighted examination components (including quizzes, tests, and exams).


Textbook Materials

Prichard and Carrano, Data Abstraction and Problem Solving with Java: Walls and Mirrors, Latest edition,

Or any alternative textbook approved by the Department.


Min C in (CSIS 1275 or CSIS 2175)





Which Prerequisite