FIT2004 is a second year core unit in the Bachelor of Computer Science (BCS) and the Bachelor of Software Engineering (BSE). It was introduced as part of the faculty restructure for 2006. Previously these degrees had a core unit CSE2304. FIT2004 is based on the late CSE2304 but has been somewhat revised due to changes in the pre-requisite units (for example FIT1008 differs from CSE1303) and other core units in the degrees.

29/08/2017 - Admin: update prerequisites to include a new unit being introduced as part of the redevelopment of the Bachelor of Computer Science Advanced (Honours) for 2018.

05/01/2017 -- Changed Exam writing time (from 3 to 2 hours) and in-semester assessment proportion (from 30% to 40%) to comply with the University policy. This change will be effective from S1/2017

19/05/14 - Added FIT2085 (new 2nd year version of FIT1008 for BSc students completing a computational science major) as alternate prerequisite for FIT1008. For 2015 implementation.

14/05/14 - Admin update: minor change to learning outcomes (as approved by ADE).

January 2014: The reasons for change are: workload requirements - the labs will run weekly which will assist the students learning with more practical work. Updated learning outcomes - required for AQF compliance.

Updated learning outcomes, synopsis and workload requirements to introduce weekly labs (rather than fortnightly). Unit will now run a 3-hour lab each fortnight, alternating with a 2-hour lab and a 1-hour tutorial each fortnight (in the same 3 hour timeslot). Effective S1, 2014.

Removed FIT2071 from prohibitions as per discussions with Chief examiners of both units and ADE. Effective S1, 2012.

Modified Pre-reqs for Sem 1,2011 implementation.

19/9/2019: Admin - updating exam duration to include additional 10 minutes as per University requirement.

30/1/2020: Changing on campus workload requirements from Lab to Studios, since Laboratory was not an appropriate description.

5/8/2020: Changing exam from 60% to 50%, and in semester assessment from 40% to 50%. The marks are being made commensurate with the workload. To be actioned for S1 2021.

10/02/2021: Admin - Updating prerequisites to explicitly list the appropriate maths units as per discussion with Manager, Student Services.

The unit is a second year core unit in the BCS, BSE, BCS/BA, BCS/LLB, and BSc/BCS degrees at the Clayton campus. It is part of a sequence of learning and practice about algorithms and data-structures. It applies and further develops techniques for the design and analysis of algorithms and data-structures taught in FIT1008/FIT1015 Computer Science, and which continue to be studied in greater depth in FIT3014 Analysis and Design of Algorithms.

Its most important role is to provide students with problem solving capabilities. In particular, it teaches them how to: formally specify a problem from an informal description; design algorithmic solutions for it; analyse the correctness and complexity of such algorithms; and implement them as an efficient computer program.

The algorithm' is the central object of study in computer science. FIT2004 equips students with the capability for solving new computing problems, that is, those without existing text-book solutions. In doing so, it introduces algorithms and data structures, which are part of the working computer scientists of software engineers' toolkit, and which are more advanced than those introduced by its prerequisite FIT1008/FIT1015 Computer Science. These algorithms and data structures are studied using techniques of a mathematical nature, hence the math requirement.

On completion of this unit, you should be able to:

1. analyse general problem solving strategies and algorithmic paradigms, and apply them to solving new problems.
2. prove correctness of programs, analyse their space and time complexities.
3. compare and contrast various abstract data types and use them appropriately.
4. develop and implement algorithms to solve computational problems.

020109

This unit introduces students to problem solving concepts and techniques fundamental to the science of programming. In doing this it covers problem specification, algorithmic design, analysis and implementation. Detailed topics include analysis of best, average and worst-case time and space complexity; introduction to numerical algorithms; recursion; advanced data structures such as heaps and B-trees; hashing; sorting algorithms; searching algorithms; graph algorithms; and numerical computing.

On campus

Weekly activities: 10% - ULOS

Assignments: 30% - ULOS

Examination (2 hours and 10 minutes): 60% - ULOS

Minimum total expected workload equals 12 hours per week comprising:

FIT

One of (FIT1008, FIT1054, FIT2085, FIT1015, CSE1303) and one of (ENG1005, MAT1830, MAT1841, MAT2003, MTH1030, MTH1035).