COMP6230

Introduction to Algorithmics

Faculty of Engineering and Built Environment School of Electrical Engineering and Computer Science

10 Units 6000 Level Course

Available in 2014

Callaghan Campus	Semester 2

Previously offered in 2013, 2012, 2011, 2010, 2009, 2008, 2007, 2006, 2005, 2004

This course introduces students to the notion of efficiency and computational complexity. The basic data structures encountered in first year, such as lists, trees and graphs, are reviewed in light of their efficiency and common usage scenario. Asymptotic measures of complexity are covered, and recurrence relations are introduced as an analytical tool. Problem-solving techniques such as the greedy strategy, divide-and-conquer, dynamic programming, and graph searching are covered. These techniques are illustrated upon optimization problems chosen for their practical relevance.

Objectives

(1) To introduce students to efficient algorithm design techniques.

(2) To introduce students to basic techniques regarding analysis of performance of algorithms.

(3) To make students familiar with the most important basic algorithms used in various computer science application and theoretical areas.

Content

(1) Preliminaries (review of basic mathematical notions, data structures, induction, basic combinatorics).

(2) Elementary algorithmics (worst-case vs. average case, basic examples, elementary operations).

(3) Asymptotic Notation (big O, Omega and Theta).

(4) Analysis of Algorithms (loops, recurrence relations).

(5) Data structures (graphs, trees, heaps, disjoint sets).

(6) Searching and Sorting.

(7) Greedy algorithms.

(8) Divide-and-Conquer.

(9) Dynamic programming.

(10) Text-search Algorithm.

(11) Introduction to the topics of computational complexity, heuristics, metaheuristics and approximation algorithms.

Replacing Course(s)

n/a

Transition

n/a

Industrial Experience

Assumed Knowledge

SENG6120
Knowledge of discrete mathematics.

Modes of Delivery

Internal Mode

Teaching Methods

Problem Based Learning
Lecture
Tutorial

Assessment Items

Examination: Class	Progressive tests and Midterm exam as per course outline.
Essays / Written Assignments	Assignment. As per course outline.
Examination: Formal	As per the University's exam timetable.
Other: (please specify)	Assessment tailored towards MIT students needs.
Projects	As per course outline.

Contact Hours

Lecture: for 3 hour(s) per Week for Full Term
Tutorial: for 2 hour(s) per Week for Full Term

Compulsory Components

Compulsory Course Component

Students must obtain 40% in the final exam to pass the course.
Student achieving >25% but less that 40% will be offered an alternate assessment if, and only if, all other assessment items have been submitted.
Students obtaining <25% will not be offered an alternate assessment, and will fail the course, unless students have submitted Adverse Circumstances in accordance with the Adverse Circumstances Policy.

Timetables