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 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 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 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 successful completion, students will have the knowledge and skills to:
- Apply fundamental programming concepts, using a functional programming language, to solve problems.
- Understand basic types and the benefits of static typing.
- Describe, understand and evolve programs, via documentation, testing, and debugging.
- Discuss, use, and apply the fundamentals of data structures, algorithms, and design; create, implement, and debug algorithms for solving problems, including recursively, using divide-and-conquer, and via decomposition.
- Discuss basic algorithmic analysis for simple algorithms; determine appropriate algorithmic approaches to a problem (for example bruteforce, greedy, divide-and-conquer, recursive backtracking, heuristic, dynamic programming).
- Understand and apply the concepts of parametric and ad-hoc polymorphism
Indicative Assessment
- Assignments (3) (30) [LO 1,2,3,4,5,6]
- Lab Assessment (5) [LO 1,2,3,4,5,6]
- Mid-term exam (10) [LO 1,2,3,4,5,6]
- Final Exam (hurdle) (55) [LO 1,2,3,4,5,6]
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, prepare for labs, and complete assignments.
Inherent Requirements
Not applicable
Requisite and Incompatibility
Prescribed Texts
Simon Thompson, Haskell: The Craft of Functional Programming — third edition, 2011, Addison Wesley
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.
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:
- 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 |
Course fees
- Domestic fee paying students
| Year | Fee |
|---|---|
| 2019 | $4320 |
- International fee paying students
| Year | Fee |
|---|---|
| 2019 | $5700 |
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.
Class summaries, if available, can be accessed by clicking on the View link for the relevant class number.
First Semester
| Class number | Class start date | Last day to enrol | Census date | Class end date | Mode Of Delivery | Class Summary |
|---|---|---|---|---|---|---|
| 2208 | 25 Feb 2019 | 04 Mar 2019 | 31 Mar 2019 | 31 May 2019 | In Person | N/A |
Second Semester
| Class number | Class start date | Last day to enrol | Census date | Class end date | Mode Of Delivery | Class Summary |
|---|---|---|---|---|---|---|
| 9196 | 22 Jul 2019 | 29 Jul 2019 | 31 Aug 2019 | 25 Oct 2019 | In Person | N/A |
