Computer Science

E2E stub topic

This subtopic focuses on end-to-end (E2E) testing as a software testing methodology that validates the complete flow of an application from start to finish, ensuring all integrated components function correctly under real-world scenarios. It examines the practical application of designing E2E test cases, selecting appropriate tools, and analyzing test outcomes to guarantee system reliability and user satisfaction. Mastery of E2E testing is crucial for identifying system-wide issues that unit or integration testing may overlook, thereby supporting robust software development life cycles.

E2E stub subtopic

The characteristics of contemporary processors, input, output and storage devices

This topic covers the internal architecture of contemporary processors, including the roles of the ALU, Control Unit, and registers within the Fetch-Decode-Execute cycle. It also examines factors influencing CPU performance, different processor architectures (Von Neumann, Harvard, CISC, RISC), and the application of various input, output, and storage devices.

Structure and function of the processor

This topic covers the fundamental architecture and internal operations of the Central Processing Unit (CPU). It examines the roles of specific registers, the function of the Arithmetic and Logic Unit (ALU) and Control Unit, and the mechanics of the Fetch-Decode-Execute cycle, including how these relate to assembly language and processor performance.

Types of processor

This topic explores the architectural differences between CISC and RISC processors, highlighting their distinct design philosophies and typical use cases. It also covers the role of GPUs beyond graphics processing and the principles of multicore and parallel processing systems.

Input, output and storage

This topic covers the application of various input, output, and storage devices to solve specific computational problems. It includes the functional differences and appropriate use cases for magnetic, flash, and optical storage, as well as the distinction between RAM and ROM and the concept of virtual storage.

Software and software development

This topic covers the classification and purpose of systems and application software, including operating system functions like memory management and scheduling. It also explores software development methodologies, such as waterfall and agile, and the characteristics of various programming paradigms including procedural and object-oriented languages.

Systems Software

This topic covers the fundamental role of systems software in managing computer hardware and providing a platform for application software. It explores the core functions of operating systems, including memory management, scheduling, and the handling of interrupts, alongside the roles of BIOS, device drivers, and virtual machines.

Applications Generation

This topic covers the nature of applications and the software development process, focusing on how applications are generated and maintained. It includes the study of utilities, the distinction between open and closed source software, and the role of translators such as interpreters, compilers, and assemblers in the compilation process.

Software Development

This topic covers the methodologies and lifecycle models used in software development, including waterfall, agile, extreme programming, the spiral model, and rapid application development. It requires an understanding of the relative merits, drawbacks, and appropriate application contexts for each methodology, alongside the practical skill of writing and following algorithms.

Types of Programming Language

This topic explores the diverse landscape of programming languages, focusing on the characteristics of various paradigms and their practical application. It specifically covers procedural and object-oriented languages, alongside assembly language, including memory addressing modes and the use of the Little Man Computer (LMC) instruction set.

Exchanging data

This topic explores the mechanisms and protocols used for exchanging data between different computer systems. It covers the technical aspects of data compression, encryption, database management, network architecture, and web technologies.

Compression, Encryption and Hashing

This topic covers the fundamental techniques used for data management and security in computer systems. It explores the principles of data compression, the mechanisms of symmetric and asymmetric encryption, and the role of hashing in data integrity.

Databases

This topic covers the fundamental principles of relational databases, including entity-relationship modelling, normalisation to 3NF, and the use of primary, foreign, and secondary keys. It also explores methods for data management, transaction processing (ACID properties), and the interpretation and modification of SQL queries.

Networks

This topic covers the fundamental characteristics of computer networks, including the importance of protocols and standards. It explores the structure of the internet, network hardware, and the differences between client-server and peer-to-peer models, alongside essential network security measures.

Web Technologies

This topic covers the fundamental technologies that underpin the World Wide Web, focusing on the roles of HTML, CSS, and JavaScript in web development. It also examines the mechanisms behind search engine functionality, specifically indexing and the PageRank algorithm, alongside the distinction between server-side and client-side processing.

Data types, data structures and algorithms

This topic covers the representation and storage of data using various primitive types and complex structures, alongside the algorithms used to manipulate them. It also encompasses Boolean algebra, including logic gates, truth tables, and the simplification of expressions using Karnaugh maps and algebraic laws.

Data Types

This topic covers the fundamental representation and storage of data within computer systems, including primitive data types and binary arithmetic. It explores how integers, real numbers, and characters are represented, manipulated, and converted between different bases, alongside the use of bitwise operations and character sets.

Data Structures

This topic covers the representation and storage of data within various structures, including arrays, records, lists, tuples, linked-lists, graphs, stacks, queues, trees, and hash tables. It requires an understanding of how to create, traverse, add, and remove data from these structures using either procedural or object-oriented programming approaches.

Boolean Algebra

This topic covers the application of Boolean logic to define and solve computational problems. It includes the manipulation of Boolean expressions using algebraic rules and Karnaugh maps, as well as the use of truth tables and logic gate diagrams to represent and simplify logic circuits.

Legal, moral, cultural and ethical issues

This topic explores the individual moral, social, ethical, and cultural opportunities and risks associated with digital technology. It covers key UK legislation governing computer use and examines the ethical implications of modern computing developments such as artificial intelligence and automated decision-making.

Computing related legislation

This topic covers the essential legal framework governing the use of computers and digital technology in the UK. It requires an understanding of specific legislation, including the Data Protection Act 1998, the Computer Misuse Act 1990, the Copyright Design and Patents Act 1988, and the Regulation of Investigatory Powers Act 2000.

Moral and ethical Issues

This topic explores the moral, social, ethical, and cultural implications of digital technology in modern society. It requires students to evaluate the opportunities and risks associated with computing, including legislation, automated decision-making, and the impact of technology on the workforce and environment.

Elements of computational thinking

This topic focuses on the fundamental principles of computational thinking, which are essential for problem-solving in computer science. It covers the application of abstraction, procedural thinking, logical reasoning, and concurrent processing to analyze and model real-world problems effectively.

Thinking abstractly

This topic explores the nature and necessity of abstraction as a fundamental principle of computational thinking. It requires learners to understand the differences between abstract models and reality, and to demonstrate the ability to devise abstract models for a variety of real-world situations.

Thinking ahead

Thinking ahead involves the strategic identification of inputs, outputs, and necessary preconditions before commencing a computational solution. It also encompasses the evaluation of caching mechanisms and the requirement for creating reusable program components to enhance efficiency and maintainability.

Thinking procedurally

Thinking procedurally involves the systematic breakdown of a problem into its constituent components and the identification of the necessary steps to reach a solution. This process requires the determination of the logical order of operations and the identification of sub-procedures essential for solving complex computational problems.

Thinking logically

Thinking logically involves identifying the specific points within a computational solution where a decision must be made. It requires determining the logical conditions that influence these decisions and understanding how those decisions subsequently affect the flow of execution through a program.

Thinking concurrently

Thinking concurrently involves identifying parts of a problem that can be solved simultaneously to improve efficiency. Learners must be able to outline the potential benefits and trade-offs associated with concurrent processing in specific scenarios.

Problem solving and programming

This topic focuses on the practical application of computational thinking to solve problems through programming. It covers essential programming techniques, computational methods, and the use of algorithms to describe and solve problems, requiring learners to demonstrate proficiency in both procedural and object-oriented paradigms.

Programming techniques

This topic covers the fundamental programming techniques required to develop software solutions, including control structures, modularity, and object-oriented programming. It emphasizes the use of recursion, variable scope, and integrated development environments (IDEs) to create efficient and maintainable code.

Computational methods

This topic focuses on the computational methods used to solve problems, emphasizing the identification of features that make a problem solvable by computational means. It covers key techniques such as problem recognition, decomposition, divide and conquer, and abstraction, alongside advanced methods like backtracking, data mining, heuristics, performance modelling, pipelining, and visualisation.

Algorithms

This topic covers the analysis, design, and implementation of algorithms to solve computational problems. It focuses on evaluating algorithm efficiency using Big O notation and understanding standard algorithms for searching, sorting, and data structure traversal.

Analysis of the problem

This topic focuses on the initial phase of the non-exam assessment (NEA) programming project, requiring learners to identify and justify a problem suitable for a computational solution. It involves researching the problem, identifying stakeholders, and specifying measurable success criteria and requirements for the proposed system.

Problem identification

Problem identification is the initial stage of the non-exam assessment (NEA) where learners must justify why their chosen project is suitable for a computational solution. This involves describing the problem's features, explaining its amenability to a computational approach, and identifying the stakeholders who will benefit from the final system.

Stakeholders

This topic focuses on the identification and analysis of stakeholders within the context of a software development project. Learners must identify individuals, groups, or personas interested in the solution and explain how the proposed system meets their specific needs.

Research the problem

This topic focuses on the research phase of the Programming Project (Component 03/04), requiring learners to investigate their chosen problem and existing solutions. Learners must identify and justify suitable approaches, explain the essential features of their proposed computational solution, and articulate the limitations of their design.

Specify the proposed solution

This topic focuses on the formal specification of a proposed computational solution within the Programming Project (Component 03/04). Learners must define and justify the technical requirements, including hardware and software configurations, and establish measurable success criteria to evaluate the final product.

Design of the solution

The design phase of the programming project requires learners to systematically decompose a problem into smaller, manageable components suitable for computational solutions. This stage involves defining the overall structure, selecting appropriate algorithms, identifying key data structures and variables, and planning a robust testing strategy to ensure the final product meets the specified success criteria.

Decompose the problem

Decomposition is a fundamental computational thinking skill that involves breaking down a complex problem into smaller, more manageable sub-problems. This process allows for the systematic analysis and solution of each component, which can then be integrated to form a complete, effective solution to the original problem.

Describe the solution

This topic focuses on the design phase of the non-exam assessment (NEA) programming project. Learners must explain and justify the structure of their solution, describe the logic using algorithms, identify usability features, and specify key data structures and variables.

Describe the approach to testing

This topic focuses on the systematic approach to testing within the Programming project (Component 03/04). It requires learners to identify and justify the test data used during both the iterative development and post-development phases to ensure the solution is robust and meets success criteria.

Developing the solution

This topic focuses on the practical implementation of a programming project, requiring learners to apply computational thinking to solve a user-driven problem. It encompasses the iterative development process, including prototyping, testing, and refining code, while ensuring the solution is well-structured, modular, and appropriately documented.

Iterative development process

The iterative development process is a core component of the non-exam assessment (NEA) programming project, requiring learners to provide annotated evidence of each stage of development. This approach involves creating and refining prototype solutions, justifying design and implementation decisions, and using testing to inform and improve the development cycle.

Testing to inform development

This topic focuses on the iterative development process within the Programming Project (Component 03/04). It requires learners to provide annotated evidence of each stage of development, including prototypes and testing, to justify their design and implementation decisions.

Evaluation

Evaluation is a critical component of the non-exam assessment (NEA) where learners assess the success of their developed solution. This involves testing for robustness and usability, cross-referencing outcomes against original success criteria, and discussing maintenance and potential future developments.

Testing to inform evaluation

This topic focuses on the evaluation phase of the programming project, requiring learners to provide annotated evidence of robustness and usability testing. It involves evaluating the final solution against success criteria established during the analysis phase and discussing future maintenance and development.

Success of the solution

This topic focuses on the final evaluation phase of the programming project, where learners assess the success of their developed solution. It requires the use of test evidence from both development and post-development stages to evaluate the solution against the success criteria established during the analysis phase.

Describe the final product

This topic focuses on the final stage of the non-exam assessment (NEA) programming project, where learners must provide annotated evidence of the usability features identified during the design phase. Learners are required to comment on the effectiveness of these features and demonstrate how the final product meets the needs of the user.

Maintenance and development

This topic focuses on the final stage of the programming project, requiring learners to evaluate their completed solution and consider its long-term viability. Learners must discuss the maintainability of their code and propose potential future developments to address limitations or enhance functionality.