COMPSCI 750 : Computational Complexity


2024 Semester Two (1245) (15 POINTS)

Course Prescription

Definitions of computational models and complexity classes: time complexity (e.g., P and NP), space complexity (e.g., L and PSPACE), circuit and parallel complexity (NC), polynomial-time hierarchy (PH), interactive complexity (IP), probabilistic complexity (BPP), and fixed-parameter complexity. Recommended preparation: COMPSCI 320 or 350

Course Overview

The course surveys classical and recent computational  complexity results. Depending on the lecturers, the course  will include   descriptive string complexity,   quantum computing, logic, and randomness.


Course Requirements

No pre-requisites or restrictions

Capabilities Developed in this Course

Capability 3: Knowledge and Practice
Capability 4: Critical Thinking
Capability 5: Solution Seeking
Capability 6: Communication

Learning Outcomes

By the end of this course, students will be able to:
  1. Understand and describe key concepts and results in computational and descriptive complexity. (Capability 3, 4, 5 and 6)
  2. Formalise and abstract computational tasks and evaluate their complexities. (Capability 3, 4, 5 and 6)
  3. Present and critically analyse the basic models of quantum computing. (Capability 3, 4, 5 and 6)
  4. Apply theoretical results to problems in logic, randomness and big data. (Capability 3, 4, 5 and 6)
  5. Communicate and demonstrate theoretical results or applications to the class. (Capability 3, 4, 5 and 6)


Assessment Type Percentage Classification
Assignments 60% Individual Coursework
Test 40% Individual Test
Assessment Type Learning Outcome Addressed
1 2 3 4 5


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

Key Topics

  • Computational resources
  • Logic, in particular satisfiability of Boolean formulas
  • Classical versus quantum computing (depending on lecturer)
  • Special topics, such as randomness, proof complexity, and others

Workload Expectations

This course is a standard 15 point course. Students are expected to spend at least 10 hours per semester week involved in each 15 point course.

For this course, each week you can expect 2 hours of contact hours, 4 hours of assignment preparation, and 4 hours of self-directed learning. These are only guidelines and extra study may be required if you missing knowledge of some areas. 

Delivery Mode

Campus Experience

The course will take place on-campus. The activities for the course are scheduled as a standard weekly timetable.

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.

  • Michael Sipser, Introduction to the Theory of Computation, 2d or 3d edition. More references will be given in class.

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.

The course includes new topics such as randomness which are mathematically interesting
and relevant to the current practice of computing science.

Other Information

The content of this course is often formulated in terms of definitions, theorems and proofs as reviewed in the first Chapter of Sipser's textbook Introduction to the Theory of Computation. If you don't have experience with mathematics covered in CompSci 350 or Maths 315, you are strongly advised to talk to the course coordinator before enrolling.

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 for potential plagiarism or other forms of academic misconduct, using computerised detection mechanisms.

Class Representatives

Class representatives are students tasked with representing student issues to departments, faculties, and the wider university. If you have a complaint about this course, please contact your class rep who will know how to raise it in the right channels. See your departmental noticeboard for contact details for your class reps.


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


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 31/10/2023 10:51 a.m.