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Component 01 - Computing Principles | AS-Level (H046) | A-Level (H446) | 1 The characteristics of contemporary processors, input, output and storage devices | Structure and function of the processor | The Arithmetic and Logic Unit (ALU), Control Unit and registers: Program Counter (PC), Accumulator (ACC), Memory Address Register (MAR), Memory Data Register (MDR), Current Instruction Register (CIR).Buses: data, address and control: How this relates to assembly language programs.The fetch-decode-execute cycle, including its effect on registers.The factors affecting the performance of the CPU, clock speed, number of cores, cache.Von Neumann, Harvard and contemporary processor architecture. | The use of pipelining in a processor to improve efficiency. | Types of processor | The differences between, and uses of, CISC and RISC processors.Multicore and parallel systems. | GPUs and their uses (including those not related to graphics). | Input, output and storage | How different input output and storage devices can be applied as a solution of different problems.The uses of magnetic, flash and optical storage devices.RAM and ROM.Virtual storage. | |

2 Software and software development | Operating systems | The need for, function and purpose of operating systems.Memory management (paging, segmentation and virtual memory).Interrupts, the role of interrupts and Interrupt Service Routines (ISR), role within the fetch decode execute cycle.Scheduling: round robin, first come first served, multi-level feedback queues, shortest job first and shortest remaining time.Distributed, embedded, multi-tasking, multiuser and real time operating systems.BIOS.Device drivers.Virtual machines, any instance where software is used to take on the function of a machine including executing intermediate code or running an operating system withinanother. | |

Applications generation | The nature of applications, justifying suitable applications for a specific purpose.Utilities.Open source vs closed source.Translators: interpreters, compilers and assemblers. | Stages of compilation (lexical analysis, syntax analysis, code generation and optimisation).Linkers and loaders and use of libraries. | Introduction to programming & Types of programming language | Procedural programming language techniques: * program flow * variables and constants * procedures and functions * arithmetic, Boolean and assignment * operators * string handling * file handling.Assembly language (including following and writing simple programs with Little Man Computer). | Need for and characteristics of a variety of programming paradigms.Procedural languages.Modes of addressing memory (immediate, direct, indirect and indexed).Object-oriented languages with an understanding of classes, objects, methods, attributes, inheritance, encapsulation and polymorphism. |

3 Exchanging data | Compression, Encryption and Hashing | | Lossy vs Lossless compression.Run length encoding and dictionary coding for lossless compression.Symmetric and asymmetric encryption.Different uses of hashing. | Databases | Relational database, flat file, primary key, foreign key, secondary key, entity relationship modeling.Methods for capturing, selecting, managing and exchanging data. | Normalisation and indexing.Normalisation to 3NF.SQL – Interpret and modify.Referential integrity.Transaction processing, ACID (Atomicity, Consistency, Isolation, Durability), record locking and redundancy. | Networking | Characteristics of networks and the importance of protocols and standards.Internet structure: * The TCP/IP Stack. * DNS * Protocol layering. * LANs and WANs. * Packet and circuit switching.Client-server and peer to peer. | Network security and threats, use of firewalls, proxies and encryption.Network hardware. | Web technologies | HTML, CSS and JavaScript.Lossy v lossless compression. | Search engine indexing.PageRank algorithm.Server and client side processing. | 4 Data types, data structures and algorithms | Data types | Primitive data types, integer, real/floating point, character, string and Boolean.Represent positive integers in binary.Use of sign and magnitude and two’s complement to represent negative numbers in binary.Addition and subtraction of binary integers.Represent positive integers in hexadecimal.Convert positive integers between binary, hexadecimal and denary.Positive and negative real numbers using normalised floating point representation.How character sets (ASCII and UNICODE) are used to represent text. | Floating point addition and subtraction.Bitwise manipulation and masks: shifts, combining with AND, OR, and XOR. | Data structures | Arrays (of up to 3 dimensions), records, lists, tuples.The properties of stacks and queues. | The following structures to store data: linked-list, graph (directed and undirected), stack, queue, tree, binary search tree, hash table.How to create, traverse, add data to and remove data from the data structures mentioned above. (NB: this can be either using arrays and procedural programming or an object-oriented approach). | Boolean algebra | Define problems using Boolean logic.Manipulate Boolean expressions, including the use of Karnaugh maps to simplify Boolean expressions.Use logic gate diagrams and truth tables. | Use the following rules to derive or simplify statements in Boolean algebra: De Morgan’s Laws, distribution, association, commutation, double negation.The logic associated with D type flip flops, half and full adders. | 5 Legal, moral, cultural and ethical issues | Computing related legislation | The Data Protection Act 1998.The Computer Misuse Act 1990.The Copyright Design and Patents Act 1988.The Regulation of Investigatory Powers Act 2000. | | Ethical, moral and cultural issues | The individual (moral), social, ethical and cultural opportunities and risks of digital technology: * Computers in the workforce * Automated decision making * Artificial intelligence * Environmental effects * Censorship and the Internet * Monitor behavior * Analyse personal information * Piracy and offensive communications * Layout, colour paradigms and character sets. | |

Component 02 – Algorithms and programming | AS (H046) | A-Level (H446) | 1 Elements of computational thinking | Thinking abstractly | The nature of abstraction.The need for abstraction.The differences between an abstraction and reality.Devise an abstract model for a variety of situations. | | Thinking ahead | Identify the inputs and outputs for a given situation.Determine the preconditions for devising a solution to a problem.The need for reusable program components. | The nature, benefits and drawbacks of caching. | Thinking procedurally | Identify the components of a problem.Identify the components of a solution to a problem.Determine the order of the steps needed tosolve a problem.Identify sub-procedures necessary to solve aproblem. | | Thinking logically | Identify the points in a solution where adecision has to be taken.Determine the logical conditions that affectthe outcome of a decision.Determine how decisions affect flow througha program. | | Thinking concurrently | | Determine the parts of a problem that can be tackled at the same time.Outline the benefits and trade offs that might result from concurrent processing in a particular situation. | 2 Problem solving and programming | Programming techniques | Programming constructs: sequence, iteration, branching.Global and local variables.Modularity, functions and procedures, parameter passing by value and reference.Use of an IDE to develop/debug a program. | Recursion, how it can be used and compares to an iterative approach.Use of object oriented techniques. | Software development | Understand the waterfall lifecycle, agile methodologies, extreme programming, the spiral model and rapid application development.The relative merits and drawbacks of different methodologies and when they might be used.Writing and following algorithms.Different test strategies, including black and white box testing and alpha and beta testing.Test programs that solve problems using suitable test data and end user feedback, justify a test strategy for a given situation. | |

Computational methods | | Features that make a problem solvable by computational methods.Problem recognition.Problem decomposition.Use of divide and conquer.Use of abstraction.Learners should apply their knowledge of: * backtracking * data mining * heuristics * performance modelling * pipelining * visualisation to solve problems |

3 Algorithms to solve problems and standard algorithms | Algorithms | Analysis and design of algorithms for a given situation.Standard algorithms (bubble sort, insertion sort, binary search and linear search).Implement bubble sort, insertion sort.Implement binary and linear search.Representing, adding data to and removing data from queues and stacks.Compare the suitability of different algorithms for a given task and data set. | The suitability of different algorithms for a given task and data set, in terms of execution time and space.Measures and methods to determine the efficiency of different algorithms, Big O notation (constant, linear, polynomial, exponential and logarithmic complexity).Comparison of the complexity of algorithms.Algorithms for the main data structures (stacks, queues, trees, linked lists); depth-first (post-order) and breadth-first traversal of trees.Standard algorithms (merge sort, quick sort, Dijkstra’s shortest path algorithm, A* algorithm). |

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