OCR H446 A-level Knowledge Compendium
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1.1 Characteristics of Contemporary Processors, Input, Output, and Storage Devices
1.1.1 STRUCTURE AND FUNCTION OF THE PROCESSOR OVERVIEW
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1.1.1 (a) The ALU, Control Unit and Registers. Buses: data, address and control: how this relates to assembly language programs
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1.1.1 (b) The Fetch-Decode-Execute Cycle; including its effects on registers
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1.1.1 (c) The factors affecting the performance of the CPU: clock speed, number of cores, cache
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1.1.1 (d) The use of pipelining in a processor to improve efficiency
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1.1.1 (e) Von Neumann, Harvard and contemporary processor architecture
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1.1.2 TYPES OF PROCESSOR OVERVIEW
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1.1.2 (a) The differences between and uses of CISC and RISC processors
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1.1.2 The differences between and uses of CISC and RISC processors
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1.1.2 (b) GPUs and their uses (including those not related to graphics)
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1.1.2 (c) Multicore and parallel systems
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1.1.3 INPUT, OUTPUT, AND STORAGE OVERVIEW
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1.1.3 (a) How different input, output and storage devices can be applied to the solution of different problems
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1.1.3 (b) The uses of magnetic, flash and optical storage devices
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1.1.3 (c) RAM and ROM
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1.1.3 (d) Virtual storage
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1.2 Software and Software Development
1.2.1 Systems Software Overview
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1.2.1 (a) The need for, function and purpose of operating systems
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1.2.1 (b) Memory management (paging, segmentation, and virtual memory)
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1.2.1 (c) Interrupts, the role of interrupts and Interrupt Service Routines (ISR), role within the Fetch‑Decode-Execute Cycle
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1.2.1 (d) Scheduling: round robin, first come first served, multi-level feedback queues, shortest job first and shortest remaining time
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1.2.1 (e) Distributed, embedded, multi-tasking, multi-user and Real Time operating systems
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1.2.1 (f) BIOS
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1.2.1 (g) Device drivers
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1.2.1 (h) 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 within another
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1.2.2 Applications Generation Overview
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1.2.2 (a) The nature of applications, justifying suitable applications for a specific purpose
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1.2.2 (b) Utilities
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1.2.2 (c) Open source vs closed source
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1.2.2 (d) Translators: Interpreters, compilers, and assemblers
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1.2.2 (e) Stages of compilation (lexical analysis, syntax analysis, code generation, and optimisation)
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1.2.2 (f) Linkers and loaders and use of libraries
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1.2.3 Software Development Overview
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1.2.3 (a) Understand the waterfall lifecycle, agile methodologies, extreme programming, the spiral model and rapid application development
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1.2.3 (b) The relative merits and drawbacks of different methodologies and when they might be used
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1.2.3 (c) Writing and following algorithms
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1.2.4 Types of Programming Language Overview
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1.2.4 (a) Need for and characteristics of a variety of programming paradigms
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1.2.4 (b) Procedural languages
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1.2.4 (c) Assembly language (including following and writing simple programs with the Little Man Computer instruction set)
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1.2.4 (d) Modes of addressing memory (immediate, direct, indirect and indexed)
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1.2.4 (e) Object-oriented languages (see appendix 5d for pseudocode style) with an understanding of classes, objects, methods, attributes, inheritance, encapsulation and polymorphism
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1.3 Exchanging Data
1.3.1 Compression, Encryption and Hashing Overview
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1.3.1 (a) Lossy vs lossless compression
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1.3.1 (b) Run length encoding and dictionary coding for lossless compression
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1.3.1 (c) Symmetric and asymmetric encryption
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1.3.1 (d) Different uses of hashing
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1.3.2 Databases Overview
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1.3.2 (a) Relational database, flat file, primary key, foreign key, secondary key, entity relationship modelling, normalisation and indexing
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1.3.2 (b) Methods of capturing, selecting, managing and exchanging data
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1.3.2 (c) Normalisation to 3NF
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1.3.2 (d) SQL - Interpret and modify
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1.3.2 (e) Referential integrity
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1.3.2 (f) Transaction processing, ACID (Atomicity, Consistency, Isolation, Durability), record locking and redundancy
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1.3.3 Networks Overview
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1.3.3 (a) Characteristics of networks and the importance of protocols and standards
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1.3.3 (b) The internet structure: The TCP/IP stack, DNS, protocol layering, packet and circuit switching
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1.3.3 (c) Network security and threats, use of firewalls, proxies and encryption
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1.3.3 (d) Network hardware
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1.3.3 (e) Client-server and peer to peer
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1.3.4 Web Technologies Overview
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1.3.4 (a) HTML, CSS and JavaScript
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1.3.4 (b) Search engine indexing
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1.3.4 (c) PageRank algorithm
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1.3.4 (d) Server and client side processing
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1.4 Data Types, Data Structures, and Algorithms
1.4.1 Data Types Overview
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1.4.1 (a) Primitive data types, integer, real/floating point, character, string and Boolean
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1.4.1 (b) Represent positive integers in binary
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1.4.1 (c) Use of sign and magnitude and two's complement to represent negative numbers in binary
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1.4.1 (d) Addition and subtraction of binary integers
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1.4.1 (e) Represent positive integers in hexadecimal
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1.4.1 (f) Convert positive integers between binary hexadecimal and denary
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1.4.1 (g) Representation and normalisation of floating point numbers in binary
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1.4.1 (h) Floating point arithmetic, positive and negative numbers, addition and subtraction
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1.4.1 (i) Bitwise manipulation and masks: shifts, combining with AND, OR, and XOR
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1.4.1 (j) How character sets (ASCII and UNICODE) are used to represent text
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1.4.2 Data Structures Overview
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1.4.2 (a) Arrays (of up to 3 dimensions), records, lists, tuples
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1.4.2 (b) The following structures to store data: linked-list, graph (directed and undirected), stack, queue, tree, binary search tree, hash table
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1.4.2 (c) 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)
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1.4.3 Boolean Algebra Overview
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1.4.3 (a) Define problems using Boolean logic
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1.4.3 (b) Manipulate Boolean expressions, including the use of Karnaugh maps to simplify Boolean expressions
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1.4.3 (c) Use the following rules to derive or simplify statements in Boolean algebra: De Morgan's laws, distribution, association, commutation, double negation
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1.4.3 (d) Using logic gate diagrams and truth tables
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1.4.3 (e) The logic associated with D type flip flops, half and full adders
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1.5 Legal, Moral, Cultural, and Ethical Issues
1.5.1 Computing Related Legislation Overview
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1.5.1 (a) The data protection act 1998 / 2018
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1.5.1 (b) The computer misuse act 1990
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1.5.1 (c) The copyright design and patents act 1988
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1.5.1 (d) The regulation of investigatory powers act 2000
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1.5.2 Moral and Ethical Issues Overview
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1.5.2 The individual moral, social, ethical and cultural opportunities and risks of digital technology
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2.1 Elements of Computational Thinking
2.1.1 Thinking Abstractly Overview
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2.1.1 (a) The nature of abstraction
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2.1.1 (b) The need for abstraction
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2.1.1 (c) The differences between an abstraction and reality
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2.1.1 (d) Devise an abstract model for a variety of situations
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2.1.2 Thinking Ahead Overview
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2.1.2 (a) Identify the inputs and outputs for a given situation
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2.1.2 (b) Determine the preconditions for devising a solution to a problem
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2.1.2 (c) The nature, benefits and drawbacks of caching
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2.1.2 (d) The need for reusable program components
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2.1.3 Thinking Procedurally Overview
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2.1.3 (a) Identify the components of a problem
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2.1.3 (b) Identify the components of a solution to a problem
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2.1.3 (c) Determine the order of the steps needed to solve a problem
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2.1.3 (d) Identify sub-procedures necessary to solve a problem
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2.1.4 Thinking Logically Overview
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2.1.4 (a) Identify the points in a solution where a decision has to be taken
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2.1.4 (b) Determine the logical conditions that affect the outcome of a decision
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2.1.4 (c) Determine how decisions affect flow through a program
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2.1.5 Thinking Concurrently Overview
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2.1.5 (a) Determine the parts of a problem that can be tackled at the same time
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2.1.5 (b) Outline the benefits and trade offs that might result from concurrent processing in a particular situation
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2.2 Problem Solving and Programming
2.2.1 Programming Techniques Overview
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2.2.1 (a) Programming constructs: sequence, iteration, branching
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2.2.1 (b) Recursion, how it can be used and compares to an iterative approach
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2.2.1 (c) Global and local variables
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2.2.1 (d) Modularity, functions and procedures, parameter passing by value and by reference
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2.2.1 (e) Use of an IDE to develop/debug a program
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2.2.1 (f) Use of object oriented techniques
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2.2.2 Computational Methods Overview
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2.2.2 (a) Features that make a problem solvable by computational methods
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2.2.2 (b) Problem recognition
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2.2.2 (c) Problem decomposition
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2.2.2 (d) Use of divide and conquer
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2.2.2 (e) Use of abstraction
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2.2.2 (f) Learners should apply their knowledge of: backtracking, data mining, heuristics, performance modelling, pipelining, visualisation to solve problems
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2.3 Algorithms
2.3.1 Algorithms Overview
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2.3.1 (a) Analysis and design of algorithms for a given situation
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2.3.1 (b) The suitability of different algorithms for a given task and data set, in terms of execution time and space
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2.3.1 (c) Measures and methods to determine the efficiency of different algorithms, Big O notation (constant, linear, polynomial, exponential and logarithmic complexity)
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2.3.1 (d) Comparison of the complexity of algorithms
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2.3.1 (e) Algorithms for the main data structures, (stacks, queues, trees, linked lists, depth-first (post-order) and breadth-first traversal of trees)
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2.3.1 (f) Standard algorithms (bubble sort, insertion sort, merge sort, quick sort, Dijkstra’s shortest path algorithm, A* algorithm, binary search and linear search)
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