• 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 Undergraduate
  • Course convener
    • Dr Ekaterina Lebedeva
    • Prof Antony Hosking
  • Mode of delivery In Person
  • Co-taught Course ANUC1100
  • Offered in First Semester 2017
    Second Semester 2017
    See Future Offerings

This course is the first of three core computer science courses on programming. It introduces students to the field of computer science as a discipline for solving problems through computation and provides the foundation for more advanced courses on programming and software development. Data structures and algorithms, the key concepts at the core of computer science, receive their first treatment in this course. The course addresses both functional and imperative programming paradigms.

The course covers functional programming in depth, developing the core idea of functions operating on data structures.  Students learn the organization of programming languages using types, how programs are evaluated (reduction), functional composition, recursive functions, algebraic data types, pattern matching, parametric polymorphism, higher-order functions.  Students also gain exposure to structural induction and proof, introduction to asymptotic analysis of basic data structures, abstract data types, modules, laziness, and streams. The functional paradigm demonstrates elegant solutions to many programming problems.

The course also introduces imperative programming as an alternative paradigm to functional programming, highlighting similarities and contrasting differences. Students learn the basic ingredients of imperative programs: mutable variables, sequencing, conditionals, iteration, functions, eager evaluation, and side effects.

The course also introduces students to standard productivity tools for software development that will be used throughout the course and remainder of the computer science degree. These include distributed software revision control systems.

The Advanced version of this course covers these topics in more depth, allowing students to deepen their understanding and experience.

Learning Outcomes

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

  1. Apply fundamental programming concepts, using a functional programming language, to solve simple problems.
  2. Understand basic types and the benefits of static typing.
  3. Distinguish language definition from implementation, syntax and parsing from semantics and evaluation.
  4. Describe, understand and evolve programs, via documentation, testing, and debugging.
  5. Discuss, use, and apply the fundamentals of data structures, algorithms, and design; create, implement, and debug algorithms for solving simple problems, including recursively, using divide-and-conquer, and via decomposition.
  6. Discuss basic algorithmic analysis for simple algorithms; determine appropriate algorithmic approaches to a problem (brute-force, greedy, divide-and-conquer, recursive backtracking, heuristic, dynamic programming).
  7. Describe and apply alternative computational paradigms to simple problems.
  8. Understand the legal context for protection of software as intellectual property.

Indicative Assessment

Assignments (30%), Lab Assessment (5%), Mid-Term Exam (10%), Final Exam (55%)

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

Thirty hours of lectures, twelve two-hour tutorial/laboratory sessions. At least the same amount of time will be required to work through the material, and prepare assignments and for labs

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. 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:
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
2017 $3660
International fee paying students
Year Fee
2017 $4878
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
2295 20 Feb 2017 27 Feb 2017 31 Mar 2017 26 May 2017 In Person

Second Semester

Class number Class start date Last day to enrol Census date Class end date Mode Of Delivery
9692 24 Jul 2017 31 Jul 2017 31 Aug 2017 27 Oct 2017 In Person

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