B2 Programming

For the new IB Diploma Computer Science syllabus to start teaching in August 2025, and for first examinations in May 2027.

Unit and lesson overviews will be gradually published as developed.

Lesson 1: Hello world

Lesson 2: Numeric types & operations

B2.1.1 Construct and trace programs using a range of global and local variables of various data types.

  • Data types: Boolean value, char, decimal, integer, string

Lesson 3: String types & operations

B2.1.2 Construct programs that can extract and manipulate substrings.

  • Writing of programs that accurately identify and extract substrings from given strings, demonstrating the ability to perform various manipulations, such as altering, concatenating or replacing

Lesson 4: Exception handling & debugging techniques

B2.1.3 Describe how programs use common exception handling techniques.

  • Potential points of failure in a program must include unexpected inputs, resource unavailability, logic errors.
  • The role of exception handling in developing programs
  • Exception handling constructs that effectively manage errors must include try/catch in Java, and try/except in Python, along with the finally block.

B2.1.4 Construct and use common debugging techniques.

  • Debugging techniques may include trace tables, breakpoint debugging, print statements and step-by- step code execution.

Lesson 5,6: Static & dynamic structures; Arrays & lists

B2.2.1 Compare static and dynamic data structures.

  • The fundamental differences between static and dynamic data structures, including their underlying mechanisms for memory allocation and resizing
  • The advantages and disadvantages of each type in various scenarios, considering factors such as speed, memory usage, flexibility

B2.2.2 Construct programs that apply arrays and Lists.

  • One-dimensional (1D) arrays, two-dimensional (2D) arrays, ArrayLists in Java
  • One-dimensional (1D) Lists and two-dimensional (2D) Lists in Python
  • Add, remove and traverse elements in a dynamic list

Lesson 7: Stacks

B2.2.3 Explain the concept of a stack as a “last in, first out” (LIFO) data structure.

  • Must include fundamental operations such as push, pop, peek and isEmpty
  • How stack operations impact both performance and memory usage
  • An appropriate stack for a specific problem

Lesson 8: Queues

B2.2.4 Explain the concept of a queue as a “first in, first out” (FIFO) data structure.

  • Must include fundamental operations such as enqueue, dequeue, front and isEmpty
  • How queue operations impact both performance and memory usage
  • An appropriate queue for a specific problem

Lesson 9: Sequence & selection

B2.3.1 Construct programs that implement the correct sequence of code instructions to meet program objectives.

  • The impact of instruction order on program functionality
  • Ways to avoid errors, such as infinite loops, deadlock, incorrect output

B2.3.2 Construct programs utilizing appropriate selection structures.

  • Must include: if, else, else if (Java), elif (Python), to execute different code blocks based on specified conditions
  • Selection structures with or without Boolean operators (AND, OR, NOT) and/or relational operators (<, <=, >, >=, ==, !=) to control program flow effectively

Lesson 10,11: Iteration

B2.3.3 Construct programs that utilize looping structures to perform repeated actions.

  • Types of loops, including counted loops and conditional loops, and appropriate use of each type
  • Conditional statements within loops, using Boolean and/or relational operators to govern the loop’s execution

Lesson 12: Functions & modularisation

B2.3.4 Construct functions and modularization.

  • Functions to define reusable blocks of code with different inputs
  • Modularization to create well-structured, reusable and maintainable code
  • The principles of scope (local versus global)
  • The benefits of code modularization, applying this concept to various programming scenarios

Lesson 13: Big O

B2.4.1 Describe the efficiency of specific algorithms by calculating their Big O notation to analyse their scalability.

  • The time and space complexities of algorithms and calculating Big O notation
  • Algorithm choice based on scalability and efficiency requirements

Lesson 14,15: Search algorithms

B2.4.2 Construct and trace algorithms to implement a linear search and a binary search for data retrieval.

  • The differences in efficiency between different methods of linear and binary search
  • Use of search technique based on efficiency requirements—for example, searching a database for a sorted/indexed list of names to find a phone number, versus searching by the number to identify the name

Lesson 16,17: Sort algorithms

B2.4.3 Construct and trace algorithms to implement bubble sort and selection sort, evaluating their time and space complexities.

  • The time and space complexities of each algorithm, denoted by their respective Big O notations
  • The advantages and disadvantages of each algorithm in terms of efficiency across various data sets

Lesson 18,19,20: Recursion (HL)

B2.4.4 Explain the fundamental concept of recursion and its applications in programming. (HL only)

  • The fundamentals of recursion and its advantages and limitations
  • The utility of recursion in solving problems that can be broken down into smaller, similar sub-problems
  • Recursive algorithms, including but not limited to quicksort
  • The limitations of recursion, including complexity and memory usage
  • Situations that best suit the use of recursion, including fractal image creation, traversing binary trees, sorting algorithms

B2.4.5 Construct and trace recursive algorithms in a programming language. (HL only)

  • Simple, non-branching recursive algorithms in programming only

Lesson 21: File processing

B2.5.1 Construct code to perform file-processing operations.

  • Programs that manipulate text files
  • Opening a sequential file in various modes (read, write, append)
  • How to read from and write to files, append data to an existing file, and close a file once operations are completed
  • Classes for Java users may include Scanner, FileWriter, BufferedReader.
  • Functions for Python users may include open(), read(), readline(), write(), close().

Lesson 22,23,24,25,26,27: Programming scenarios

Lesson 28,29: Review

Lesson 30: Assessment

Copyright © Paul Baumgarten.