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COMP5211: Algorithms (2011 - Semester 1)

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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: Wolle, Thomas
Session options: Semester 1, Semester 2
Versions for this Unit:
Site(s) for this Unit: http://thomaswolle.net/COMP5211/index.html
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 and algorithms, and it 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, greedy approaches, 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. Some knowledge of computer programming is required.
Lecturer/s: Wolle, Thomas
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 1 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 Algorithms Design and Problem Solving Skills (Level 4)

For explanation of attributes and levels see Engineering/IT Graduate Attribute Matrix 2009.

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 and Problem Solving Skills (Level 4)
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 Homework Assignment No 50.00 Multiple Weeks
2 Final Exam No 50.00 Exam Period
Assessment Description: Homework Assignment:

Every week, small assignments are handed out and/or announced that are to be done by the students as homework. These homeworks have to be independently solved (approximately) within one week, and handed in by email. These homeworks will be marked, and these marks contribute 50% to the final mark of the course. Handing in homework as a group of students is not allowed. However, students are allowed to discuss homework and class material with peers. Also, using additional resources, such as (other) books, the Internet, scientific papers etc. is allowed. When formulating and writing down solutions, students have to work alone, and they have to cite all the sources/references that were used. Representing other people`s work as your own, is plagiarism and is in violation of university policies.

Note that we reserve the right not to hand out homework assignments strictly every single week.

Also, we reserve the right to have an oral examination of the assignments if we believe it is necessary (for instance, when there is too much similarity between two students homework, etc.).

Final Exam:

Written Final Exam. The mark of the exam contributes 50% to the final mark of the course.

It is a policy of the School of Information Technologies that in order to pass this unit, a student must attain a mark of at least 40% in the written examination as well as any other major component of Assessment nominated by the lecturer. A student must also achieve an overall final mark of 50 or more. Any student not meeting these requirements can achieve a maximum mark of no more than 45.

Late work: In the interest of fairness to all students, the School of Information Technologies policy states that late work cannot be accepted. In exceptional cases late work must be submitted directly to the unit of study coordinator accompanied by an application for Special Consideration as outlined on page 16 of the School of Information Technologies Postgraduate Enrolment Guide.
Grading:
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 http://sydney.edu.au/policies . 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.
Special Conditions to Pass UoS To pass this unit of study a minimum mark of 40% must be obtained in the final examination.
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

Faculty policies regarding academic honesty and plagiarism, special consideration and appeals in Engineering and Information Technologies can be found on the Faculty's policy page at http://www.eng.usyd.edu.au/policies"> http://www.eng.usyd.edu.au/policies. School and Faculty policies are governed by Academic Board resolutions whose details can be found on the Central Policy Online site at http://www.usyd.edu.au/policy/"> http://www.usyd.edu.au/policy/.

Policies regarding assessment formatting, submission methods, late submission penalties and assessment feedback depend on the unit of study. Details of these policies, where applicable, should be found above with other assessment details.
Prescribed Text/s: Note: Students are expected to have a personal copy of all books listed.
  • Algorithm Design
Online Course Content: http://thomaswolle.net/COMP5211/index.html

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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 / Science 2011, 2012, 2013, 2014
Master of Engineering (2024 and earlier) 2014

Course Goals

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

Attribute Practiced Assessed
Design and Problem Solving Skills (Level 4) Yes 0%

These goals are selected from Engineering/IT Graduate Attribute Matrix 2009 which defines overall goals for courses where this unit is primarily offered. See Engineering/IT Graduate Attribute Matrix 2009 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.