This course continues to build on topics taught in the previous two courses. It focuses on construction of medium scale programs, using design patterns and tools that are used in the software development process. Students will gain further experience with industry standard revision control and integrated development environment (IDE) tools.
Students will learn appropriate application of programming abstractions they have learned in previous courses to the structuring of medium scale software: inheritance, generic types, polymorphism, procedural abstraction, and abstract recursive data structures (including abstract syntax trees as a program representation, and tools that manipulate them).
The course also covers more advanced data structures, such as priority queues, B-trees, red-black trees, and AVL trees, and deepens understanding of appropriate algorithmic strategies.
The course also treats intellectual property considerations in software development and deployment.
Learning Outcomes
Upon successful completion, students will have the knowledge and skills to:
Upon completion of this course, the student will be able to:- Apply fundamental programming concepts for medium scale programs
- Understand basic types and the benefits of static typing, with understanding of generics, subtyping, and overloading, and their roles in structuring programs
- Map programming language abstractions through to execution environment; use non-source (text) internal representations of programs (e.g., abstract syntax trees); sketch low-level run-time representations of core language constructs (objects and closures)
- Describe contractual specifications, analyse documentation and specifications against other’s code, develop, understand, test, and evolve substantial programs using a modern IDE, and associated configuration tools; explain the importance of correctness for quality software; understand common coding errors and how to avoid them; practice fundamental defensive programming; understand principles of secure design
- Use, implement, and evaluate more advanced data structures and associated algorithms; discuss factors other than computational efficiency for evaluating software; create, implement, debug, and evaluate algorithms for solving problems, including recursively, using divide-and-conquer, and via decomposition; implement an abstract data type; analyse design and implementation alternatives
- Apply basic algorithmic analysis to simple algorithms; use big-O notation formally, upper lower, and expected case bounds; use and solve recurrence relations; use appropriate algorithmic approaches to solve problems (brute-force, greedy, divide-and-conquer, recursive backtracking, heuristic, dynamic programming, branch-and-bound)
- Explain how system components contribute to performance; understand Amdahl’s law and its limitations; design and conduct performance experiments; use software tools to profile and measure program performance
- Understand, apply, and analyse state and state machines in expressing computations
- Understand fundamental concepts of GUIs and user interfaces; understand the basics of modeling and simulation
- Contrast the concepts of copyright, patenting, and trademarks as mechanisms for protecting intellectual property, within the legal context for these mechanisms; understand, analyse, and evaluate ethical/social tradeoffs in technical decisions, evaluating stakeholder positions
Indicative Assessment
Assignments, labs, tutorials (40%); final exam (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
Thirty one hour lectures and nine 2 hour laboratory sessionsRequisite and Incompatibility
Prescribed Texts
No prescribed textbooks.
Assumed Knowledge
Introductory programming, preferably in an object-oriented language, to design and implement programs with several classes, with simple inheritance.
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 |
|---|---|---|---|---|---|---|
| 2209 | 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 |
|---|---|---|---|---|---|---|
| 9197 | 22 Jul 2019 | 29 Jul 2019 | 31 Aug 2019 | 25 Oct 2019 | In Person | N/A |