IB Computer Science: the syllabus, the IA solution and exam papers
A guide to IB Computer Science: the core topics, HL extensions, the exam papers including the HL case study, and the Internal Assessment computational solution.
IB Computer Science is a group 4 subject that combines computational thinking with practical programming. Its marks reward the ability to design, build and evaluate solutions and to reason precisely about algorithms — not just to memorise syntax. Success in the Diploma Programme comes from combining strong fundamentals with a well-scoped IA. For one-to-one support see IB Computer Science tutoring.
Syllabus structure
The core covers system fundamentals, computer organisation, networks, and computational thinking, problem-solving and programming. HL adds further depth — including abstract data structures (linked lists, stacks, queues, trees), object-oriented programming, resource management and control — plus an annually released case study on a set topic.
HL vs SL
HL and SL share the core; HL studies the additional higher-level topics and sits an extra paper on the case study. HL therefore demands both broader theory and deeper algorithmic and OOP understanding. Programming is typically taught in Java, though the IA can use another suitable language.
The exam papers
- Paper 1: theory and problem-solving across the core (and, for HL, the additional topics), including pseudocode, tracing and algorithm design.
- Paper 2: focused on options / OOP content at HL.
- Paper 3 (HL): based on the pre-released case study, requiring applied analysis of a specific scenario.
The Internal Assessment
The IA is a computational solution: a working program built for a real client or problem, documented across planning, design, development, testing and evaluation. The most common weakness is an over-ambitious scope; a focused solution, fully documented against the criteria, scores better than a large unfinished one.
How to score well
- Master pseudocode and tracing: Paper 1 rewards precise algorithm reasoning, not just working code.
- Scope the IA tightly: a smaller, complete, well-tested solution beats an ambitious half-built one.
- Prepare the case study early: for HL Paper 3, build vocabulary and background on the released topic well before the exam.
- Practise OOP deliberately: encapsulation, inheritance and polymorphism recur across HL papers and the IA.