• Offered by Research School of Computer Science
  • ANU College ANU College of Engineering and Computer Science
  • Course subject Computer Science
  • Areas of interest Business Information Systems, Digital Arts, Bioinformatics, Computer Science, Mathematics More...
  • Academic career UGRD
  • Course convener
    • Dr Uwe Zimmer
  • Mode of delivery In Person
  • Offered in First Semester 2014
    See Future Offerings

Computer programs as a formal definition of a desired method or outcome (algorithm) are cornerstones in almost any current product design. Those programs are then mechanically translated and executed on a computer.

The course introduces the art of programming in small steps, starting from clearly structuring the required data. Typed functions, conditional expressions, and repetition (recursion) are introduced alongside as the basic methods to operate on this structured data. A key aim is to illustrate the interdependancy of algorithms and data structures - significantly, that data structures largely determine algorithms, for example, that products are processed by projections, unions by alternatives, and that recursive data structures such as lists are processed by recursive algorithms.

Programs also require time to execute in a computer system. Basic understanding of the relation between program design and execution time is an essential part of an efficient design.

For all but the simplest programs, some means of abstraction and structuring is required to manage the complexities faced by programmers, as individuals and as groups. The course introduces modularisation techniques and abstract data types, as a means of managing such complexity. Modular design is of fundamental and practical importance for program development and leads to elegant and maintainable programs.

Learning Outcomes

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

Students who succeed in all aspects of this course will be able to:

  • describe and contrast various algorithmic components, and relate them to specific corresponding data structures.
  • analyse program fragments and explain their types, behaviours and effects.
  • design algorithmic solutions to simple problems and present their implementation in a functional programming language and an object-oriented programming language.
  • design data structures appropriate for the representation and implementation of simple algorithmic problems.
  • analyse small programming problems to suggest, design and implement appropriate modular program structures, based on a data-directed approach.

Indicative Assessment

Continuous Assessment (40%); Examinations (60%)

The ANU uses Turnitin to enhance student citation and referencing techniques, and to assess assignment submissions as a component of the University's approach to managing Academic Integrity. While the use of Turnitin is not mandatory, the ANU highly recommends Turnitin is used by both teaching staff and students. For additional information regarding Turnitin please visit the ANU Online website.

Workload

Twenty two one-and-a-half-hour lectures, ten two-hour tutorial/laboratory sessions. At least the same amount of time will be required to work through the material, and prepare labs and assignments.

Requisite and Incompatibility

You are not able to enrol in this course if you have completed COMP1130.

Assumed Knowledge

Students are assumed to have achieved a level of knowledge of mathematics comparable to at least ACT Maths Methods major or NSW 2 unit maths or equivalent.

Areas of Interest

  • Business Information Systems
  • Digital Arts
  • Bioinformatics
  • Computer Science
  • Mathematics
  • Electronic Commerce
  • Information Technology
  • Software Engineering
  • Engineering
  • Mechatronics
  • Robotics
  • Advanced Computing
  • Information Systems
  • Human Centred Computing
  • Information-Intensive Computing
  • Intelligent Systems
  • Software Development
  • IT in New Media
  • Algorithms and Data
  • Artifical Intelligence
  • Computer Systems
  • Computer Engineering
  • Computational Foundations

Majors

Minors

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. Students continuing in their current program of study will have their tuition fees indexed annually from the year in which you commenced your program. 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
1994-2003 $1650
2004 $2190
2005 $2190
2006 $2190
2007 $2298
2008 $2592
2009 $2850
2010 $2916
2011 $2946
2012 $2946
2013 $2946
2014 $2952
International fee paying students
Year Fee
1994-2003 $3234
2004 $3234
2005 $3288
2006 $3426
2007 $3426
2008 $3426
2009 $3426
2010 $3750
2011 $3756
2012 $3756
2013 $3756
2014 $3762
Note: Please note that fee information is for current year only.

Offerings and Dates

The list of offerings for future years is indicative only

First Semester

Class number Class start date Last day to enrol Census date Class end date Mode Of Delivery Class Summary
2891 17 Feb 2014 07 Mar 2014 31 Mar 2014 30 May 2014 In Person N/A

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