Faculty of Information Technology
FIT1008 Fundamentals of algorithms is a level 1, 6-credit-point, undergraduate unit from the Faculty of Information Technology, offered in 2026 in Semester 1 and Semester 2 at Clayton and Malaysia. It needs (FIT1045 or FIT1053) and (FIT1058 or MAT1830) and unlocks 14 units, leading on to 53 units in all. Students rate it 4.0 out of 5 from 1 review and call it hard.
The 2027 handbook has no page for FIT1008. This is its 2026 entry, the latest one.
Solid introduction to data structures and complexity. The content is genuinely useful for interviews later on. Assignment specs were a bit long and some marking felt strict on edge cases, so read the rubric carefully and write your own tests.
You can't enrol if you have passed any of these.
Pass these before you enrol.
14 units list FIT1008 as a prerequisite or corequisite.
Prerequisites: Students beginning FIT1008 are assumed to be able to: Identify the main components of an algorithm (variables, operators, expressions, etc), and write the algorithm associated to the specification of a simple problem. Be able to translate a simple algorithm into a program containing variable declarations, selection, repetition, and lists and/or arrays.
The same content under another code. Only one of them counts.
From Semester 2, 2026: Data structures and algorithms are the tools that allow programs to solve problems efficiently, reliably and at scale. This unit develops the core algorithmic thinking and implementation skills needed to move from a problem statement to a well-structured computational solution. You will learn to represent problems using appropriate data structures, design algorithms that use those structures effectively, and reason about how choices affect correctness, performance and maintainability. The unit covers recursion, introductory complexity analysis, and structures such as stacks, queues, trees, heaps and hash tables. You will evaluate algorithm behaviour both theoretically and experimentally, building a practical understanding of time, space and trade-offs. Through structured programming activities, you will strengthen your ability to design, implement, test and explain algorithmic solutions. The unit builds disciplined habits of precise reasoning, careful coding, performance awareness and reflection, preparing you for later study in advanced algorithms, software design, artificial intelligence, systems and computational problem solving.
Semester 1, 2026: This unit introduces you to core problem-solving, analytical skills, and methodologies useful for developing flexible, robust, and maintainable software. In doing this, it covers a range of conceptual levels, from fundamental algorithms and data structures, down to their efficient implementation as well as complexity. Topics include data types, data structures, algorithms, algorithmic complexity, recursion, and their practical applications.
| Teaching period | Campus | Mode |
|---|---|---|
| First semester | Clayton | On campus |
| First semester | Malaysia | On campus |
| Second semester | Clayton | On campus |
| Second semester | Malaysia | On campus |
Assessment details may change. Please refer to the assessment information in Moodle closer to the start of the teaching period.
When you finish this unit, you should be able to:
Semester 2: Analyse computational problems to identify suitable algorithmic strategies, data representations and performance considerations.
Semester 1: Translate problem statements into algorithms and implement them in a high level programming language;
Semester 2: Demonstrate understanding of data structures and algorithms by implementing, using, and testing them in ways that support correctness, readability and maintainability.
Semester 1: Determine appropriate basic abstract data types, including; stacks, queues, lists, binary trees, priority queues, heaps and hash tables; for specific contexts;
Semester 2: Design modular algorithmic solutions using appropriate abstract data types, including lists, stacks, queues, trees, heaps and hash tables.
Semester 1: Theoretically and experimentally evaluate different implementations of basic abstract data types;
Semester 2: Demonstrate awareness and working knowledge of relevant tools and technologies, and use them effectively to increase productivity and improve quality, such as IDEs, AI, and Version Control Systems.
Semester 1: Analyse the efficiency of algorithms by determining their best-case and worst-case big-O time complexity;
Semester 2: Plan, monitor, and reflect on the development of your algorithmic thinking and implementation practice through focused problem solving, feedback and iterative improvement.
Semester 2: Communicate algorithmic reasoning and correctness, implementation choices, performance trade-offs and testing evidence using appropriate technical terminology and representations.
This unit has a requirement of 1-2 hours per week of asynchronous learning.
Minimum total expected workload to achieve the learning outcomes for this unit is 144 hours per semester typically comprising a mixture of scheduled online and face to face learning activities and independent study. Independent study may include associated reading and preparation for scheduled teaching activities.
1. Programmer's Field Guide: https://programmers.guide for Learning to Program in C++ 2. Introduction to Algorithms by Thomas Cormen, Charles Leiserson, Ronald Rivest, and Clifford Stein as a reference book. 3. Visualisation of data structures and algorithms covered in the unit: https://www.cs.usfca.edu/~galles/visualization/Algorithms.html
FIT1008 is part of 4 areas of study in the 2026 handbook.
You need (FIT1045 or FIT1053) and (FIT1058 or MAT1830) before you enrol. Enrolment rules also apply.
FIT1008 is a prerequisite or corequisite for 14 units, including FIT2004, FIT2014, FIT2099, FIT2102, FIT2109 and FIT2111. Those lead on to 53 units in all.
In 2026, FIT1008 runs in Semester 1 and Semester 2 at Clayton and Malaysia.
Students who took it rate it hard to do well in and heavy on workload (1 rating). The handbook expects about 144 hours of study across the semester.
No. FIT1008 has 7 assessment tasks and no exam.
FIT1008 is part of Computational science and Computer science.
It is rated 4.0 out of 5 from 1 review. Read the reviews above or add your own.