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COMP5211: Algorithms (2014 - Semester 2)

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Unit: COMP5211: Algorithms (6 CP)
Mode: Normal-Day
On Offer: Yes
Level: Postgraduate
Faculty/School: School of Computer Science
Unit Coordinator/s: Dr Viglas, Anastasios
Session options: Semester 2
Versions for this Unit:
Campus: Camperdown/Darlington
Pre-Requisites: None.
Brief Handbook Description: The study of algorithms is a fundamental aspect of computing. This unit of study covers data structures, algorithms, and gives an overview of the main ways of computational thinking from simple list manipulation and data format conversion, up to shortest paths and cycle detection in graphs. Students will gain essential knowledge in computer science, including basic concepts in data structures, algorithms, and intractability, using paradigms such as dynamic programming, divide and conquer, greed, local search, and randomisation, as well NP-hardness.
Assumed Knowledge: This unit of study assumes that students have general knowledge of mathematics (especially Discrete Math) and problem solving. Having moderate knowledge about Data structure can also help students to better understand the concepts of Algorithms will be taught in this course.
Lecturer/s: Dr Viglas, Anastasios
Timetable: COMP5211 Timetable
Time Commitment:
# Activity Name Hours per Week Sessions per Week Weeks per Semester
1 Independent Study 5.00 13
2 Lecture 2.00 1 13
3 Tutorial 1.00 2 13
T&L Activities: Lecture: Lecture

Tutorial: Tutorial

Attributes listed here represent the key course goals (see Course Map tab) designated for this unit. The list below describes how these attributes are developed through practice in the unit. See Learning Outcomes and Assessment tabs for details of how these attributes are assessed.

Attribute Development Method Attribute Developed
Understand main concepts of Graphs. Design (Level 2)

For explanation of attributes and levels see Engineering & IT Graduate Outcomes Table.

Learning outcomes are the key abilities and knowledge that will be assessed in this unit. They are listed according to the course goal supported by each. See Assessment Tab for details how each outcome is assessed.

Design (Level 2)
1. Knowledge of fundamental algorithms for several problems, including graphs, greedy agorithms, divide-and-conquer, dynamic programming, and network flow as well as basic concepts of NP-completeness.
2. Collaboration in lectures/tutorials and exchange of ideas to solve algorithmic problems.
3. Ability to understand and analyze given algorithms as well as ability to design algorithmic solutions for given problems.
4. Students will practice their writing presentation skills.
Assessment Methods:
# Name Group Weight Due Week Outcomes
1 Assignments No 20.00 Multiple Weeks 1, 2, 3, 4,
2 Quizzes No 20.00 Multiple Weeks 1, 2, 3, 4,
3 Final Exam No 60.00 Exam Period 1,
Assessment Description: Assignment: Short weekly assignments, that may include implementations of algorithms.

Quiz: Short weekly quizzes, during tutorial times, on e-learning.

Final Exam: Final Examination
Grade Type Description
Standards Based Assessment Final grades in this unit are awarded at levels of HD for High Distinction, DI (previously D) for Distinction, CR for Credit, PS (previously P) for Pass and FA (previously F) for Fail as defined by University of Sydney Assessment Policy. Details of the Assessment Policy are available on the Policies website at . Standards for grades in individual assessment tasks and the summative method for obtaining a final mark in the unit will be set out in a marking guide supplied by the unit coordinator.
Policies & Procedures: IMPORTANT: School policy relating to Academic Dishonesty and Plagiarism.

In assessing a piece of submitted work, the School of IT may reproduce it entirely, may provide a copy to another member of faculty, and/or to an external plagiarism checking service or in-house computer program and may also maintain a copy of the assignment for future checking purposes and/or allow an external service to do so.

Other policies

See the policies page of the faculty website at for information regarding university policies and local provisions and procedures within the Faculty of Engineering and Information Technologies.
Prescribed Text/s: Note: Students are expected to have a personal copy of all books listed.
  • Algorithm Design

Note that the "Weeks" referred to in this Schedule are those of the official university semester calendar

Week Description
Week 1 Unit introduction, algorithms and complexity, motivation and course outline.
Week 2 Introduction to graph algorithms: BFS and DFS
Week 3 Greedy algorithms: Interval scheduling, Kruskal's algorithm, Dijkstra's algorithm
Week 4 Divide and conquer: Recurrences, sorting, integer multiplication, selection
Week 5 Dynamic programming: weighted interval scheduling, longest increasing subsequence, knapsack
Week 6 Dynamic programming: Nim, RNA structure
Week 7 Network flows, maxflow mincut theorems, matching
Week 8 Max-flow and min-cut applications: Disjoint paths, airline scheduling, project section
Week 9 Introduction to complexity theory: Polynomial time reductions, P, NP, and NP-completeness
Week 10 Coping with hardness: Solving special cases, approximations, local search
Week 11 Beyond NP: Weakly NP-hard, coNP, PSPACE
Week 12 Advanced topic such as fixed parameter tractability, hashing, other complexity classes, etc.
Week 13 Review and outlook
Exam Period Assessment Due: Final Exam

Course Relations

The following is a list of courses which have added this Unit to their structure.

Course Year(s) Offered
Master of Professional Engineering (Software) 2013, 2014
Software Engineering / Arts 2011, 2012, 2013, 2014
Software Engineering / Commerce 2010, 2011, 2012, 2013, 2014
Software Engineering / Medical Science 2011, 2012, 2013, 2014
Software Engineering / Project Management 2012, 2013, 2014
Software Engineering / Science 2011, 2012, 2013, 2014
Master of Engineering 2014

Course Goals

This unit contributes to the achievement of the following course goals:

Attribute Practiced Assessed
Design (Level 2) Yes 100%
Maths/Science Methods and Tools (Level 2) No 0%
Engineering/IT Specialisation (Level 2) No 0%

These goals are selected from Engineering & IT Graduate Outcomes Table which defines overall goals for courses where this unit is primarily offered. See Engineering & IT Graduate Outcomes Table for details of the attributes and levels to be developed in the course as a whole. Percentage figures alongside each course goal provide a rough indication of their relative weighting in assessment for this unit. Note that not all goals are necessarily part of assessment. Some may be more about practice activity. See Learning outcomes for details of what is assessed in relation to each goal and Assessment for details of how the outcome is assessed. See Attributes for details of practice provided for each goal.