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Advanced Theoretical Computer Science (COMP90057)
Graduate courseworkPoints: 12.5On Campus (Parkville)
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: 3 November 2022
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 entry to MC-IT Spatial 100-point program
Corequisites
None
Non-allowed subjects
433-330 Theory of Computation
COMP30025 COMP30021
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: 3 November 2022
Assessment
Additional details
- Three individual assignments involving mathematical proof and possibly some programming, requiring approximately 35 - 40 hours of work in total, due in weeks 4, 7 and 11 (30%)
- 3-hour written examination held at the end of semester (70%).
Hurdle Requirement: To pass the subject, students must obtain at least:
- 15/30 in the assignments
- 35/70 on the examination.
Assessment addresses all Intended Learning Outcomes (ILOs)
Last updated: 3 November 2022
Dates & times
- Semester 2
Principal coordinator Tony Wirth Mode of delivery On Campus (Parkville) Contact hours 48 hours Total time commitment 200 hours Teaching period 29 July 2019 to 27 October 2019 Last self-enrol date 9 August 2019 Census date 31 August 2019 Last date to withdraw without fail 27 September 2019 Assessment period ends 22 November 2019 Semester 2 contact information
Time commitment details
200 hours
Last updated: 3 November 2022
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 Doctor of Philosophy - Engineering Course Master of Philosophy - Engineering Course Master of Science (Computer Science) Course Master of Data Science Course Ph.D.- Engineering Specialisation (formal) Spatial Specialisation (formal) Distributed Computing Specialisation (formal) Computing Specialisation (formal) Software with Business Specialisation (formal) Software - 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: 3 November 2022