# COMPSCI 720 : Advanced Design and Analysis of Algorithms

## Science

### 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.

### 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 part of this course studies 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. There is a substantial programming component and quiz on this part.

The second part covers parameterized and approximation algorithms for several classical NP-hard optimization problems. If time allows, we will also look at applications from computational biology. No knowledge of biology is required! The second part also has a practical component that requires you to read research papers, write a report, and give a presentation.

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.

### Course Requirements

Prerequisite: COMPSCI 320

### 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. Develop, design and justify efficient and correct structural graph algorithms. (Capability 1, 2 and 3)
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 from parameterized algorithms (e.g. kernelization, depth-bounded search trees) (Capability 1 and 2)
5. Explain and apply techniques from 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)

### Assessments

Assessment Type Percentage Classification
Coursework 100% Individual Coursework
1 2 3 4 5 6
Coursework

### Tuākana

Tuākana Science is a multi-faceted programme for Māori and Pacific students providing topic specific tutorials, one-on-one sessions, test and exam preparation and more. Explore your options at
https://www.auckland.ac.nz/en/science/study-with-us/pacific-in-our-faculty.html
https://www.auckland.ac.nz/en/science/study-with-us/maori-in-our-faculty.html

### Special Requirements

You must attend presentations by other students throughout the last four weeks of the course.

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, 3 hours of reading and thinking about the content, and 4 hours of work on assignments and other coursework.

### 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

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.

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.

Note for this year we plan to adjust the level of difficulty of the programming assignment and add a research report/presentation component in replacement to a final exam.

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.

### Class Representatives

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 course assessment continues to meet the principles of the University’s assessment policy. Some adjustments may need to be made in emergencies. You will be kept fully informed by your course co-ordinator/director, and if disruption occurs you should refer to the university website for information about how to proceed.

The delivery mode may change depending on COVID restrictions. Any changes will be communicated through Canvas.

### 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 .

### Disclaimer

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 students may be asked to submit 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. In exceptional circumstances changes to elements of this course may be necessary at short notice. Students enrolled in this course will be informed of any such changes and the reasons for them, as soon as possible, through Canvas.

Published on 31/10/2022 09:29 a.m.