• Offered by Research School of Computer Science
  • ANU College ANU College of Engineering and Computer Science
  • Course subject Computer Science
  • Academic career PGRD
  • Course convener
    • Dr Dirk Pattinson
  • Mode of delivery In Person
  • Co-taught Course
  • Offered in Second Semester 2018
    See Future Offerings

This course presents some formal notations that are commonly used for the description of computation and of computing systems, for the specification of software and for mathematically rigorous arguments about program properties.  The following areas of study constitute the backbone of the course. Predicate calculus and natural deduction, inductive definitions of data types as a basis for recursive functions and structural induction, formal language theory (particularly regular expressions, finite state machines and context free grammars), and specification languages.

Learning Outcomes

Upon successful completion, students will have the knowledge and skills to:

Upon completion of this course, the student will be able to do the following:

  1. Apply the concepts of standard mathematical logic to produce proofs or refutations of well-formed propositions or arguments phrased in English or in a variety of formal notations (first order logic, discrete mathematics or Hoare logic). Express problems, presented in English, in these formal notations and demonstrate an awareness of the differences between them.
  2. Generate a finite state automaton that recognises a given regular language either described in English or presented as a regular expression; similarly, describe the language accepted by a given deterministic or nondeterministic automaton.
  3. Relate structural induction to other forms of mathematical induction, and write a recursive definition of a given simple operation on data of a given type presented via an inductive definition of the data structure.
  4. Explain the concept of program correctness and prove simple programs correct using Hoare Logic.
  5. Demonstrate understanding of Turing Machine computability, and design Turing Machines to accomplish simple tasks.

Indicative Assessment

Assignments (36%); Tutorials (4%); Quiz (10%); Final Exam (50%)

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Workload

Thirty one-hour lectures and nine one-hour tutorials

Requisite and Incompatibility

Incompatible with COMP1600

Specialisations

Fees

Tuition fees are for the academic year indicated at the top of the page.  

If you are a domestic graduate coursework or international student you will be required to pay tuition fees. Tuition fees are indexed annually. Further information for domestic and international students about tuition and other fees can be found at Fees.

Student Contribution Band:
2
Unit value:
6 units

If you are an undergraduate student and have been offered a Commonwealth supported place, your fees are set by the Australian Government for each course. At ANU 1 EFTSL is 48 units (normally 8 x 6-unit courses). You can find your student contribution amount for each course at Fees.  Where there is a unit range displayed for this course, not all unit options below may be available.

Units EFTSL
6.00 0.12500
Domestic fee paying students
Year Fee
2018 $4080
International fee paying students
Year Fee
2018 $5400
Note: Please note that fee information is for current year only.

Offerings, Dates and Class Summary Links

ANU utilises MyTimetable to enable students to view the timetable for their enrolled courses, browse, then self-allocate to small teaching activities / tutorials so they can better plan their time. Find out more on the Timetable webpage.

The list of offerings for future years is indicative only.
Class summaries, if available, can be accessed by clicking on the View link for the relevant class number.

Second Semester

Class number Class start date Last day to enrol Census date Class end date Mode Of Delivery Class Summary
8361 23 Jul 2018 30 Jul 2018 31 Aug 2018 26 Oct 2018 In Person N/A

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