COMPSCI 720 : Advanced Design and Analysis of Algorithms


2021 Semester One (1213) (15 POINTS)

Course Prescription

Selected advanced topics in design and analysis of algorithms, such as: combinatorial enumeration algorithms; advanced graph algorithms; analytic and probabilistic methods in the analysis of algorithms; randomised algorithms; methods for attacking NP-hard problems. Recommended preparation: COMPSCI 320 and a B- or higher in COMPSCI 220

Course Overview

Algorithm design and analysis is a fundamental and important part of computer science. This course introduces students to advanced techniques for the design and analysis of algorithms, and explores some applications  of the resulting algorithms. 

The first half of this course covers basic combinatorial algorithms (how to enumerate objects and rank/hash them). Additionally, we study advanced algorithms for families of graphs of bounded combinatorial width (treewidth, pathwidth, treedepth, branchwidth), often formulated as linear-time dynamic programs, for many popular NP-hard problems.

The second half covers parameterized and approximation algorithms for several classical NP-hard optimization problems. Towards the end of the course, we will also look at applications from computational biology. No knowledge in biology required!

The material taught in this course is particularly relevant for all students wishing to pursue further postgraduate studies in theoretical computer science or discrete mathematics and for those who are planning for a career that involves efficient programming and/or problem solving.

While there are no formal prerequisites for this course,  we recommend that students have successfully completed COMPSCI 220 and COMPSCI 320 and master the material of both courses.

Course Requirements

Prerequisite: Departmental approval

Capabilities Developed in this Course

Capability 1: Disciplinary Knowledge and Practice
Capability 2: Critical Thinking
Capability 3: Solution Seeking
Capability 4: Communication and Engagement
Capability 5: Independence and Integrity

Learning Outcomes

By the end of this course, students will be able to:
  1. Write efficient combinatorial object enumeration algorithms (e.g. subsets, permutations, integer and set partitions, rooted and free trees) (Capability 1 and 2)
  2. Define and explain the notion of bounded pathwidth and treewidth (including t-parses, partial k-trees and tree decompositions) (Capability 1 and 2)
  3. Develop and communicate linear-time graph algorithms for computational hard problems when the input is restricted (Capability 1, 3 and 4)
  4. Explain and apply techniques to design of parameterized algorithms (e.g. kernelization, depth-bounded search trees) (Capability 1 and 2)
  5. Explain and apply techniques to design approximation algorithms (e.g. greedy approximations, pricing method, linear programming) (Capability 1 and 2)
  6. Design simple parameterized and approximation algorithms (Capability 3, 4 and 5)


Assessment Type Percentage Classification
Assignments 40% Individual Coursework
Final Exam 60% Individual Examination
Assessment Type Learning Outcome Addressed
1 2 3 4 5 6
Final Exam

Special Requirements


Workload Expectations

This course is a standard 15 point course and students are expected to spend 10 hours per week involved in each 15 point course that they are enrolled in.

For this course, you can expect 3 hours of lectures, 4 hours of reading and thinking about the content and  3 hours of work on assignments or exam preparation on average per week.

Delivery Mode

Campus Experience

Attendance is expected at scheduled activities including lectures.
Depending on assigned lecture theatre, lectures will be available as recordings.
The course will not include live online events.
Attendance on campus is required for the exam.
The activities for the course are scheduled as a standard weekly timetable.

This course is available for remote students.

Learning Resources

All reading resources are freely accessible through he University Library websites and links will be provided in Canvas.

Student Feedback

During the course Class Representatives in each class can take feedback to the staff responsible for the course and staff-student consultative committees.

At the end of the course students will be invited to give feedback on the course and teaching through a tool called SET or Qualtrics. The lecturers and course co-ordinators will consider all feedback.

Your feedback helps to improve the course and its delivery for all students.

Digital Resources

Course materials are made available in a learning and collaboration tool called Canvas which also includes reading lists and lecture recordings (where available).

Please remember that the recording of any class on a personal device requires the permission of the instructor.

Academic Integrity

The University of Auckland will not tolerate cheating, or assisting others to cheat, and views cheating in coursework as a serious academic offence. The work that a student submits for grading must be the student's own work, reflecting their learning. Where work from other sources is used, it must be properly acknowledged and referenced. This requirement also applies to sources on the internet. A student's assessed work may be reviewed against online source material using computerised detection mechanisms.


The content and delivery of content in this course are protected by copyright. Material belonging to others may have been used in this course and copied by and solely for the educational purposes of the University under license.

You may copy the course content for the purposes of private study or research, but you may not upload onto any third party site, make a further copy or sell, alter or further reproduce or distribute any part of the course content to another person.

Inclusive Learning

All students are asked to discuss any impairment related requirements privately, face to face and/or in written form with the course coordinator, lecturer or tutor.

Student Disability Services also provides support for students with a wide range of impairments, both visible and invisible, to succeed and excel at the University. For more information and contact details, please visit the Student Disability Services’ website

Special Circumstances

If your ability to complete assessed coursework is affected by illness or other personal circumstances outside of your control, contact a member of teaching staff as soon as possible before the assessment is due.

If your personal circumstances significantly affect your performance, or preparation, for an exam or eligible written test, refer to the University’s aegrotat or compassionate consideration page

This should be done as soon as possible and no later than seven days after the affected test or exam date.

Learning Continuity

In the event of an unexpected disruption we undertake to maintain the continuity and standard of teaching and learning in all your courses throughout the year. If there are unexpected disruptions the University has contingency plans to ensure that access to your course continues and your assessment is fair, and not compromised. Some adjustments may need to be made in emergencies. You will be kept fully informed by your course co-ordinator, and if disruption occurs you should refer to the University Website for information about how to proceed.

Level 1: Delivered normally as specified in delivery mode
Level 2: You will not be required to attend in person. All teaching and assessment will have a remote option. 
Level 3 / 4: All teaching activities and assessments are delivered remotely .

Student Charter and Responsibilities

The Student Charter assumes and acknowledges that students are active participants in the learning process and that they have responsibilities to the institution and the international community of scholars. The University expects that students will act at all times in a way that demonstrates respect for the rights of other students and staff so that the learning environment is both safe and productive. For further information visit Student Charter


Elements of this outline may be subject to change. The latest information about the course will be available for enrolled students in Canvas.

In this course you may be asked to submit your coursework assessments digitally. The University reserves the right to conduct scheduled tests and examinations for this course online or through the use of computers or other electronic devices. Where tests or examinations are conducted online remote invigilation arrangements may be used. The final decision on the completion mode for a test or examination, and remote invigilation arrangements where applicable, will be advised to students at least 10 days prior to the scheduled date of the assessment, or in the case of an examination when the examination timetable is published.

Published on 26/11/2020 05:57 p.m.