Program Design and Fundamental Constructs

Apply systematic problem-solving techniques, decomposition, and pattern recognition to analyse computational problems.

Understand and apply different types of abstraction to model real-world systems and manage complexity in programming.

Apply software design principles like top-down design and information hiding, and evaluate the theoretical limits of computation.

Understand how to gather requirements, write program specifications, and implement basic programming constructs using variables, input/output, and operators.

Implement selection, iteration, and nested control structures to manage program flow, and manipulate strings to process text-based data.

Design and implement modular programs using procedures, functions, parameters, and appropriate scoping, documented with clear interface specifications.

Apply core object-oriented programming principles, write recursive algorithms, and compare different programming paradigms.

Trace, test, and debug programs systematically, argue for their correctness and efficiency, and deliver complete, user-tested programming solutions.

Understand the denary and binary number systems, convert between them, and perform binary arithmetic including operations with signed numbers using two's complement.

Understand the hexadecimal number system, convert between hexadecimal and other bases, identify practical uses in computing, and represent decimal digits using BCD.

Explain how characters, images, and sound are encoded in binary, calculate file sizes, and apply compression techniques including RLE and Huffman coding.

Represent real numbers in binary floating-point format and apply mathematical concepts including set theory, matrices, modular arithmetic, and sequences to computing problems.

Understand the fundamentals of Boolean logic and apply algebraic laws and Karnaugh maps to simplify Boolean expressions.

Design and analyze digital logic circuits using logic gates, adders, and flip-flops, and solve A-Level exam-style problems.

Understand algorithmic complexity using Big O notation and analyze the time and space complexity of algorithms across different cases.

Implement and analyze standard searching and sorting algorithms, and evaluate the complexity of recursive versus iterative approaches.

Implement graph traversal and pathfinding algorithms, and apply advanced algorithmic paradigms like greedy algorithms and dynamic programming.

Implement fundamental linear data structures including arrays, dynamic lists, stacks, and queues, understanding their operations and array-based implementations.

Implement linked lists, binary trees, binary search trees, and hash tables, understanding node-based storage and hashing techniques.

Represent graphs using adjacency matrices and lists, and evaluate and compare data structures to select the most appropriate one for a given problem.