Baccalauréat international · IB Diploma
Computer Science · HL
Papers, samples and curriculum documents for this course. · Dossiers, échantillons et documents de programme pour ce cours.
Handouts, exercise sheets and slides
Shared topic documents retain their source course and topic titles. Use your chosen board’s specification for coverage, tier and exam requirements.
Handouts · Supports de cours · A-Level Computer Science · Informatique A-Level (20)
- 1. Information representation · 1. Représentation de l'information
- 2. Communication
- 3. Hardware · 3. Matériel
- 4. Processor Fundamentals · 4. Fonctionnement de base du processeur
- 5. System Software · 5. Logiciels système
- 6. Security, privacy and data integrity · 6. Sécurité, confidentialité et intégrité des données
- 7. Ethics and Ownership · 7. Éthique et propriété intellectuelle
- 8. Databases · 8. Bases de données
- 9. Algorithm Design and Problem-solving · 9. Conception d'algorithmes et résolution de problèmes
- 10. Data Types and Structures · 10. Types et structures de données
- 11. Programming · 11. Programmation
- 12. Software Development · 12. Développement logiciel
- 13. Data Representation · 13. Représentation des données
- 14. Communication and internet technologies · 14. Technologies de communication et Internet
- 15. Hardware and Virtual Machines · 15. Matériel et machines virtuelles
- 16. System Software · 16. Logiciels système
- 17. Security · 17. Sécurité
- 18. Artificial Intelligence (AI) · 18. Intelligence artificielle (IA)
- 19. Computational thinking and Problem-solving · 19. Pensée computationnelle et résolution de problèmes
- 20. Further Programming · 20. Programmation avancée
Exercise sheets · Fiches d'exercices · A-Level Computer Science · Informatique A-Level (85)
- 1.1 Data Representation · 1.1 Représentation des données
- 1.1.2 Binary magnitudes, one's complement, subtraction and where BCD and hex are used
- 1.2 Multimedia · 1.2 Multimédia
- 1.2.1 Encoding a picture and a sound: the file header, the drawing list, and sampling
- 1.3 Compression
- 2.1 Networks including the internet · 2.1 Réseaux incluant Internet
- 2.1.1 Network types, client-server and peer-to-peer models, and topologies
- 2.1.2 Cloud computing, transmission media, Ethernet and CSMA/CD, and internet hardware
- 2.1.3 Finding a server: URLs, the Domain Name Service and IP addressing
- 3.1 Computers and their components · 3.1 Ordinateurs et leurs composants
- 3.1.1 Primary memory: RAM, ROM and their types
- 3.1.2 Secondary storage: magnetic, solid state and optical
- 3.1.3 Input and output devices, and buffers
- 3.1.4 Embedded systems, monitoring and control
- 3.2 Logic Gates and Logic Circuits · 3.2 Portes logiques et circuits logiques
- 3.2.1 Truth tables and expressions from a logic circuit
- 3.2.2 Building logic circuits from expressions, problems and truth tables
- 4.1 Central Processing Unit (CPU) Architecture · 4.1 Architecture de l'unité centrale (CPU)
- 4.1.1 Registers, interrupts, ports and performance
- 4.2 Assembly Language · 4.2 Langage assembleur
- 4.3 Bit manipulation · 4.3 Manipulation de bits
- 4.3.1 Arithmetic and cyclic shifts, and when a shift stops being a multiply or a divide
- 5.1 Operating Systems · 5.1 Systèmes d'exploitation
- 5.1.1 Utility software
- 5.1.2 Program libraries and DLL files
- 5.2 Language Translators · 5.2 Traducteurs de langages
- 5.2.1 Partial compilation (Java) and the IDE
- 6.1 Data Security · 6.1 Sécurité des données
- 6.2 Data Integrity · 6.2 Intégrité des données
- 7.1 Ethics and Ownership · 7.1 Éthique et propriété intellectuelle
- 7.1.1 Professional bodies, justifying a software licence, and the impact of AI
- 8.1 Database Concepts · 8.1 Concepts de bases de données
- 8.1.1 Normalising to 3NF, E-R diagrams and the full relational vocabulary
- 8.2 Database Management Systems (DBMS) · 8.2 Systèmes de gestion de bases de données (SGBD)
- 8.3 Data Definition Language (DDL) and Data Manipulation Language (DML) · 8.3 Langage de définition de données (LDD) et langage de manipulation de données (LMD)
- 8.3.1 Joining two tables, aggregates with GROUP BY, and choosing SQL data types
- 9.1 Computational Thinking Skills · 9.1 Compétences de pensée computationnelle
- 9.1.1 Abstraction and decomposition in practice
- 9.2 Algorithms · 9.2 Algorithmes
- 9.2.1 Logic statements and decisions in an algorithm
- 9.2.2 Flowcharts: reading, drawing and converting
- 9.2.3 Structured English, stepwise refinement and describing an algorithm
- 10.1 Data Types and Records · 10.1 Types de données et enregistrements
- 10.2 Arrays · 10.2 Tableaux
- 10.2.1 Bubble sort, array bounds and the standard array routines
- 10.3 Files · 10.3 Fichiers
- 10.4 Introduction to Abstract Data Types (ADT) · 10.4 Introduction aux types de données abstraits (TDA)
- 10.4.1 The circular queue, a linked list in arrays, and choosing the right ADT
- 11.1 Programming Basics · 11.1 Principes de base de la programmation
- 11.1.1 Operators and expressions
- 11.1.2 Built-in functions and library routines
- 11.2 Constructs
- 11.2.1 CASE structures, and choosing between IF and CASE
- 11.2.2 Count-controlled loops: FOR ... NEXT, totals and counts
- 11.2.3 WHILE and REPEAT loops, and choosing the right loop
- 11.2.4 Trace tables: dry-running an algorithm and finding logic errors
- 11.3 Structured Programming · 11.3 Programmation structurée
- 11.3.1 Functions, and choosing between a procedure and a function
- 11.3.2 Parameters by value and by reference, and variable scope
- 11.3.3 Efficient pseudocode and breaking a task into modules
- 12.1 Program Development Life cycle · 12.1 Cycle de vie du développement de programmes
- 12.2 Program Design · 12.2 Conception de programme
- 12.3 Program Testing and Maintenance · 12.3 Tests et maintenance de programmes
- 12.3.1 Test strategy, test plans and choosing a testing method
- 13.1 User-defined data types · 13.1 Types de données définis par l'utilisateur
- 13.1.1 Designing a user-defined type for a problem, and the linked list
- 13.2 File organisation and access · 13.2 Organisation et accès aux fichiers
- 13.3 Floating-point numbers, representation and manipulation · 13.3 Nombres à virgule flottante, représentation et manipulation
- 13.3.1 The mantissa-exponent trade-off, normalisation, and overflow and underflow
- 14.1 Protocols · 14.1 Protocoles
- 14.2 Circuit switching, packet switching · 14.2 Commutation de circuits, commutation par paquets
- 15.1 Processors, Parallel Processing and Virtual Machines · 15.1 Processeurs, traitement parallèle et machines virtuelles
- 15.2 Boolean Algebra and Logic Circuits · 15.2 Algèbre de Boole et circuits logiques
- 15.2.1 The full adder, flip-flops drawn and traced, and four-variable Karnaugh maps
- 16.1 Purposes of an Operating System (OS) · 16.1 Rôles d'un système d'exploitation (OS)
- 16.2 Translation Software · 16.2 Logiciels de traduction
- 16.2.1 Recursive BNF, syntax diagrams, and RPN in both directions
- 17.1 Encryption, Encryption Protocols and Digital Certificates · 17.1 Cryptographie, protocoles de cryptographie et certificats numériques
- 18.1 Artificial Intelligence (AI) · 18.1 Intelligence artificielle (IA)
- 19.1 Algorithms · 19.1 Algorithmes
- 19.1.1 ADT algorithms - linked lists, binary trees, graphs, and Big O
- 19.2 Recursion · 19.2 Récursivité
- 20.1 Programming Paradigms · 20.1 Paradigmes de programmation
- 20.1.1 The five addressing modes, and declarative programming with facts, rules and goals
- 20.2 File Processing and Exception Handling · 20.2 Traitement de fichiers et gestion des exceptions
Presentation slides · Diaporamas de présentation · A-Level Computer Science · Informatique A-Level (20)
- 1. Information representation · 1. Représentation de l'information
- 2. Communication
- 3. Hardware · 3. Matériel
- 4. Processor Fundamentals · 4. Fonctionnement de base du processeur
- 5. System Software · 5. Logiciels système
- 6. Security, privacy and data integrity · 6. Sécurité, confidentialité et intégrité des données
- 7. Ethics and Ownership · 7. Éthique et propriété intellectuelle
- 8. Databases · 8. Bases de données
- 9. Algorithm Design and Problem-solving · 9. Conception d'algorithmes et résolution de problèmes
- 10. Data Types and Structures · 10. Types et structures de données
- 11. Programming · 11. Programmation
- 12. Software Development · 12. Développement logiciel
- 13. Data Representation · 13. Représentation des données
- 14. Communication and internet technologies · 14. Technologies de communication et Internet
- 15. Hardware and Virtual Machines · 15. Matériel et machines virtuelles
- 16. System Software · 16. Logiciels système
- 17. Security · 17. Sécurité
- 18. Artificial Intelligence (AI) · 18. Intelligence artificielle (IA)
- 19. Computational thinking and Problem-solving · 19. Pensée computationnelle et résolution de problèmes
- 20. Further Programming · 20. Programmation avancée
Course units and learning goals · Unités de cours et objectifs d'apprentissage
These lessons teach selected course objectives. Check the remaining coverage gaps; the material is not a complete preparation programme. · Ces leçons abordent des objectifs de cours sélectionnés. Vérifiez les lacunes restantes en couverture ; ce matériel ne constitue pas un programme d'entraînement complet.
A.1 · Computer fundamentals
- Checking an asserted identity.
- Separate authentication from authorization. Authentication checks identity; authorization determines permitted actions. A threat model connects a valuable asset, a possible attack and an appropriate control.
- Use a fictitious school dataset to define users and permissions. Draw data flows, compare validation and verification, and specify tests for normal, boundary and invalid input. Do not use real credentials or student records in exercises.
- authentication
- Checking an asserted identity
- authorization
- Determining permitted actions
A.2 · Networks
- Achieved rate of useful data transfer.
- Transmission time depends on data size and rate. Total delay may also include propagation, processing and queueing. Encryption protects content under its assumptions but does not remove congestion or every metadata exposure.
- Trace a message route using a documented local model. Record payload size, units and measured time. Use school-approved networks and synthetic messages; do not scan or intercept another user traffic.
- throughput
- Achieved rate of useful data transfer
- latency
- Delay experienced in communication
A.3 · Databases
- Attribute set uniquely identifying a table row.
- A join combines rows according to a specified condition. The result count depends on relationship cardinality and filters. A foreign key constraint enforces a relationship rule; it does not automatically encrypt personal data.
- Design a small synthetic user-order dataset with no real personal information. Declare keys, test duplicate and missing-reference inserts, then check a query result against a hand-worked expected table.
- primary key
- Attribute set uniquely identifying a table row
- foreign key
- Attribute set referencing a key in another table
A.4 · Machine learning
- An attribute set uniquely identifying a record.
- A primary key uniquely identifies a record; a foreign key relates records. In prediction, leakage can expose information unavailable at the real decision time. Accuracy alone may hide an unbalanced target distribution.
- Use fictional booking records to identify entities, attributes and relationships. For a learning exercise, use a public non-sensitive dataset, separate training and test data, and describe who may be affected by errors. The current 2027 CS objective scope awaits the acquired guide.
- primary key
- An attribute set uniquely identifying a record
- data leakage
- Use of information unavailable at the intended prediction time
B.1 · Computational thinking
- A finite procedure solving a stated task.
- State input conditions and expected outputs. Use boundary cases, empty collections where allowed, duplicates and invalid values. Distinguish a wrong algorithm from a wrong implementation or an incomplete requirement.
- Trace a search over a small fictional sorted list. State the indexing convention. For binary search, update bounds so the remaining interval shrinks and reject unsorted input unless sorting is part of the task.
- algorithm
- A finite procedure solving a stated task
- boundary test
- A test at a limit of the allowed input range
B.2 · Programming
- A finite procedure solving a stated task.
- State input conditions and expected outputs. Use boundary cases, empty collections where allowed, duplicates and invalid values. Distinguish a wrong algorithm from a wrong implementation or an incomplete requirement.
- Trace a search over a small fictional sorted list. State the indexing convention. For binary search, update bounds so the remaining interval shrinks and reject unsorted input unless sorting is part of the task.
- algorithm
- A finite procedure solving a stated task
- boundary test
- A test at a limit of the allowed input range
B.3 · Object-oriented programming
- Controlling access to state through an interface.
- A method call acts on a particular instance. State changes should satisfy preconditions and postconditions. Polymorphism lets code use a common interface with different implementations when the contract is respected.
- Implement a small synthetic account or inventory model. Test two independent instances, rejected invalid operations and boundary values. Keep the model away from real financial accounts and credentials.
- encapsulation
- Controlling access to state through an interface
- instance
- An individual object of a class
B.4 · Abstract data types (HL only)
- A last-in-first-out abstract data type.
- Choose the structure for the required access pattern. Complexity depends on implementation and assumptions: removing the first item from a shifting array differs from advancing a head pointer in a queue.
- Trace operation sequences by hand, then compare a program with the expected states. Test empty, singleton and repeated operations. State overflow behaviour if capacity is fixed.
- stack · pile
- A last-in-first-out abstract data type
- queue · file d'attente
- A first-in-first-out abstract data type
Case study · Case study
- Completed work per unit time under a stated workload.
- A recommendation should connect a requirement to a mechanism and an observable test. For example, a concurrency problem requires a strategy that prevents conflicting updates, plus tests demonstrating the invariant. A claim about faster response requires comparable workload measurements rather than only a complexity label. Evaluate alternatives under the same stated conditions.
- Use an original school-approved scenario and synthetic data. Build a matrix of claim, supporting scenario evidence, technical explanation, limitation and acceptance test. Mark missing facts explicitly and show how the recommendation would change if an assumption failed. This prepares case-based reasoning without reproducing an unavailable IB assessment case study or inventing its examination rubric.
- throughput
- Completed work per unit time under a stated workload
- acceptance test
- A test of whether a specified user requirement is met
IA · Computational solution
- A finite procedure solving a stated task.
- State input conditions and expected outputs. Use boundary cases, empty collections where allowed, duplicates and invalid values. Distinguish a wrong algorithm from a wrong implementation or an incomplete requirement.
- Trace a search over a small fictional sorted list. State the indexing convention. For binary search, update bounds so the remaining interval shrinks and reject unsorted input unless sorting is part of the task.
- algorithm
- A finite procedure solving a stated task
- boundary test
- A test at a limit of the allowed input range
Preparing for this qualification · Préparation à cette qualification
- This ordering records the 2027 A/B structure separately from the 2014 course final assessment in 2026.
- Do not carry forward old Options A–D or the old assessment weights. A.4 machine learning and B.3 OOP are in the new public structure; B.4 is HL-only.
- Current paper marks, case-study assessment differences, approved language conventions and IA rubric remain blocked pending the current guide.
- The project is a school-supervised working computational solution with requirements, tests and user evaluation, never an invented written replacement.
Teaching coverage still needed · Couverture pédagogique encore nécessaire
- 2027 exact objectives/rubrics not verified from an acquired guide. These original foundation cases do not establish full current-course parity.
Specifications and sample documents · Spécifications et documents d'échantillon
Course materials · Matériel pédagogique
- Study notes · Notes de cours →
- Revision questions · Questions de révision →
- Teaching guidance · Guide pédagogique · Teacher access · Accès enseignant →
- Teacher diagnostics · Diagnostique enseignant · Teacher access · Accès enseignant →
- Supervised task guidance · Guide pour la tâche supervisée · Teacher access · Accès enseignant →
Course preparation · Préparation du cours
Documents are available. Board-specific notes, assessments and interactive past-paper practice are not yet available for every course. · Les documents sont disponibles. Les notes spécifiques au conseil, les évaluations et la pratique interactive des anciens sujets ne sont pas encore disponibles pour tous les cours.
Lessons · Leçons →