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Advanced Theoretical Computer Science (COMP90057)
Graduate courseworkPoints: 12.5On Campus (Parkville)
To learn more, visit 2023 Course and subject delivery.
About this subject
- Overview
- Eligibility and requirements
- Assessment
- Dates and times
- Further information
- Timetable(opens in new window)
Contact information
Semester 2
Overview
Availability | Semester 2 |
---|---|
Fees | Look up fees |
AIMS
At the heart of theoretical computer science are questions of both philosophical and practical importance. What does it mean for a problem to be solvable by computer? What are the limits of computability? Which types of problems can be solved efficiently? What are our options in the face of intractability? This subject covers such questions in the content of a wide-ranging exploration of the nexus between logic, complexity and algorithms, and examines many important (and sometimes surprising) results about the nature of computing.
INDICATIVE CONTENT
- Turing machines
- The Church-Turing Thesis
- Decidable languages
- Reducability
- Time Complexity: The classes P and NP, NP-complete problems
- Space complexity: including sub-linear space
- Circuit complexity
- Approximation algorithms
- Probabilistic complexity classes
- Additional topics may include descriptive complexity, interactive proofs, communication complexity, complexity as applied to cryptography
- Space complexity, including sub-linear space
- Finite state automata, pushdown automata, regular languages, context-free languages to the Recommended Background Knowledge.
Example of assignment
- Proving the equivalence of a variant of a standard machine to the original version
- Describing an NP-hardness reduction
- Designing an approximation algorithm for an NP-hard problem.
Intended learning outcomes
INTENDED LEARNING OUTCOMES (ILO)
On completion of this subject the student is expected to:
- Design, manipulate, and reason about Turing machines
- Account for the inherent complexity of many computational problems of practical importance
- Conduct formal reasoning about machines, circuits, problems and algorithms, including reduction-based proof
- Design approximation algorithms for intractable problems
- Apply complexity arguments to related fundamental computational problems, such as randomized computations, interactive proof systems and cryptographic pseudorandom generators
Generic skills
On completion of this subject, students should have developed the following skills:
- Ability to apply knowledge of science and engineering fundamentals
- Ability to communicate effectively, with the engineering team and with the community at large
- Capacity for lifelong learning and professional development
- Profound respect for truth and intellectual integrity, and for the ethics of scholarship.
Last updated: 31 January 2024
Eligibility and requirements
Prerequisites
Code | Name | Teaching period | Credit Points |
---|---|---|---|
COMP30026 | Models of Computation | Semester 2 (On Campus - Parkville) |
12.5 |
OR
Equivalent (COMP20004 Discrete Structures prior to 2014)
OR
Admission into one of the following:
- 100pt Program course entry point in the MC-IT Master of Information Technology
- MC-CS Master of Computer Science
- MC-SCICMP Master of Science (Computer Science)
Corequisites
Non-allowed subjects
433-330 Theory of Computation
COMP30025 Theory of Computation
COMP30021 Theoretical Computer Science
Recommended background knowledge
Proficiency in discrete mathematics and propositional logic.
Inherent requirements (core participation requirements)
The University of Melbourne is committed to providing students with reasonable adjustments to assessment and participation under the Disability Standards for Education (2005), and the Assessment and Results Policy (MPF1326). Students are expected to meet the core participation requirements for their course. These can be viewed under Entry and Participation Requirements for the course outlines in the Handbook.
Further details on how to seek academic adjustments can be found on the Student Equity and Disability Support website: http://services.unimelb.edu.au/student-equity/home
Last updated: 31 January 2024
Assessment
Description | Timing | Percentage |
---|---|---|
Quiz (30 min). Week 4.
| Week 4 | 5% |
Assignment 1. 15%. Week 8.
| Week 8 | 15% |
Assignment 2. 5%. Week 12.
| Week 12 | 5% |
Weekly pre-tutorial activity (weeks 3 – 12). 15%
| From Week 3 to Week 12 | 15% |
Two-hour exam. 60%
| During the examination period | 60% |
Additional details
Hurdle Requirement: To pass the subject, students must obtain at least:
- hurdle on non-exam items: 20/40
- hurdle on exam: 30/60 .
Assessment addresses all Intended Learning Outcomes (ILOs)
Last updated: 31 January 2024
Dates & times
- Semester 2
Coordinator Daniel Beck Mode of delivery On Campus (Parkville) Contact hours 36 hours, comprising two 1-hour lectures and one 1-hour tutorial Total time commitment 200 hours Teaching period 24 July 2023 to 22 October 2023 Last self-enrol date 4 August 2023 Census date 31 August 2023 Last date to withdraw without fail 22 September 2023 Assessment period ends 17 November 2023 Semester 2 contact information
Time commitment details
200 hours
What do these dates mean
Visit this webpage to find out about these key dates, including how they impact on:
- Your tuition fees, academic transcript and statements.
- And for Commonwealth Supported students, your:
- Student Learning Entitlement. This applies to all students enrolled in a Commonwealth Supported Place (CSP).
Subjects withdrawn after the census date (including up to the ‘last day to withdraw without fail’) count toward the Student Learning Entitlement.
Last updated: 31 January 2024
Further information
- Texts
Prescribed texts
Michael Sipser, "Introduction to the Theory of Computation", 3rd Edition.
- Related Handbook entries
This subject contributes to the following:
Type Name Course Master of Data Science Course Ph.D.- Engineering Course Doctor of Philosophy - Engineering Course Master of Philosophy - Engineering Course Master of Science (Computer Science) Specialisation (formal) Computing Specialisation (formal) Software Specialisation (formal) Software with Business Specialisation (formal) Distributed Computing - Available through the Community Access Program
About the Community Access Program (CAP)
This subject is available through the Community Access Program (also called Single Subject Studies) which allows you to enrol in single subjects offered by the University of Melbourne, without the commitment required to complete a whole degree.
Entry requirements including prerequisites may apply. Please refer to the CAP applications page for further information.
Additional information for this subject
Subject coordinator approval required
- Available to Study Abroad and/or Study Exchange Students
This subject is available to students studying at the University from eligible overseas institutions on exchange and study abroad. Students are required to satisfy any listed requirements, such as pre- and co-requisites, for enrolment in the subject.
Last updated: 31 January 2024