- Code COMP1130
- Unit Value 6 units
- Offered by School of Computing
- ANU College ANU College of Engineering Computing & Cybernetics
- Course subject Computer Science
- Areas of interest Computer Science, Information Technology, Software Engineering, Software Development, Computer Systems
This course is a variation on Programming for Problem Solving (COMP1100 ). It covers the same topics in more depth, requiring addtional contact hours to allow students to deepen their understanding and experience. They will understand the foundations of program semantics, program proof, and implementation of the programming language features that they have learned in the course. As the advanced version of the course the first six Learning Outcomes are the same as for COMP1100.
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.
- Reflect on the fundamental mathematical concepts underlying functional programming.
- Use formal proof and structural induction to reason about the correctness of functional programs.
- Assessing the significance of different evaluation strategies, including laziness, for the computational behaviour of functional programs.
This course may be taken as an alternative to Programming as Problem Solving COMP1100 and satisfies all prerequisites that would be satisfied by that course.
- Assignments (30) [LO 1,2,3,4,5,6]
- Lab Assessment (5) [LO 1,2,3,4,5,6]
- Mid-Term Exam (10) [LO 1,2,3,7,8]
- Final Exam (55) [LO 1,2,3,4,5,6,7,8,9]
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WorkloadForty 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
Assumed KnowledgeStudents are assumed to have achieved a level of knowledge of mathematics comparable to at least ACT Specialist Mathematics Major/Minor or NSW Mathematics Extension 1 or equivalent. No programming, Computer Science or IT experience or skills are required
Tuition fees are for the academic year indicated at the top of the page.
Commonwealth Support (CSP) Students
If you 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). More information about your student contribution amount for each course at Fees.
- Student Contribution Band:
- Unit value:
- 6 units
If you are a domestic graduate coursework student with a Domestic Tuition Fee (DTF) place or international student you will be required to pay course tuition fees (see below). Course tuition fees are indexed annually. Further information for domestic and international students about tuition and other fees can be found at Fees.
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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.
|Class number||Class start date||Last day to enrol||Census date||Class end date||Mode Of Delivery||Class Summary|
|4171||19 Feb 2024||26 Feb 2024||31 Mar 2024||24 May 2024||In Person||N/A|