Introduction to Algorithmics

10 Units

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.

Faculty Faculty of Engineering and Built Environment
School School of Electrical Engineering and Computer Science
Availability Semester 2 - 2014 (Callaghan Campus)
Semester 2 - 2015 (Callaghan Campus)

(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.


(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 0
Assumed Knowledge SENG6120 Knowledge of discrete mathematics.
Modes of Delivery Internal Mode
Teaching Methods Problem Based Learning
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.
Course Materials None listed
Timetable 2015 Course Timetables for COMP6230

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