, <body>, <h1> to <h6>, <p>, <a href>, <img src alt>, <div>, <ul>/<ol>/<li>, <form>, <input>. The class and id attributes let CSS and JavaScript target elements."},{"id":"fc-1.3.4-009","topicId":"1.3.4","front":"CSS Selectors and Rules","back":"Element (p {}), class (.warning {}) and id (#header {}) selectors with properties such as color, background-color, font-family, border, margin and padding. CSS can be inline, internal in <style>, or an external .css file."},{"id":"fc-1.3.4-010","topicId":"1.3.4","front":"JavaScript in the Browser","back":"Runs client-side: variables, functions, if statements and loops; document.getElementById('x').value or .innerHTML reads and changes the page; alert() shows a message. Used for validation and updating pages without reloading."},{"id":"fc-1.3.4-011","topicId":"1.3.4","front":"Search Engine Indexing","back":"Crawlers (spiders) follow links, fetch pages and store their keywords, metadata and links in an index, so a search is answered from the index rather than by scanning the live web."},{"id":"fc-1.3.4-012","topicId":"1.3.4","front":"PageRank Formula","back":"PR(A) = (1 - d) + d x (PR(T1)/C(T1) + ... + PR(Tn)/C(Tn)), where d is the damping factor (about 0.85) and C(T) is the number of outbound links on page T. Pages linked from important pages rank higher."},{"id":"fc-1.4.1-001","topicId":"1.4.1","front":"Binary","back":"A number system using only 0s and 1s (base 2), fundamental to computer storage and processing, e.g. 0100 = 4 in denary; universal but less human-readable."},{"id":"fc-1.4.1-002","topicId":"1.4.1","front":"Denary","back":"A number system with 10 digits (0-9, base 10), used in everyday arithmetic, intuitive but inefficient for computers."},{"id":"fc-1.4.1-003","topicId":"1.4.1","front":"Hexadecimal","back":"A number system with 16 symbols (0-9, A-F, base 16), compact but less intuitive than denary. A = 10, B = 11…"},{"id":"fc-1.4.1-004","topicId":"1.4.1","front":"Boolean","back":"A data type storing TRUE (1) or FALSE (0) for logical operations and conditionals, e.g. 10 > 5 is TRUE."},{"id":"fc-1.4.1-005","topicId":"1.4.1","front":"Character","back":"A data type storing a single letter, number, or symbol."},{"id":"fc-1.4.1-006","topicId":"1.4.1","front":"String","back":"A sequence of characters stored as text in quotes, e.g. 'Hello'."},{"id":"fc-1.4.1-007","topicId":"1.4.1","front":"Integer","back":"A data type for whole numbers without decimals, e.g. -42 or 23."},{"id":"fc-1.4.1-008","topicId":"1.4.1","front":"Real/Floating Point","back":"A data type for numbers with decimals."},{"id":"fc-1.4.1-009","topicId":"1.4.1","front":"ASCII","back":"An 8-bit encoding standard for alphanumeric characters, e.g. 'A' = 65; widely used but limited to 256 characters."},{"id":"fc-1.4.1-010","topicId":"1.4.1","front":"UNICODE","back":"A universal encoding that extends on ASCII, supporting multiple languages with 16+ bits, versatile but uses more memory."},{"id":"fc-1.4.1-011","topicId":"1.4.1","front":"AND (∧)","back":"A logical operator returning TRUE (1) if all inputs are TRUE, e.g. 1 ∧ 1 = 1."},{"id":"fc-1.4.1-012","topicId":"1.4.1","front":"OR (∨)","back":"A logical operator returning TRUE (1) if any input is TRUE, e.g. 1 ∨ 0 = 1."},{"id":"fc-1.4.1-013","topicId":"1.4.1","front":"XOR (⊻)","back":"A logical operator returning TRUE (1) if exactly one input is TRUE, e.g. 1 ⊻ 0 = 1."},{"id":"fc-1.4.1-014","topicId":"1.4.1","front":"NOT (¬)","back":"A logical operator inverting a Boolean value, e.g. ¬1 = 0."},{"id":"fc-1.4.1-015","topicId":"1.4.1","front":"Bitwise Manipulation","back":"Operations on individual bits, e.g. Masks and shifts."},{"id":"fc-1.4.1-016","topicId":"1.4.1","front":"Shifts","back":"A bitwise operation moving bits left or right. The same as multiplying or dividing by 2 dependent on the direction."},{"id":"fc-1.4.1-017","topicId":"1.4.1","front":"Two's Complement","back":"A method representing negative numbers. Write the number out as a positive. From the right hand side, find the first bit that is a 1. Copy everything up to and including that 1. Flip all other bits to the left. MSB becomes negative."},{"id":"fc-1.4.1-018","topicId":"1.4.1","front":"Sign and Magnitude","back":"A method of representing signed numbers in binary where the most significant bit indicates the sign (0 for positive, 1 for negative) and the remaining bits represent the number."},{"id":"fc-1.4.1-019","topicId":"1.4.1","front":"Exponent","back":"The part of a number that specifies the number of times and direction to shift the floating point within the mantissa. Positive exponent, shift decimal to the right, negative, shift left. Allows large/small number representation but limited by bit size."},{"id":"fc-1.4.1-020","topicId":"1.4.1","front":"Mantissa","back":"In floating-point representation, the fractional part of a number in normalised binary form. 1.75 would be 01.11."},{"id":"fc-1.4.1-021","topicId":"1.4.1","front":"Normalisation in Binary","back":"A method to store real numbers in binary using a mantissa and exponent where normalisation adjusts the mantissa to start with 10 for negative numbers, 01 for positive, ensures unique representation and maximises precision."},{"id":"fc-1.4.1-022","topicId":"1.4.1","front":"Floating Point Arithmetic","back":"Operations on decimal binary numbers. Using the exponent to calculate where the decimal place needs to move to within a sequence of a binary."},{"id":"fc-1.4.2-001","topicId":"1.4.2","front":"Arrays","back":"A data structure storing a finite, ordered collection of same data type elements under one identifier, accessed by index. Fast access but fixed size. Contiguous meaning data exists together in memory."},{"id":"fc-1.4.2-002","topicId":"1.4.2","front":"Lists","back":"A data structure maintaining a sequence of elements by index, dynamic in size and can hold multiple data types."},{"id":"fc-1.4.2-003","topicId":"1.4.2","front":"Linked Lists","back":"A dynamic structure where nodes store data and a pointer to the next, easy to modify but slow traversal. Memory intensive due to use of pointers. Non contiguous meaning data can exists anywhere in memory."},{"id":"fc-1.4.2-004","topicId":"1.4.2","front":"Tuples","back":"An ordered, immutable collection of mixed data types, e.g. (1, 'hello', 3.14); stable but immutable."},{"id":"fc-1.4.2-005","topicId":"1.4.2","front":"Records","back":"A structure grouping related fields into one unit, e.g. {name: 'Alice', age: 16}."},{"id":"fc-1.4.2-006","topicId":"1.4.2","front":"Stacks","back":"A LIFO structure where the last item added is removed first."},{"id":"fc-1.4.2-007","topicId":"1.4.2","front":"Queues","back":"A FIFO structure where the first item added is removed first."},{"id":"fc-1.4.2-008","topicId":"1.4.2","front":"Circular Queues","back":"A dynamic queue structure where the end connects to the beginning, reusing space via wrapping front and rear pointers."},{"id":"fc-1.4.2-009","topicId":"1.4.2","front":"Trees","back":"A hierarchical structure of nodes with a root and children, e.g file systems."},{"id":"fc-1.4.2-010","topicId":"1.4.2","front":"Binary Search Tree","back":"A tree with at most two children per node, left smaller, right larger, fast to search, but data needs to be ordered."},{"id":"fc-1.4.2-011","topicId":"1.4.2","front":"Graphs","back":"A structure of nodes and edges for relationships, e.g social network relationships; versatile but memory-heavy."},{"id":"fc-1.4.2-012","topicId":"1.4.2","front":"Directed Graphs","back":"A graph with one-way edges, e.g. A → B."},{"id":"fc-1.4.2-013","topicId":"1.4.2","front":"Undirected Graphs","back":"A graph with bidirectional edges, e.g. A ↔ B."},{"id":"fc-1.4.2-014","topicId":"1.4.2","front":"Breadth First Traversal","back":"A graph traversal exploring neighbors first, using a queue, e.g. level-by-level."},{"id":"fc-1.4.2-015","topicId":"1.4.2","front":"Depth First Traversal","back":"A graph traversal going deep before backtracking, using a stack, e.g. branch exploration."},{"id":"fc-1.4.2-016","topicId":"1.4.2","front":"Hash Table","back":"A structure mapping inputs to indexes via a hash function, fast retrieval but collision risk."},{"id":"fc-1.4.2-017","topicId":"1.4.2","front":"Indexing","back":"A technique creating a index for fast data retrieval, speeds up queries/searching a database."},{"id":"fc-1.4.2-018","topicId":"1.4.2","front":"Dynamic Data Structures","back":"A structure that grows or shrinks at runtime, e.g. linked lists; adaptable but complex to manage."},{"id":"fc-1.4.3-001","topicId":"1.4.3","front":"Boolean Logic","back":"A branch of algebra where logical operators (AND, OR, NOT) are used to process true or false values, underpinning digital circuits."},{"id":"fc-1.4.3-002","topicId":"1.4.3","front":"Boolean Expressions","back":"An expression composed of Boolean variables and logical operators that evaluates to either TRUE or FALSE, e.g. A ∧ B ∨ ¬C."},{"id":"fc-1.4.3-003","topicId":"1.4.3","front":"Association Laws","back":"Rules stating that the grouping of terms does not affect the result: A ∧ (B ∧ C) = (A ∧ B) ∧ C and A ∨ (B ∨ C) = (A ∨ B) ∨ C, simplifying expressions."},{"id":"fc-1.4.3-004","topicId":"1.4.3","front":"Commutation Laws","back":"Rules stating that the order of operands does not affect the result: A ∧ B = B ∧ A and A ∨ B = B ∨ A, showing symmetry in logic."},{"id":"fc-1.4.3-005","topicId":"1.4.3","front":"Distribution Laws","back":"Rules defining how AND and OR operations distribute: A ∧ (B ∨ C) = (A ∧ B) ∨ (A ∧ C) and A ∨ (B ∧ C) = (A ∨ B) ∧ (A ∨ C), key for simplification."},{"id":"fc-1.4.3-006","topicId":"1.4.3","front":"De Morgan's First Law","back":"The negation of a disjunction is the conjunction of the negations: ¬(A ∨ B) = ¬A ∧ ¬B, used in circuit design and proofs."},{"id":"fc-1.4.3-007","topicId":"1.4.3","front":"De Morgan's Second Law","back":"The negation of a conjunction is the disjunction of the negations: ¬(A ∧ B) = ¬A ∨ ¬B, essential for logical equivalence."},{"id":"fc-1.4.3-008","topicId":"1.4.3","front":"Double Negation Law","back":"States that negating a value twice results in the original value: A = ¬¬A, simplifying negated expressions."},{"id":"fc-1.4.3-009","topicId":"1.4.3","front":"D-Type Flip Flops","back":"A sequential circuit that stores a single bit of data, switching states on a clock edge based on input, e.g. used in registers."},{"id":"fc-1.4.3-010","topicId":"1.4.3","front":"Half Adders","back":"A combinational circuit that adds two single-bit binary numbers, outputting a sum bit and a carry bit, e.g. 1 + 1 = 10 (sum 0, carry 1)."},{"id":"fc-1.4.3-011","topicId":"1.4.3","front":"Full Adders","back":"A combinational circuit that adds three bits (including a carry input), producing a sum and carry output, e.g. 1 + 1 + 1 = 11 (sum 1, carry 1)."},{"id":"fc-1.4.3-012","topicId":"1.4.3","front":"Karnaugh Maps","back":"A visual technique for simplifying Boolean expressions by grouping 1s in a grid to minimise logical operations, e.g. reducing A ∧ B ∨ A ∧ ¬B to A."},{"id":"fc-1.4.3-013","topicId":"1.4.3","front":"Logic Gate Diagrams","back":"Graphical representations of Boolean expressions using standard symbols for logic gates (AND, OR, NOT), e.g. A ∧ B as an AND gate."},{"id":"fc-1.5.1-001","topicId":"1.5.1","front":"Computer Misuse Act (1990)","back":"A UK law introduced in 1990 to combat unauthorised computer activities, prohibiting actions like hacking and malware distribution, e.g. penalties up to 7 years for illegal access; protects digital systems and data security but struggles with evolving cyber threats."},{"id":"fc-1.5.1-002","topicId":"1.5.1","front":"Unauthorised Access","back":"Defines and criminalises gaining access to computer material without proper permission, e.g. hacking into a system, punishable by up to 7 years."},{"id":"fc-1.5.1-003","topicId":"1.5.1","front":"Cybercrimes","back":"Covers activities such as hacking, malware distribution, and digital fraud, addressed under the Act to protect systems and data."},{"id":"fc-1.5.1-004","topicId":"1.5.1","front":"Electronic Vandalism","back":"Makes it illegal to modify data or interfere with computer systems without consent, e.g. deleting files or spreading viruses."},{"id":"fc-1.5.1-005","topicId":"1.5.1","front":"Information Theft","back":"Prohibits the unlawful acquisition of personal or confidential data through digital means, e.g. stealing login credentials."},{"id":"fc-1.5.1-006","topicId":"1.5.1","front":"Copyright, Designs and Patents Act (1988)","back":"A UK law from 1988 protecting intellectual property like software, music, and designs. Copyright is automatic. Permission can be granted by the creator or purchased if the creator chooses."},{"id":"fc-1.5.1-007","topicId":"1.5.1","front":"Intellectual Property Protection","back":"Establishes legal ownership rights for literary, dramatic, musical, and artistic works, including software, preventing unauthorised use."},{"id":"fc-1.5.1-008","topicId":"1.5.1","front":"Copyright Duration","back":"Ensures copyright protection for 70 years after the creator's death or creation if anonymous, e.g. software protected until 2095 if created in 2025."},{"id":"fc-1.5.1-009","topicId":"1.5.1","front":"Illegal Distribution","back":"Prevents the unauthorised copying or sharing of protected works, e.g. pirating software or music, with fines or imprisonment."},{"id":"fc-1.5.1-010","topicId":"1.5.1","front":"Digital Copyright","back":"Applies copyright laws to digital content, including music, films, and software, e.g. protecting a downloaded game from being copied."},{"id":"fc-1.5.1-011","topicId":"1.5.1","front":"Data Protection Act (2018 - UK GDPR)","back":"A UK law from 2018, aligned with GDPR, regulating personal data processing, storage, and access, e.g. requires consent for data collection; ensures privacy and user rights but imposes compliance costs on organisations."},{"id":"fc-1.5.1-012","topicId":"1.5.1","front":"Regulation","back":"Determines how personal data is processed, stored, and accessed, aligning with GDPR to ensure lawful handling, e.g. consent for data collection."},{"id":"fc-1.5.1-013","topicId":"1.5.1","front":"User Rights","back":"Introduces strict guidelines for users to access, modify, and delete their personal data, e.g. right to erasure or data portability."},{"id":"fc-1.5.1-014","topicId":"1.5.1","front":"Security Requirements","back":"Mandates data controllers and processors to ensure data is protected, e.g. encryption or secure storage to prevent breaches."},{"id":"fc-1.5.1-015","topicId":"1.5.1","front":"Accountability","back":"Requires organisations to justify and document data collection and processing practices, e.g. maintaining records for audits."},{"id":"fc-1.5.1-016","topicId":"1.5.1","front":"Regulation of Investigatory Powers Act (2000)","back":"A UK law from 2000 allowing authorised surveillance and interception of communications for security, e.g. monitoring emails with warrants; enhances public safety but raises privacy concerns with oversight challenges."},{"id":"fc-1.5.1-017","topicId":"1.5.1","front":"Surveillance Powers","back":"Grants government bodies the authority to monitor electronic communications with warrants, e.g. for national security."},{"id":"fc-1.5.1-018","topicId":"1.5.1","front":"Interception of Communications","back":"Allows agencies to intercept phone calls, emails, and internet activity with proper authorisation, e.g. tracking terrorism suspects."},{"id":"fc-1.5.1-019","topicId":"1.5.1","front":"Data Access","back":"Permits access to encrypted communications and stored data for national security purposes, e.g. requiring decryption keys from providers."},{"id":"fc-1.5.1-020","topicId":"1.5.1","front":"Public Safety & Privacy","back":"Balances law enforcement capabilities with individual rights and privacy protections, e.g. oversight by judicial bodies."},{"id":"fc-1.5.2-001","topicId":"1.5.2","front":"Artificial Intelligence & Bias","back":"Examines ethical concerns in AI to ensure fairness, e.g. biased hiring algorithms misjudging candidates; promotes equitable decision-making but challenging to eliminate bias due to data or design flaws."},{"id":"fc-1.5.2-002","topicId":"1.5.2","front":"Automation & Job Loss","back":"Assesses the social and economic impact of automation replacing human tasks, e.g. self-checkouts reducing cashier jobs; increases productivity but leads to workforce displacement and retraining needs."},{"id":"fc-1.5.2-003","topicId":"1.5.2","front":"Privacy Issues","back":"Addresses ethical risks of data collection and consent in digital systems, e.g. tracking via cookies without user approval; safeguards personal autonomy but weak enforcement hinders protection."},{"id":"fc-1.5.2-004","topicId":"1.5.2","front":"Environmental Impact","back":"Evaluates the ecological consequences of computing, e.g. e-waste from obsolete devices; encourages sustainable tech practices but high implementation costs delay progress."},{"id":"fc-1.5.2-005","topicId":"1.5.2","front":"Digital Divide","back":"Explores social inequity in technology access, e.g. rural areas lacking broadband vs. urban connectivity; fosters inclusion through wider access but resource demands slow efforts."},{"id":"fc-1.5.2-006","topicId":"1.5.2","front":"Monitor Behaviour","back":"Involves using computers to ethically track actions, e.g. CCTV for security; enhances public safety but risks privacy invasion if unregulated."},{"id":"fc-1.5.2-007","topicId":"1.5.2","front":"Analyse Personal Information","back":"Processing personal data with ethical oversight, e.g. medical records improving healthcare; enhances service quality but risks misuse if data security fails."},{"id":"fc-1.5.2-008","topicId":"1.5.2","front":"Piracy and Offensive Communications","back":"Addresses ethical and legal issues of illegal copying and harmful content, e.g. pirated software or hate speech; protects intellectual rights and social harmony but control is difficult online."},{"id":"fc-1.5.2-009","topicId":"1.5.2","front":"Layout, Colour Paradigms and Character Sets","back":"Considers cultural influences on software design, e.g. red symbolising danger in the West, luck in China; improves user experience through cultural adaptation but increases design complexity."},{"id":"fc-1.5.2-010","topicId":"1.5.2","front":"Computers in the Workforce","back":"Opportunities: safer, cheaper and round-the-clock production, new technical jobs, remote working. Risks: job losses and deskilling, need for retraining, workers monitored, a widening digital divide."},{"id":"fc-1.5.2-011","topicId":"1.5.2","front":"Automated Decision Making","back":"Computers making decisions without a human, e.g. loan approval or self-driving cars. Fast and consistent, but can inherit bias from training data, be hard to explain, and leave accountability unclear."},{"id":"fc-1.5.2-012","topicId":"1.5.2","front":"Censorship and the Internet","back":"Governments or ISPs blocking content. For: protects people from illegal or harmful material. Against: restricts free speech, can hide legitimate information and be misused for political control."},{"id":"fc-2.1.1-001","topicId":"2.1.1","front":"Abstraction","back":"Simplifying a problem by focusing on essential details and removing irrelevant ones, reduces complexity for design but may overlook context-specific details."},{"id":"fc-2.1.1-002","topicId":"2.1.1","front":"Data Abstraction","back":"Representing data based on its logical behavior and operations, hiding implementation, e.g. stacks with push/pop."},{"id":"fc-2.1.1-003","topicId":"2.1.1","front":"Graph Theory","back":"Using abstract models of nodes and edges to solve complex problems, e.g. shortest path in a network; enables efficient problem-solving."},{"id":"fc-2.1.1-004","topicId":"2.1.1","front":"Abstraction vs Reality","back":"Distinguishing simplified models from real-world complexity, e.g, a map omits minor roads; abstraction aids focus but loses fine detail."},{"id":"fc-2.1.1-005","topicId":"2.1.1","front":"Representational Abstraction","back":"Removing unnecessary detail so that only the features needed for the problem remain, e.g. the London Underground map shows connections between stations but not real distances."},{"id":"fc-2.1.1-006","topicId":"2.1.1","front":"Abstraction by Generalisation","back":"Grouping similar things under a common concept by their shared characteristics, e.g. treating cars, vans and lorries as 'vehicles' in a car park system, or a class hierarchy in OOP."},{"id":"fc-2.1.1-007","topicId":"2.1.1","front":"Procedural Abstraction","back":"Using a procedure or function without needing to know how it works inside, e.g. calling sort(). The implementation is hidden behind its interface."},{"id":"fc-2.1.1-008","topicId":"2.1.1","front":"Need for Abstraction","back":"Reduces complexity so problems are easier to understand and solve; programs are smaller and faster to write; programmers work at a high level without hardware detail; models can be reused."},{"id":"fc-2.1.1-009","topicId":"2.1.1","front":"Abstract Model","back":"A simplified representation of a real situation that keeps only the essential features, e.g. a traffic simulation that models cars as points moving along a network of roads."},{"id":"fc-2.1.1-010","topicId":"2.1.1","front":"Devising an Abstract Model","back":"Decide the purpose, identify the entities and attributes that matter, discard irrelevant detail, choose data structures (e.g. a graph for a road network) and define the operations needed."},{"id":"fc-2.1.1-011","topicId":"2.1.1","front":"Layers of Abstraction","back":"Systems are built in layers, each hiding the one below: the TCP/IP stack, or high-level language, assembly language and machine code. Each layer only needs the interface to the next."},{"id":"fc-2.1.1-012","topicId":"2.1.1","front":"Example: Chess Program","back":"Board as a 2D array, pieces as objects with a type and position; ignores the material and size of the physical set, the players' names and the time of day."},{"id":"fc-2.1.2-001","topicId":"2.1.2","front":"Caching","back":"Storing frequently accessed data in fast memory for quicker retrieval, e.g. browser caching images; speeds up performance but consumes memory."},{"id":"fc-2.1.2-002","topicId":"2.1.2","front":"Inputs","back":"Data required for a system to process an algorithm, e.g. user form data; defines system scope but incorrect inputs lead to errors."},{"id":"fc-2.1.2-003","topicId":"2.1.2","front":"Outputs","back":"Results produced after processing inputs, e.g. a sorted list from an algorithm."},{"id":"fc-2.1.2-004","topicId":"2.1.2","front":"Preconditions","back":"Conditions required before execution to ensure correct outcomes, e.g. non-empty array for search."},{"id":"fc-2.1.2-005","topicId":"2.1.2","front":"Reusable Program Components","back":"Pre-written, tested code reused across programs, e.g. a sorting function; accelerates development and reliability but may need adaptation for specific use cases."},{"id":"fc-2.1.2-006","topicId":"2.1.2","front":"Identifying Inputs and Outputs","back":"Inputs are the data a solution needs from users, sensors, files or other programs; outputs are the results it produces on screen, in files or as signals. Listing them first defines the scope of the problem."},{"id":"fc-2.1.2-007","topicId":"2.1.2","front":"Benefits of Caching","back":"Frequently used data or instructions are kept in fast memory so they can be reused without recomputing or refetching: faster responses, less network and disk traffic, less processor work."},{"id":"fc-2.1.2-008","topicId":"2.1.2","front":"Drawbacks of Caching","back":"Cached data can become stale or out of date; it uses memory; deciding what to cache is difficult; a cache miss adds overhead; sensitive data held in a cache is a security risk."},{"id":"fc-2.1.2-009","topicId":"2.1.2","front":"Web Caching Example","back":"A browser stores a site's images and CSS so revisits load faster; a server caches the results of common database queries so many users get the same page without re-running the query."},{"id":"fc-2.1.2-010","topicId":"2.1.2","front":"Reusable Components: Benefits","back":"Already written and tested so fewer bugs; saves development time and cost; behaviour is consistent across programs. Examples: libraries, APIs, classes and functions."},{"id":"fc-2.1.2-011","topicId":"2.1.2","front":"Reusable Components: Drawbacks","back":"May not match the exact requirements; can be larger or slower than a custom solution; relies on a third party for updates and security fixes; may carry licensing costs."},{"id":"fc-2.1.2-012","topicId":"2.1.2","front":"Preconditions in Practice","back":"A precondition states what must be true before a procedure is called, e.g. the list is sorted before a binary search. Either document it for the caller or check it in code and handle failures."},{"id":"fc-2.1.3-001","topicId":"2.1.3","front":"Procedural Abstraction","back":"Breaking a problem into sequential steps with specific functions, e.g. recipe steps; structures solutions but requires clear step definition."},{"id":"fc-2.1.3-002","topicId":"2.1.3","front":"Components of a Problem","back":"Dividing a problem into modular, testable sub-procedures, e.g. login and display modules; enhances manageability but increases initial planning."},{"id":"fc-2.1.3-003","topicId":"2.1.3","front":"Decomposition","back":"Breaking a large problem into smaller sub-problems that are easier to understand, solve and test. Repeat until each part is simple enough to implement as a single sub-procedure."},{"id":"fc-2.1.3-004","topicId":"2.1.3","front":"Sub-procedure","back":"A named block of code (procedure or function) that solves one sub-problem, e.g. validateLogin(). It can be written and tested separately, reused, and called from the main program."},{"id":"fc-2.1.3-005","topicId":"2.1.3","front":"Components of a Solution","back":"The sub-procedures, data structures and interfaces that together solve the problem. For a quiz program: load questions, ask a question, check the answer, update the score, show results."},{"id":"fc-2.1.3-006","topicId":"2.1.3","front":"Order of Steps","back":"Some steps depend on earlier ones (a file must be opened before it is read), so their sequence is fixed. Independent steps can be ordered for clarity or even run concurrently."},{"id":"fc-2.1.3-007","topicId":"2.1.3","front":"Top-down Design","back":"Start with the overall problem and refine it step by step into smaller sub-problems, producing a hierarchy of procedures that can be implemented one at a time."},{"id":"fc-2.1.3-008","topicId":"2.1.3","front":"Structure (Hierarchy) Chart","back":"A diagram showing how a program is broken into modules and sub-modules, which module calls which, and the data passed between them."},{"id":"fc-2.1.3-009","topicId":"2.1.3","front":"Benefits of Thinking Procedurally","back":"Easier to plan, test and debug; work can be shared across a team; sub-procedures can be reused in other programs; changes are contained within one module."},{"id":"fc-2.1.3-010","topicId":"2.1.3","front":"Interface of a Sub-procedure","back":"The parameters it accepts and the value it returns. Defining interfaces clearly lets modules be developed and tested independently."},{"id":"fc-2.1.3-011","topicId":"2.1.3","front":"Example: Checkout Sub-procedures","back":"scanItem(), applyDiscount(), calculateTotal(), takePayment() and printReceipt(), each a separate sub-procedure called in order by the main program."},{"id":"fc-2.1.3-012","topicId":"2.1.3","front":"Prerequisite Step","back":"A step that must be completed before another can begin, e.g. input must be validated before it is stored. Identifying prerequisites determines the order of the steps."},{"id":"fc-2.1.4-001","topicId":"2.1.4","front":"Flowcharts","back":"Diagrams visually representing a program's logical flow with decision points, e.g. diamond for if-then-else."},{"id":"fc-2.1.4-002","topicId":"2.1.4","front":"Logical Conditions","back":"Boolean statements guiding program flow via control structures, e.g. x > 0."},{"id":"fc-2.1.4-003","topicId":"2.1.4","front":"Decision Points in a Solution","back":"Moments where a program chooses paths based on conditions, e.g. if x > 0."},{"id":"fc-2.1.4-004","topicId":"2.1.4","front":"Selection (Branching)","back":"A construct where the program chooses between paths based on a Boolean condition: if / elseif / else, or switch/case when comparing one value against several options."},{"id":"fc-2.1.4-005","topicId":"2.1.4","front":"Boolean Operators in Conditions","back":"AND, OR and NOT combine simple conditions, e.g. if age >= 18 AND hasID then allow entry. Brackets and the order of evaluation change the result."},{"id":"fc-2.1.4-006","topicId":"2.1.4","front":"Nested Decisions","back":"A decision placed inside another decision; the inner condition is only tested if the outer one is true. Reduce deep nesting with elseif or by combining conditions."},{"id":"fc-2.1.4-007","topicId":"2.1.4","front":"Decisions and Program Flow","back":"Each decision point splits the flow into alternative paths. Tracing which path is taken for given inputs predicts the output and reveals logic errors."},{"id":"fc-2.1.4-008","topicId":"2.1.4","front":"Loop Conditions","back":"Decisions that control iteration: while checks the condition before each pass, do-until (repeat) checks after so the body runs at least once, for counts a fixed number of times."},{"id":"fc-2.1.4-009","topicId":"2.1.4","front":"Trace Table","back":"A table recording the value of each variable and condition line by line as an algorithm runs. Used to follow logic, test decisions and find errors."},{"id":"fc-2.1.4-010","topicId":"2.1.4","front":"Validation as a Decision","back":"Checking that input meets rules (presence, range, type, length, format) before it is used. The decision determines whether to accept it, reject it or ask again."},{"id":"fc-2.1.4-011","topicId":"2.1.4","front":"Comparison Operators","back":"== equal to, != not equal to, <, <=, >, >=. Writing = (assignment) instead of == (comparison) in a condition is a common logic error in OCR pseudocode."},{"id":"fc-2.1.4-012","topicId":"2.1.4","front":"Flowchart Decision Symbol","back":"A diamond containing the condition, with labelled Yes/No (True/False) exits showing how the outcome of the decision affects the flow of the program."},{"id":"fc-2.1.5-001","topicId":"2.1.5","front":"Concurrent Processing","back":"Running multiple tasks simultaneously to boost efficiency, e.g. multi-threading in games; improves performance but not all tasks can be run concurrently."},{"id":"fc-2.1.5-002","topicId":"2.1.5","front":"Concurrent vs Parallel Processing","back":"Concurrent: several tasks make progress in overlapping time periods, e.g. time-sliced on one core. Parallel: tasks execute at the same instant on multiple cores or processors. Parallel processing is one way to achieve concurrency."},{"id":"fc-2.1.5-003","topicId":"2.1.5","front":"Thread","back":"A single sequence of instructions inside a process that can be scheduled on its own. Threads of the same process share memory, so they can work concurrently on the same data."},{"id":"fc-2.1.5-004","topicId":"2.1.5","front":"Identifying Parts That Can Run Concurrently","back":"Look for parts of a problem that do not depend on each other's results, e.g. downloading several files or applying a filter to different regions of an image. A task that needs another's output must wait for it."},{"id":"fc-2.1.5-005","topicId":"2.1.5","front":"Dependency Between Tasks","back":"When one task needs the result of another before it can start, e.g. data must be sorted before a binary search. Dependencies limit which parts of a problem can be tackled at the same time."},{"id":"fc-2.1.5-006","topicId":"2.1.5","front":"Benefits of Concurrent Processing","back":"Independent tasks finish sooner; makes use of every core; programs stay responsive (a UI thread keeps working while a file loads); many users can be served at once, e.g. a ticketing website."},{"id":"fc-2.1.5-007","topicId":"2.1.5","front":"Trade-offs of Concurrent Processing","back":"Overhead of creating and coordinating threads; harder to write, test and debug; shared data must be protected, which can slow things down; not every problem can be split; results may need recombining."},{"id":"fc-2.1.5-008","topicId":"2.1.5","front":"Race Condition","back":"A bug where the result depends on the timing of two concurrent tasks using shared data, e.g. two threads both read a balance of 100 and each add 10, leaving 110 instead of 120."},{"id":"fc-2.1.5-009","topicId":"2.1.5","front":"Deadlock","back":"Two or more tasks each wait for a resource held by the other, so none can continue. Avoided by acquiring locks in a fixed order, using timeouts, or never holding more than one lock at a time."},{"id":"fc-2.1.5-010","topicId":"2.1.5","front":"Lock (Mutual Exclusion)","back":"A mechanism that allows only one thread to use a shared resource at a time; others wait until it is released. Prevents race conditions but can create bottlenecks and deadlock if misused."},{"id":"fc-2.1.5-011","topicId":"2.1.5","front":"Concurrency in a Multi-user System","back":"Each user's request is handled at the same time for speed, but shared data such as a seat count must be locked or updated atomically so the same seat is never sold twice."},{"id":"fc-2.1.5-012","topicId":"2.1.5","front":"When Concurrency Is Not Worth It","back":"Gains are limited by the sequential parts of a problem and by coordination costs. For small tasks the overhead of setting up threads can make a concurrent solution slower than a sequential one."},{"id":"fc-2.2.1-001","topicId":"2.2.1","front":"Branching","back":"A control structure selecting paths based on Boolean conditions, e.g. if x > 0 print 'positive'; enables decisions but complex nesting reduces readability."},{"id":"fc-2.2.1-002","topicId":"2.2.1","front":"Functions","back":"Reusable subroutines returning a value, e.g. def add(a, b): return a + b; promotes modularity."},{"id":"fc-2.2.1-003","topicId":"2.2.1","front":"Global Variables","back":"Variables declared globally, accessible anywhere, e.g. score = 0; simplifies access but risks unintended changes."},{"id":"fc-2.2.1-004","topicId":"2.2.1","front":"Integrated Development Environment (IDE)","back":"A tool aiding coding with debugging and testing features, streamlines development."},{"id":"fc-2.2.1-005","topicId":"2.2.1","front":"Iterations","back":"Repeating code until a condition or count is met, e.g. while loop; automates repetition but risks infinite loops."},{"id":"fc-2.2.1-006","topicId":"2.2.1","front":"Local Variables","back":"Variables scoped to a subroutine, e.g. temp in a function; reduces conflicts but limits scope."},{"id":"fc-2.2.1-007","topicId":"2.2.1","front":"Modularity","back":"Dividing a program into reusable modules, e.g. input/processing files; enhances maintenance but requires planning."},{"id":"fc-2.2.1-008","topicId":"2.2.1","front":"Parameter Passing by Reference","back":"Passing a variable's address to modify it, e.g. altering a list; efficient but risks accidental overwriting of original variable."},{"id":"fc-2.2.1-009","topicId":"2.2.1","front":"Parameter Passing by Value","back":"Passing a copy of a variable, safe but memory-intensive."},{"id":"fc-2.2.1-010","topicId":"2.2.1","front":"Parameters","back":"Inputs to functions/procedures, e.g. x, y in multiply(x, y); customises behavior but requires correct passing."},{"id":"fc-2.2.1-011","topicId":"2.2.1","front":"Procedures","back":"Code blocks performing tasks without return, e.g. def print_message(); organizes logic but no output."},{"id":"fc-2.2.1-012","topicId":"2.2.1","front":"Recursion","back":"A function calling itself with a base case; elegant but memory intensive."},{"id":"fc-2.2.1-013","topicId":"2.2.1","front":"Sequences","back":"Executing statements in order, e.g. print 'A' then 'B'."},{"id":"fc-2.2.1-014","topicId":"2.2.1","front":"Subroutines","back":"Independent code performing tasks, e.g. calculate_total()."},{"id":"fc-2.2.2-001","topicId":"2.2.2","front":"Backtracking","back":"Exploring paths and retreating from dead-ends, e.g. maze solving; finds solutions but slow for large problems."},{"id":"fc-2.2.2-002","topicId":"2.2.2","front":"Computable Problems","back":"Problems solvable with finite steps, e.g. sorting; enables automation but excludes undecidable issues."},{"id":"fc-2.2.2-003","topicId":"2.2.2","front":"Computational Methods","back":"Algorithmic techniques for problem-solving."},{"id":"fc-2.2.2-004","topicId":"2.2.2","front":"Data Mining","back":"Extracting patterns from large datasets, e.g. sales trends; reveals insights but computationally intensive."},{"id":"fc-2.2.2-005","topicId":"2.2.2","front":"Divide and Conquer","back":"Splitting problems into sub-problems, e.g. merge sort."},{"id":"fc-2.2.2-006","topicId":"2.2.2","front":"Heuristics","back":"Approximating solutions for complex problems, e.g. A* pathfinding; fast but not always optimal."},{"id":"fc-2.2.2-007","topicId":"2.2.2","front":"Performance Modelling","back":"Simulating system behavior under conditions, e.g. network load; predicts performance, not always accurate."},{"id":"fc-2.2.2-008","topicId":"2.2.2","front":"Problem Decomposition","back":"Breaking problems into manageable parts, e.g. game graphics/logic."},{"id":"fc-2.2.2-009","topicId":"2.2.2","front":"Problem Recognition","back":"Identifying solution patterns, understanding common inputs, processes and outputs."},{"id":"fc-2.2.2-010","topicId":"2.2.2","front":"Visualisation","back":"Using diagrams to model algorithms, e.g, flowcharts; aids understanding but time-consuming."},{"id":"fc-2.2.2-011","topicId":"2.2.2","front":"Pipelining","back":"Splitting a process into stages so that different items are at different stages at the same time, like a production line; e.g. the CPU fetching one instruction while decoding another. Increases throughput."},{"id":"fc-2.2.2-012","topicId":"2.2.2","front":"Abstraction in Computational Methods","back":"Stripping a problem down to a model a computer can solve, e.g. representing delivery routes as a weighted graph so that Dijkstra's algorithm can find the shortest path."},{"id":"fc-2.3.1-001","topicId":"2.3.1","front":"A* Algorithm","back":"An informed search estimating shortest paths with distance and cost, e.g. game pathfinding; efficient but heuristic-dependent. A good enough approach to pathfinding."},{"id":"fc-2.3.1-002","topicId":"2.3.1","front":"Big O Notation","back":"Classifying efficiency by worst-case time/space complexity. Describes the time and space complexity of a given algorithm based on the size of the input/dataset."},{"id":"fc-2.3.1-003","topicId":"2.3.1","front":"Binary Search","back":"A logarithmic search dividing sorted lists, O(log n); fast but requires data to be sorted first."},{"id":"fc-2.3.1-004","topicId":"2.3.1","front":"Bubble Sort","back":"Swapping adjacent elements until sorted, O(n²), simple but slow for large data sets."},{"id":"fc-2.3.1-005","topicId":"2.3.1","front":"Dijkstra's Shortest Path Algorithm","back":"Finding shortest paths by exploring all options, e.g. network routing; optimal but slow for large graphs."},{"id":"fc-2.3.1-006","topicId":"2.3.1","front":"Insertion Sort","back":"Building a sorted list incrementally, O(n²), intuitive but inefficient for data that has no order to it already."},{"id":"fc-2.3.1-007","topicId":"2.3.1","front":"Linear Search","back":"Checking each item sequentially, O(n), simple but slow."},{"id":"fc-2.3.1-008","topicId":"2.3.1","front":"Merge Sort","back":"Dividing and merging sublists, O(n log n), efficient but space-heavy."},{"id":"fc-2.3.1-009","topicId":"2.3.1","front":"O(1) (Constant Time/Space)","back":"Fixed time/space regardless of input, e.g. array access; fastest but rare in algorithm design."},{"id":"fc-2.3.1-010","topicId":"2.3.1","front":"O(2ⁿ) (Exponential Time/Space)","back":"Exponential growth with input, e.g. recursive Fibonacci; powerful but impractical."},{"id":"fc-2.3.1-011","topicId":"2.3.1","front":"O(log(n)) (Logarithmic Time/Space)","back":"Logarithmic growth, e.g. binary search; scalable but needs structure."},{"id":"fc-2.3.1-012","topicId":"2.3.1","front":"O(n) (Linear Time/Space)","back":"Proportional growth, e.g. linear search; predictable but scales poorly."},{"id":"fc-2.3.1-013","topicId":"2.3.1","front":"O(nᵏ) (Polynomial Time/Space)","back":"Polynomial growth, e.g. O(n²) for loops; manageable but slow for high k."},{"id":"fc-2.3.1-014","topicId":"2.3.1","front":"Quick Sort","back":"Partitioning around a pivot, O(n log n) average; fast but worst-case O(n²)."},{"id":"fc-2.3.1-015","topicId":"2.3.1","front":"Space Complexity","back":"Memory required by an algorithm."},{"id":"fc-2.3.1-016","topicId":"2.3.1","front":"Time Complexity","back":"Time taken as a function of input size."}]}]]}]}],["$L18"],"$L19"]}] </article></body></html>

11:["$","$1","c",{"children":[["$","div",null,{"className":"min-h-screen py-16","children":["$","div",null,{"className":"max-w-6xl mx-auto px-6","children":[["$","div",null,{"className":"mb-10","children":[["$","div",null,{"className":"inline-flex items-center gap-2 rounded-full border border-[color:var(--border)] bg-[color:var(--surface)] px-4 py-2 text-sm text-[color:var(--muted)]","children":[["$","span",null,{"className":"inline-block h-2 w-2 rounded-full","style":{"background":"var(--accent)"}}],"Daily Practice"]}],["$","h1",null,{"className":"mt-5 text-4xl md:text-5xl font-semibold tracking-[-0.04em]","children":"Daily Deck"}],["$","p",null,{"className":"mt-3 text-lg text-[color:var(--muted)]","children":"Twenty flashcards from across the OCR H446 course, refreshed every day. Ten minutes on the clock."}]]}],["$","$L17",null,{"flashcards":[{"id":"fc-1.1.1-001","topicId":"1.1.1","front":"Accumulator (ACC)","back":"Holds the results of calculations performed by the ALU. Checks for conditional branching. Stores data from the MDR/RAM."},{"id":"fc-1.1.1-002","topicId":"1.1.1","front":"Address Bus","back":"A unidirectional pathway that carries memory addresses for data or instructions."},{"id":"fc-1.1.1-003","topicId":"1.1.1","front":"Arithmetic and Logic Unit (ALU)","back":"Handles arithmetic calculations and logical operations required for executing instructions."},{"id":"fc-1.1.1-004","topicId":"1.1.1","front":"Buses","back":"Communication pathways that transfer data, addresses to other components and controls signals between CPU components."},{"id":"fc-1.1.1-005","topicId":"1.1.1","front":"Contemporary Processor Architecture","back":"A modern CPU design that integrates elements from both Von Neumann and Harvard architectures."},{"id":"fc-1.1.1-006","topicId":"1.1.1","front":"Control Bus","back":"A bi-directional pathway that transmits control signals sent from the control unit to manage the execution and coordination of instructions in the CPU."},{"id":"fc-1.1.1-007","topicId":"1.1.1","front":"Control Unit (CU)","back":"Sends control signals to coordinate the movement of data through the processor. It also controls the buses to manage communication between the CPU, memory, and input/output devices."},{"id":"fc-1.1.1-008","topicId":"1.1.1","front":"Current Instruction Register (CIR)","back":"A register that holds the current instruction being processed, separating it into operand and opcode."},{"id":"fc-1.1.1-009","topicId":"1.1.1","front":"Data Bus","back":"A bi-directional pathway that carries data between the processor and memory."},{"id":"fc-1.1.1-010","topicId":"1.1.1","front":"Fetch-Decode-Execute Cycle","back":"The sequence in which the CPU retrieves, interprets, and executes instructions."},{"id":"fc-1.1.1-011","topicId":"1.1.1","front":"Harvard Architecture","back":"A computer architecture that separates instruction and data storage into distinct memory units to improve efficiency. Uses data and address buses."},{"id":"fc-1.1.1-012","topicId":"1.1.1","front":"Memory Address Register (MAR)","back":"Stores the memory address of the current instruction or data location to be accessed via RAM."},{"id":"fc-1.1.1-013","topicId":"1.1.1","front":"Memory Data Register (MDR)","back":"Holds data that is being read from or written to memory (RAM) during processing. Sends data/instruction to the current instruction register."},{"id":"fc-1.1.1-014","topicId":"1.1.1","front":"Pipelining","back":"A technique that enables overlapping instruction execution by fetching the next instruction while processing the current one."},{"id":"fc-1.1.1-015","topicId":"1.1.1","front":"Program Counter (PC)","back":"A register that stores the address of the next instruction to be executed."},{"id":"fc-1.1.1-016","topicId":"1.1.1","front":"Registers","back":"Small, fast memory units within the CPU that temporarily store data, instructions, or addresses."},{"id":"fc-1.1.1-017","topicId":"1.1.1","front":"Von Neumann Architecture","back":"A computing model where data and instructions share the same memory and communication pathways. Not as efficient as Harvard."},{"id":"fc-1.1.1-018","topicId":"1.1.1","front":"Fetch","back":"The PC copies the address to the MAR, which is then sent via the Address Bus. The PC increments, a Read signal is sent via the Control Bus. The RAM places the instruction on the Data Bus, transferring it to the MDR, then into the CIR for decoding."},{"id":"fc-1.1.1-019","topicId":"1.1.1","front":"Decode","back":"Interprets the fetched instruction. The CIR sends the instruction to the Control Unit, where the instruction is split into opcode and operand. The CU then generates control signals to prepare the necessary registers, buses, and ALU for execution."},{"id":"fc-1.1.1-020","topicId":"1.1.1","front":"Execute","back":"Carries out the decoded instruction. The result is then stored in a register, memory, or sent to an output device."},{"id":"fc-1.1.1-021","topicId":"1.1.1","front":"Clock Speed","back":"The rate at which the processor's internal clock generates pulses, affecting how quickly instructions are executed. Higher clock speeds leads to more cycles per second."},{"id":"fc-1.1.1-022","topicId":"1.1.1","front":"Number of Cores","back":"The number of processing units in a CPU, allowing multiple instructions to be executed simultaneously, increasing performance."},{"id":"fc-1.1.1-023","topicId":"1.1.1","front":"Cache","back":"A small, high-speed memory within the CPU that stores frequently used instructions and data. Quicker to access than RAM, therefore more cache increases performance."},{"id":"fc-1.1.2-001","topicId":"1.1.2","front":"Complex Instruction Set Computer (CISC)","back":"A processor architecture designed to execute complex instructions. Instructions may take multiple clock cycles, instructions are variable in size in format, limiting pipelining efficiency. Complex circuitry increases cost in comparison to RISC. Multiple addressing modes."},{"id":"fc-1.1.2-002","topicId":"1.1.2","front":"Graphic Processing Unit (GPU)","back":"A specialised processor containing many small cores optimised for parallel processing, commonly used in graphics rendering, machine learning, and data processing."},{"id":"fc-1.1.2-003","topicId":"1.1.2","front":"Multicore Systems","back":"A processor design that integrates multiple CPU cores onto a single chip, enabling efficient workload distribution and improved performance."},{"id":"fc-1.1.2-004","topicId":"1.1.2","front":"Parallel Processing System","back":"Multiple processors or processor cores work simultaneously to execute different parts of a task or multiple tasks at the same time, improving efficiency and reducing execution time."},{"id":"fc-1.1.2-005","topicId":"1.1.2","front":"Reduced Instruction Set Computer (RISC)","back":"A processor architecture that executes simple instructions within a single clock cycle (higher battery life compare to CISC), allowing for pipelining but requiring more RAM for program execution. Less complex circuitry reduces cost."},{"id":"fc-1.1.3-001","topicId":"1.1.3","front":"Input Devices","back":"Hardware peripherals that allow users to send data to a computer. Examples include keyboards, mice, and scanners."},{"id":"fc-1.1.3-002","topicId":"1.1.3","front":"Output Devices","back":"Devices that take digital signals from a computer and convert them into a human-perceivable format, such as monitors and speakers."},{"id":"fc-1.1.3-003","topicId":"1.1.3","front":"Storage Device","back":"Any hardware component used to store data permanently. Examples include flash storage, magnetic storage, optical storage and virtual storage."},{"id":"fc-1.1.3-004","topicId":"1.1.3","front":"Random Access Memory (RAM)","back":"A fast, temporary memory location used to store active programs and data. It allows quick access but loses all stored information when the system is turned off (volatile memory). More RAM can increase performance as data does not be accessed from slower secondary storage as frequently."},{"id":"fc-1.1.3-005","topicId":"1.1.3","front":"Read-Only Memory (ROM)","back":"Permanently stores essential instructions required for the computer's startup process. It cannot be modified and retains data even when power is lost (non-volatile). Holds firmware/bios, bootloader and embedded software."},{"id":"fc-1.1.3-006","topicId":"1.1.3","front":"Flash Storage","back":"A solid-state storage technology that retains data using memory chips. It has no moving parts, making it faster and more durable than traditional hard drives. Suitable for small portable devices. Consumes less power compared to magnetic."},{"id":"fc-1.1.3-007","topicId":"1.1.3","front":"Magnetic Storage","back":"A storage method that uses magnetised areas to represent data. It is typically used in hard disk drives, offering high capacity at a low cost. Susceptible to damage due to moving parts. Consumes more power compared to flash."},{"id":"fc-1.1.3-008","topicId":"1.1.3","front":"Optical Storage","back":"A medium that uses laser technology (pits and falls) to read and write data, commonly found in CDs, DVDs, and Blu-ray discs. Portable, but small in capacity. Can be damaged/scratched easily making the data unusable."},{"id":"fc-1.1.3-009","topicId":"1.1.3","front":"Cloud Storage","back":"Allows data to be stored on remote servers and accessed via the internet. It enables users to store, manage, and retrieve files on-demand, providing scalability, security, and backup without relying on local storage devices."},{"id":"fc-1.2.1-001","topicId":"1.2.1","front":"Operating System","back":"A collection of software that manages hardware resources, provides a user interface, gives a platform for applications to run on and controls access to a computer."},{"id":"fc-1.2.1-002","topicId":"1.2.1","front":"Basic Input Output System (BIOS)","back":"Firmware stored in ROM that initializes hardware during the boot process and loads the operating system. It performs POST (Power-On Self-Test), checks connected devices, and provides low-level control over hardware components."},{"id":"fc-1.2.1-003","topicId":"1.2.1","front":"Device Drivers","back":"Software that allows the operating system to communicate with hardware devices like printers, keyboards, and network adapters (peripherals)."},{"id":"fc-1.2.1-004","topicId":"1.2.1","front":"Memory Management","back":"Allocating and managing RAM (main memory) and virtual memory efficiently to allow multiple applications to run at the same time. Function of an operating system that allows for multitasking and security (does not let programs access memory reserved for other programs)."},{"id":"fc-1.2.1-005","topicId":"1.2.1","front":"Paging","back":"Partitioning memory into equal fixed sized divisions/pieces. Uses physical addressing. Can lead to waste space in memory if applications do not use the entire division/page."},{"id":"fc-1.2.1-006","topicId":"1.2.1","front":"Segmentation","back":"Partitioning memory into variable-sized logical sections to optimise performance. Uses logical addressing, more efficient use of RAM compared to paging."},{"id":"fc-1.2.1-007","topicId":"1.2.1","front":"Virtual Memory","back":"A technique that extends RAM using secondary storage, allowing larger applications to run by swapping inactive data between RAM and disk/secondary storage to make more room for active applications/data. Frequent swapping can cause disk thrashing."},{"id":"fc-1.2.1-008","topicId":"1.2.1","front":"Virtual Machines","back":"Software that emulates a physical computer, allowing multiple operating systems to run independently on the same hardware. Useful for testing software without having the physical hardware required. Saves space, time and money."},{"id":"fc-1.2.1-009","topicId":"1.2.1","front":"Scheduling","back":"Allocates CPU time to multiple running tasks, ensuring efficient execution. First Come First Served, Round-Robin, Shortest Job First, Shortest Remaining Time, MLFQ."},{"id":"fc-1.2.1-010","topicId":"1.2.1","front":"First Come First Served (FCFS)","back":"Processes are executed in the order they arrive, like a queue. Non preemptive (once a process starts executing on the CPU, it runs to completion)."},{"id":"fc-1.2.1-011","topicId":"1.2.1","front":"Round-Robin","back":"Each task gets a fixed time slice before moving to the next, ensuring fair CPU usage. Preemptive (the CPU can interrupt a running process)."},{"id":"fc-1.2.1-012","topicId":"1.2.1","front":"Shortest Job First (SJF)","back":"Prioritises tasks with the shortest estimated runtime. Non preemptive (once a process starts executing on the CPU, it runs to completion)."},{"id":"fc-1.2.1-013","topicId":"1.2.1","front":"Shortest Remaining Time (SRT)","back":"Prioritises tasks with the least time left to execute. Preemptive (the CPU can interrupt a running process)."},{"id":"fc-1.2.1-014","topicId":"1.2.1","front":"Multi-level Feedback Queues","back":"A scheduling system that organises tasks into different priority levels, allowing processes to move between queues based on execution time. Preemptive (the CPU can interrupt a running process)."},{"id":"fc-1.2.1-015","topicId":"1.2.1","front":"Multi-tasking Operating Systems","back":"Supports multiple applications running simultaneously by managing CPU resources efficiently."},{"id":"fc-1.2.1-016","topicId":"1.2.1","front":"Multi-User Operating Systems","back":"Supports multiple users accessing system resources simultaneously, managing user sessions."},{"id":"fc-1.2.1-017","topicId":"1.2.1","front":"Distributed Operating Systems","back":"Multiple computers work together as one, distributing tasks efficiently across different machines via a network."},{"id":"fc-1.2.1-018","topicId":"1.2.1","front":"Real-Time Operating Systems","back":"An OS designed for real-time applications that require immediate responses, such as medical devices and industrial systems, ensuring guaranteed response time with plenty of overhead."},{"id":"fc-1.2.1-019","topicId":"1.2.1","front":"Embedded Operating Systems","back":"A specialised OS designed to run on dedicated hardware with minimal resources, such as appliances (washing machine) and embedded devices, optimised for specific tasks and low power consumption."},{"id":"fc-1.2.1-020","topicId":"1.2.1","front":"Interrupts","back":"A mechanism where hardware or software sends an interrupt request to the CPU, pausing the current task to handle urgent or high-priority events."},{"id":"fc-1.2.1-021","topicId":"1.2.1","front":"Interrupt Service Routines (ISR)","back":"A routine where the CPU saves its current state (storing current register values), executes code to handle an interrupt, and then restores the state to resume the previous task."},{"id":"fc-1.2.1-022","topicId":"1.2.1","front":"Intermediate Code","back":"A partially translated, machine-independent form of a program generated by a compiler, enabling portability across different architectures before final machine code generation."},{"id":"fc-1.2.2-001","topicId":"1.2.2","front":"Applications","back":"Software programs designed for end-users to perform specific tasks. Examples include word processors, web browsers, spreadsheets, desktop publishing and graphics manipulation software."},{"id":"fc-1.2.2-002","topicId":"1.2.2","front":"Utilities","back":"System software with one purpose that is used to perform maintenance/upkeep tasks, such as improving performance, diagnosing issues, and managing files, to support the operating system. Examples include disk defragmentation, compression, backups and encryption."},{"id":"fc-1.2.2-003","topicId":"1.2.2","front":"Translator","back":"A general term for software that converts source code from one programming language to another, such as compilers, interpreters, or assemblers."},{"id":"fc-1.2.2-004","topicId":"1.2.2","front":"Compilers","back":"A translator that converts an entire high-level program into machine code in one process before execution, enabling faster runtime. Platform and architecture specific."},{"id":"fc-1.2.2-005","topicId":"1.2.2","front":"Interpreters","back":"A translator that processes and executes high-level source code line by line, without producing a separate machine code file."},{"id":"fc-1.2.2-006","topicId":"1.2.2","front":"Assembler","back":"A translator that converts assembly language mnemonics into machine code, specific to a processor's architecture."},{"id":"fc-1.2.2-007","topicId":"1.2.2","front":"Compilation","back":"The multi-stage process of converting high-level source code into machine code, enabling execution by the specific processor or platform."},{"id":"fc-1.2.2-008","topicId":"1.2.2","front":"Lexical Analysis","back":"The first compilation stage, where whitespace and comments are removed, and source code is broken into tokens for syntax analysis."},{"id":"fc-1.2.2-009","topicId":"1.2.2","front":"Syntax Analysis","back":"The second compilation stage, where tokens are parsed to check code structure against syntax rules, identifying errors."},{"id":"fc-1.2.2-010","topicId":"1.2.2","front":"Code Generation","back":"The final compilation stage, where processed source code is translated into optimised machine code for execution."},{"id":"fc-1.2.2-011","topicId":"1.2.2","front":"Optimisation","back":"A compilation step that enhances machine code efficiency by minimizing resource use and execution time."},{"id":"fc-1.2.2-012","topicId":"1.2.2","front":"Libraries","back":"Pre-compiled collections of reusable functions and routines, linked into programs to avoid rewriting common code."},{"id":"fc-1.2.2-013","topicId":"1.2.2","front":"Linkers","back":"A program that resolves references and combines compiled object files and libraries into a single executable."},{"id":"fc-1.2.2-014","topicId":"1.2.2","front":"Loaders","back":"An OS component that loads executable programs and their libraries into RAM, preparing them for execution."},{"id":"fc-1.2.2-015","topicId":"1.2.2","front":"Open Source","back":"Software with publicly accessible source code, freely available for use, modification, and redistribution under an open license."},{"id":"fc-1.2.2-016","topicId":"1.2.2","front":"Closed Source","back":"Proprietary software with restricted source code access, distributed under a license limiting modification and redistribution."},{"id":"fc-1.2.3-001","topicId":"1.2.3","front":"Agile Methodologies","back":"A collective term that describes an approach to software development using rapid cycles, adapting to change by continuously integrating user feedback."},{"id":"fc-1.2.3-002","topicId":"1.2.3","front":"Extreme Programming","back":"An agile method emphasising short cycles (sprints), frequent releases, paired programming, and continuous user feedback integration. Focuses on creating high quality code."},{"id":"fc-1.2.3-003","topicId":"1.2.3","front":"Rapid Application Development","back":"A method for fast software delivery, using prototyping, extensive user involvement, and flexibility to adapt to changes."},{"id":"fc-1.2.3-004","topicId":"1.2.3","front":"Spiral Model","back":"A risk-driven hybrid model combining iterative and structured development, refining prototypes through cycles with risk analysis."},{"id":"fc-1.2.3-005","topicId":"1.2.3","front":"Waterfall Lifecycle","back":"A linear, sequential development model where each phase (e.g. analysis, design) completes before the next, offering structure but little flexibility."},{"id":"fc-1.2.3-006","topicId":"1.2.3","front":"Waterfall: Merits and Drawbacks","back":"Merits: simple, structured, clear milestones and documentation; suits fixed requirements. Drawbacks: inflexible, testing comes late, users see nothing until the end, changes are costly."},{"id":"fc-1.2.3-007","topicId":"1.2.3","front":"Agile: Merits and Drawbacks","back":"Merits: adapts to changing requirements, delivers working software frequently, close user involvement. Drawbacks: less documentation, harder to estimate cost and time, needs an experienced, committed team."},{"id":"fc-1.2.3-008","topicId":"1.2.3","front":"Extreme Programming Practices","back":"Pair programming, test-driven development (write the tests first), small frequent releases, continuous integration, an on-site customer, simple design and constant refactoring."},{"id":"fc-1.2.3-009","topicId":"1.2.3","front":"RAD: Merits and Drawbacks","back":"Merits: quick prototypes, user feedback shapes each iteration, requirements can evolve. Drawbacks: prototypes can end up poorly structured, needs constant user input, less suited to large safety-critical systems."},{"id":"fc-1.2.3-010","topicId":"1.2.3","front":"Spiral Model: Merits and Drawbacks","back":"Merits: risk is analysed on every loop, suits large high-risk projects, prototypes appear early. Drawbacks: expensive, needs risk-assessment expertise, can loop indefinitely without firm deadlines."},{"id":"fc-1.2.3-011","topicId":"1.2.3","front":"Choosing a Methodology","back":"Fixed, well-understood requirements: waterfall. Unclear or changing requirements: agile, RAD or XP. Large and high-risk: spiral. Safety-critical with heavy documentation: waterfall."},{"id":"fc-1.2.3-012","topicId":"1.2.3","front":"Testing Across the Lifecycle","back":"Alpha (in-house), beta (real users before release), black box (inputs and outputs only), white box (code paths), unit, integration and acceptance testing. Agile tests continuously; waterfall tests in a phase."},{"id":"fc-1.2.3-013","topicId":"1.2.3","front":"Writing and Following Algorithms","back":"Design with pseudocode or a flowchart, then dry-run it with a trace table using normal, boundary and erroneous test data to check it meets the requirements before coding."},{"id":"fc-1.2.4-001","topicId":"1.2.4","front":"Programming Paradigms","back":"Different approaches to programming and computation (e.g. procedural, object-oriented), selected based on problem requirements."},{"id":"fc-1.2.4-002","topicId":"1.2.4","front":"Procedural Languages","back":"A high-level paradigm where code is organised into reusable procedures and functions, using defined data types and control structures."},{"id":"fc-1.2.4-003","topicId":"1.2.4","front":"Object-Oriented Languages","back":"A paradigm where programs use objects, instances of classes, encapsulating attributes and behaviors for modularity and reuse."},{"id":"fc-1.2.4-004","topicId":"1.2.4","front":"Classes","back":"A blueprint defining attributes and methods that objects of a specific type inherit and share."},{"id":"fc-1.2.4-005","topicId":"1.2.4","front":"Objects","back":"An instance of a class, holding specific attributes and behaviors as defined by its class."},{"id":"fc-1.2.4-006","topicId":"1.2.4","front":"Methods","back":"Functions or procedures within a class, defining the actions an object can perform."},{"id":"fc-1.2.4-007","topicId":"1.2.4","front":"Attributes","back":"Data variables within an object, representing its properties or state."},{"id":"fc-1.2.4-008","topicId":"1.2.4","front":"Encapsulation","back":"An OOP principle that hides an object's attributes, restricting direct access and enforcing interaction via methods. Setting an attribute to private achieves this."},{"id":"fc-1.2.4-009","topicId":"1.2.4","front":"Inheritance","back":"An OOP mechanism where a subclass inherits attributes and methods from a superclass, promoting code reusability, saving time."},{"id":"fc-1.2.4-010","topicId":"1.2.4","front":"Polymorphism","back":"An OOP feature allowing different classes to implement a shared method uniquely, enhancing flexibility and reuse. Allowing a class to inherit a method, but making that method do something slightly different."},{"id":"fc-1.2.4-011","topicId":"1.2.4","front":"Assembly Language","back":"A low-level language using mnemonics to represent machine code instructions, tied to specific hardware architecture."},{"id":"fc-1.2.4-012","topicId":"1.2.4","front":"Direct Addressing","back":"An addressing mode where the operand specifies the exact memory address of the data to be accessed."},{"id":"fc-1.2.4-013","topicId":"1.2.4","front":"Immediate Addressing","back":"An addressing mode where the operand is the literal value to be used directly, not a memory address."},{"id":"fc-1.2.4-014","topicId":"1.2.4","front":"Indexed Addressing","back":"An addressing mode where an index register modifies a base address to dynamically locate the operand in memory."},{"id":"fc-1.2.4-015","topicId":"1.2.4","front":"Indirect Addressing","back":"An addressing mode where the operand points to a memory location holding the address of the actual data."},{"id":"fc-1.3.1-001","topicId":"1.3.1","front":"Lossless Compression","back":"A compression technique that reduces file size without losing any original data, ensuring perfect reconstruction of the file. Run length encoding and dictionary coding are examples."},{"id":"fc-1.3.1-002","topicId":"1.3.1","front":"Lossy Compression","back":"A compression method that removes non-essential data, reducing file size but causing some loss of accuracy."},{"id":"fc-1.3.1-003","topicId":"1.3.1","front":"Dictionary Coding","back":"A lossless compression method that replaces repeating patterns of text with unique codes stored in a dictionary."},{"id":"fc-1.3.1-004","topicId":"1.3.1","front":"Run-Length Encoding","back":"A lossless compression technique that replaces sequences of repeating data (e.g. identical pixels in an image) with a single value and its repetition count."},{"id":"fc-1.3.1-005","topicId":"1.3.1","front":"Symmetric Encryption","back":"A technique where the same key is used for both encryption and decryption, requiring secure key exchange."},{"id":"fc-1.3.1-006","topicId":"1.3.1","front":"Asymmetric Encryption","back":"A cryptographic approach that uses a public key for encryption and a private key for decryption, improving security in communication. More suited to sensitive transactions of data compared to symmetric."},{"id":"fc-1.3.1-007","topicId":"1.3.1","front":"Hashing","back":"A one-way function that transforms data into a fixed-length value called a hash. Commonly used for password storage and data integrity verification. A good hash function should minimise collisions and ensure small changes to an input create large changes to a hash value."},{"id":"fc-1.3.2-001","topicId":"1.3.2","front":"Atomicity","back":"Guarantees that a transaction is treated as a single unit, either fully completing or having no effect at all."},{"id":"fc-1.3.2-002","topicId":"1.3.2","front":"Consistency","back":"Ensures that a database follows predefined validation rules, maintaining referential integrity after a transaction. Cascade delete and update are examples of how this can be achieved."},{"id":"fc-1.3.2-003","topicId":"1.3.2","front":"Isolation","back":"Prevents interference between concurrent transactions, ensuring they produce the same outcome as if executed sequentially. Record locking can be used to achieve this."},{"id":"fc-1.3.2-004","topicId":"1.3.2","front":"Durability","back":"Ensures that once a transaction is committed, its changes are permanently recorded, even in the event of a system failure. Immediately writing changes data in a record to secondary storage will achieve this."},{"id":"fc-1.3.2-005","topicId":"1.3.2","front":"Relational Databases","back":"A database structured using tables with relationships between them, commonly represented by primary and foreign keys."},{"id":"fc-1.3.2-006","topicId":"1.3.2","front":"Entity-Relationship Modelling","back":"A visual representation of data entities and their relationships, aiding in database design and minimising redundancy."},{"id":"fc-1.3.2-007","topicId":"1.3.2","front":"One-to-One Relationship","back":"A relationship where each record in one table is linked to exactly one record in another table, and vice versa, e.g. a person and their passport number, used for unique pairings."},{"id":"fc-1.3.2-008","topicId":"1.3.2","front":"One-to-Many Relationship","back":"A relationship where one record in a table can be linked to multiple records in another table, but not the reverse, e.g. one customer to many orders, common in relational databases."},{"id":"fc-1.3.2-009","topicId":"1.3.2","front":"Many-to-Many Relationship","back":"A relationship where multiple records in one table can link to multiple records in another. Effective database design should avoid this type of relationship."},{"id":"fc-1.3.2-010","topicId":"1.3.2","front":"Primary Key","back":"A unique identifier assigned to each record in a table, ensuring that no two rows have the same key."},{"id":"fc-1.3.2-011","topicId":"1.3.2","front":"Foreign Key","back":"A field in one table that links to the primary key of another table, establishing relationships between tables."},{"id":"fc-1.3.2-012","topicId":"1.3.2","front":"Secondary Key","back":"An additional attribute that can be used to index or retrieve records more efficiently than relying on the primary key alone."},{"id":"fc-1.3.2-013","topicId":"1.3.2","front":"Flat File Database","back":"A simple database that stores all data in a single table, with no relationships between different data entities."},{"id":"fc-1.3.2-014","topicId":"1.3.2","front":"Indexing","back":"Speeds up data retrieval by creating a separate data structure that maps primary keys to their corresponding records."},{"id":"fc-1.3.2-015","topicId":"1.3.2","front":"Record Locking","back":"A mechanism to prevent multiple users from simultaneously modifying the same data, avoiding inconsistencies."},{"id":"fc-1.3.2-016","topicId":"1.3.2","front":"Redundancy","back":"Unnecessary duplication of data within a database, which can lead to inefficiency and increased storage requirements."},{"id":"fc-1.3.2-017","topicId":"1.3.2","front":"Referential Integrity","back":"Ensures consistency between linked tables by preventing invalid or broken relationships between records."},{"id":"fc-1.3.2-018","topicId":"1.3.2","front":"Database Normalisation","back":"A process of organising a database to reduce redundancy and improve efficiency by dividing it into structured tables."},{"id":"fc-1.3.2-019","topicId":"1.3.2","front":"First Normal Form (1NF)","back":"A table where each column contains atomic values (one value only), there are no repeating records or duplicate field name, and each row is uniquely identifiable by a primary key, ensuring structured and efficient data storage."},{"id":"fc-1.3.2-020","topicId":"1.3.2","front":"Second Normal Form (2NF)","back":"Extends 1NF by ensuring that all non-key attributes are fully functionally dependent on the entire primary key."},{"id":"fc-1.3.2-021","topicId":"1.3.2","front":"Third Normal Form (3NF)","back":"Further refines 2NF by removing transitive dependencies, ensuring all non-key attributes depend only on the primary key."},{"id":"fc-1.3.3-001","topicId":"1.3.3","front":"Local Area Networks (LANs)","back":"A network that connects computers within a small geographic area, such as a school, home, or office."},{"id":"fc-1.3.3-002","topicId":"1.3.3","front":"Wide Area Networks (WANs)","back":"A network that spans a large geographical area, often using third-party carriers to link multiple locations."},{"id":"fc-1.3.3-003","topicId":"1.3.3","front":"Client-Server Network","back":"A network model where client devices request services from a central server that manages resources and processing. Central point of failure, knowledge, money and expertise needed to set up and maintain. Easy to manage updates, backups and security."},{"id":"fc-1.3.3-004","topicId":"1.3.3","front":"Peer-to-Peer Network","back":"A decentralised network where devices communicate directly and share resources without a dedicated central server. Easy to set up, but each device is responsible for its own security, backups and updates."},{"id":"fc-1.3.3-005","topicId":"1.3.3","front":"Circuit Switching","back":"A communication method where a dedicated path is established between two nodes for the duration of the connection, e.g. traditional telephone networks; ensures consistent data flow but does not make the most efficient use of available bandwidth."},{"id":"fc-1.3.3-006","topicId":"1.3.3","front":"Packet Switching","back":"A method of transmitting data by breaking it into packets that are sent independently over a network and reassembled at the destination, e.g. the internet; efficient for variable traffic but may introduce delays due to packet reordering."},{"id":"fc-1.3.3-007","topicId":"1.3.3","front":"Domain Name System (DNS)","back":"A hierarchical system that translates human-readable domain names into IP addresses to locate network resources, e.g. 'google.com' to 142.250.190.78."},{"id":"fc-1.3.3-008","topicId":"1.3.3","front":"Protocol Layering","back":"A networking concept that divides communication functions into layers, each with specific protocols, makes it easier for manufacturer to develop hardware and software for specific layers."},{"id":"fc-1.3.3-009","topicId":"1.3.3","front":"TCP/IP Stack","back":"A suite of protocols enabling reliable data transmission between networked computers, structured in four layers (Application, Transport, Internet, Link)."},{"id":"fc-1.3.3-010","topicId":"1.3.3","front":"Encryption","back":"The process of encoding data to prevent unauthorised access, ensuring only authorised recipients with the key can decrypt it."},{"id":"fc-1.3.3-011","topicId":"1.3.3","front":"Firewalls","back":"Security barriers that monitor and control network traffic based on rules to protect systems from unauthorised access, e.g. blocking malware; enhances security but may slow traffic."},{"id":"fc-1.3.3-012","topicId":"1.3.3","front":"Proxies","back":"A server that intercepts data packets to hide the source's network address, improving security and managing access, boosts privacy but can introduce latency."},{"id":"fc-1.3.3-013","topicId":"1.3.3","front":"IP Address","back":"A unique numerical identifier assigned to a network. Used by routers to route data packets between networks; operates at the network layer, enabling communication across the internet."},{"id":"fc-1.3.3-014","topicId":"1.3.3","front":"MAC Address","back":"A unique physical identifier hardcoded into a device's network interface card (NIC). Operates at the data link layer for local network communication, permanent but limited to LAN in scope."},{"id":"fc-1.3.4-001","topicId":"1.3.4","front":"HyperText Markup Language (HTML)","back":"A markup language used to structure and display content on the web, e.g, using

tags for paragraphs; simple to use but limited to static content."},{"id":"fc-1.3.4-002","topicId":"1.3.4","front":"Cascading Style Sheets (CSS)","back":"A styling language that controls the layout, appearance, and formatting of web pages, e.g. h1 { color: blue; } enhances design flexibility, can be written inline or external."},{"id":"fc-1.3.4-003","topicId":"1.3.4","front":"JavaScript","back":"An interpreted programming language that enables interactive and dynamic content in browsers, e.g. form validation; adds interactivity but increases client-side processing load. Can be disabled and modified."},{"id":"fc-1.3.4-004","topicId":"1.3.4","front":"Client-Side Processing","back":"Execution of scripts in the user's browser using local resources, e.g. JavaScript for animations; reduces server load but can be disabled or modified."},{"id":"fc-1.3.4-005","topicId":"1.3.4","front":"Server-Side Processing","back":"Execution of scripts on a web server to process requests and return dynamic results, offers more control but increases server demand. Can be used to revalidate client-side processing."},{"id":"fc-1.3.4-006","topicId":"1.3.4","front":"Search Engine Indexing","back":"The process of collecting, analysing, and storing web page data for fast retrieval by search engines. Improves search speed but requires constant updates."},{"id":"fc-1.3.4-007","topicId":"1.3.4","front":"PageRank Algorithm","back":"A ranking system by Google that determines webpage relevance based on link quantity and quality, e.g. authoritative sites rank higher; effective for relevance and ordering of search results."},{"id":"fc-1.3.4-008","topicId":"1.3.4","front":"Common HTML Tags","back":", , , <body>, <h1> to <h6>, <p>, <a href>, <img src alt>, <div>, <ul>/<ol>/<li>, <form>, <input>. The class and id attributes let CSS and JavaScript target elements."},{"id":"fc-1.3.4-009","topicId":"1.3.4","front":"CSS Selectors and Rules","back":"Element (p {}), class (.warning {}) and id (#header {}) selectors with properties such as color, background-color, font-family, border, margin and padding. CSS can be inline, internal in <style>, or an external .css file."},{"id":"fc-1.3.4-010","topicId":"1.3.4","front":"JavaScript in the Browser","back":"Runs client-side: variables, functions, if statements and loops; document.getElementById('x').value or .innerHTML reads and changes the page; alert() shows a message. Used for validation and updating pages without reloading."},{"id":"fc-1.3.4-011","topicId":"1.3.4","front":"Search Engine Indexing","back":"Crawlers (spiders) follow links, fetch pages and store their keywords, metadata and links in an index, so a search is answered from the index rather than by scanning the live web."},{"id":"fc-1.3.4-012","topicId":"1.3.4","front":"PageRank Formula","back":"PR(A) = (1 - d) + d x (PR(T1)/C(T1) + ... + PR(Tn)/C(Tn)), where d is the damping factor (about 0.85) and C(T) is the number of outbound links on page T. Pages linked from important pages rank higher."},{"id":"fc-1.4.1-001","topicId":"1.4.1","front":"Binary","back":"A number system using only 0s and 1s (base 2), fundamental to computer storage and processing, e.g. 0100 = 4 in denary; universal but less human-readable."},{"id":"fc-1.4.1-002","topicId":"1.4.1","front":"Denary","back":"A number system with 10 digits (0-9, base 10), used in everyday arithmetic, intuitive but inefficient for computers."},{"id":"fc-1.4.1-003","topicId":"1.4.1","front":"Hexadecimal","back":"A number system with 16 symbols (0-9, A-F, base 16), compact but less intuitive than denary. A = 10, B = 11…"},{"id":"fc-1.4.1-004","topicId":"1.4.1","front":"Boolean","back":"A data type storing TRUE (1) or FALSE (0) for logical operations and conditionals, e.g. 10 > 5 is TRUE."},{"id":"fc-1.4.1-005","topicId":"1.4.1","front":"Character","back":"A data type storing a single letter, number, or symbol."},{"id":"fc-1.4.1-006","topicId":"1.4.1","front":"String","back":"A sequence of characters stored as text in quotes, e.g. 'Hello'."},{"id":"fc-1.4.1-007","topicId":"1.4.1","front":"Integer","back":"A data type for whole numbers without decimals, e.g. -42 or 23."},{"id":"fc-1.4.1-008","topicId":"1.4.1","front":"Real/Floating Point","back":"A data type for numbers with decimals."},{"id":"fc-1.4.1-009","topicId":"1.4.1","front":"ASCII","back":"An 8-bit encoding standard for alphanumeric characters, e.g. 'A' = 65; widely used but limited to 256 characters."},{"id":"fc-1.4.1-010","topicId":"1.4.1","front":"UNICODE","back":"A universal encoding that extends on ASCII, supporting multiple languages with 16+ bits, versatile but uses more memory."},{"id":"fc-1.4.1-011","topicId":"1.4.1","front":"AND (∧)","back":"A logical operator returning TRUE (1) if all inputs are TRUE, e.g. 1 ∧ 1 = 1."},{"id":"fc-1.4.1-012","topicId":"1.4.1","front":"OR (∨)","back":"A logical operator returning TRUE (1) if any input is TRUE, e.g. 1 ∨ 0 = 1."},{"id":"fc-1.4.1-013","topicId":"1.4.1","front":"XOR (⊻)","back":"A logical operator returning TRUE (1) if exactly one input is TRUE, e.g. 1 ⊻ 0 = 1."},{"id":"fc-1.4.1-014","topicId":"1.4.1","front":"NOT (¬)","back":"A logical operator inverting a Boolean value, e.g. ¬1 = 0."},{"id":"fc-1.4.1-015","topicId":"1.4.1","front":"Bitwise Manipulation","back":"Operations on individual bits, e.g. Masks and shifts."},{"id":"fc-1.4.1-016","topicId":"1.4.1","front":"Shifts","back":"A bitwise operation moving bits left or right. The same as multiplying or dividing by 2 dependent on the direction."},{"id":"fc-1.4.1-017","topicId":"1.4.1","front":"Two's Complement","back":"A method representing negative numbers. Write the number out as a positive. From the right hand side, find the first bit that is a 1. Copy everything up to and including that 1. Flip all other bits to the left. MSB becomes negative."},{"id":"fc-1.4.1-018","topicId":"1.4.1","front":"Sign and Magnitude","back":"A method of representing signed numbers in binary where the most significant bit indicates the sign (0 for positive, 1 for negative) and the remaining bits represent the number."},{"id":"fc-1.4.1-019","topicId":"1.4.1","front":"Exponent","back":"The part of a number that specifies the number of times and direction to shift the floating point within the mantissa. Positive exponent, shift decimal to the right, negative, shift left. Allows large/small number representation but limited by bit size."},{"id":"fc-1.4.1-020","topicId":"1.4.1","front":"Mantissa","back":"In floating-point representation, the fractional part of a number in normalised binary form. 1.75 would be 01.11."},{"id":"fc-1.4.1-021","topicId":"1.4.1","front":"Normalisation in Binary","back":"A method to store real numbers in binary using a mantissa and exponent where normalisation adjusts the mantissa to start with 10 for negative numbers, 01 for positive, ensures unique representation and maximises precision."},{"id":"fc-1.4.1-022","topicId":"1.4.1","front":"Floating Point Arithmetic","back":"Operations on decimal binary numbers. Using the exponent to calculate where the decimal place needs to move to within a sequence of a binary."},{"id":"fc-1.4.2-001","topicId":"1.4.2","front":"Arrays","back":"A data structure storing a finite, ordered collection of same data type elements under one identifier, accessed by index. Fast access but fixed size. Contiguous meaning data exists together in memory."},{"id":"fc-1.4.2-002","topicId":"1.4.2","front":"Lists","back":"A data structure maintaining a sequence of elements by index, dynamic in size and can hold multiple data types."},{"id":"fc-1.4.2-003","topicId":"1.4.2","front":"Linked Lists","back":"A dynamic structure where nodes store data and a pointer to the next, easy to modify but slow traversal. Memory intensive due to use of pointers. Non contiguous meaning data can exists anywhere in memory."},{"id":"fc-1.4.2-004","topicId":"1.4.2","front":"Tuples","back":"An ordered, immutable collection of mixed data types, e.g. (1, 'hello', 3.14); stable but immutable."},{"id":"fc-1.4.2-005","topicId":"1.4.2","front":"Records","back":"A structure grouping related fields into one unit, e.g. {name: 'Alice', age: 16}."},{"id":"fc-1.4.2-006","topicId":"1.4.2","front":"Stacks","back":"A LIFO structure where the last item added is removed first."},{"id":"fc-1.4.2-007","topicId":"1.4.2","front":"Queues","back":"A FIFO structure where the first item added is removed first."},{"id":"fc-1.4.2-008","topicId":"1.4.2","front":"Circular Queues","back":"A dynamic queue structure where the end connects to the beginning, reusing space via wrapping front and rear pointers."},{"id":"fc-1.4.2-009","topicId":"1.4.2","front":"Trees","back":"A hierarchical structure of nodes with a root and children, e.g file systems."},{"id":"fc-1.4.2-010","topicId":"1.4.2","front":"Binary Search Tree","back":"A tree with at most two children per node, left smaller, right larger, fast to search, but data needs to be ordered."},{"id":"fc-1.4.2-011","topicId":"1.4.2","front":"Graphs","back":"A structure of nodes and edges for relationships, e.g social network relationships; versatile but memory-heavy."},{"id":"fc-1.4.2-012","topicId":"1.4.2","front":"Directed Graphs","back":"A graph with one-way edges, e.g. A → B."},{"id":"fc-1.4.2-013","topicId":"1.4.2","front":"Undirected Graphs","back":"A graph with bidirectional edges, e.g. A ↔ B."},{"id":"fc-1.4.2-014","topicId":"1.4.2","front":"Breadth First Traversal","back":"A graph traversal exploring neighbors first, using a queue, e.g. level-by-level."},{"id":"fc-1.4.2-015","topicId":"1.4.2","front":"Depth First Traversal","back":"A graph traversal going deep before backtracking, using a stack, e.g. branch exploration."},{"id":"fc-1.4.2-016","topicId":"1.4.2","front":"Hash Table","back":"A structure mapping inputs to indexes via a hash function, fast retrieval but collision risk."},{"id":"fc-1.4.2-017","topicId":"1.4.2","front":"Indexing","back":"A technique creating a index for fast data retrieval, speeds up queries/searching a database."},{"id":"fc-1.4.2-018","topicId":"1.4.2","front":"Dynamic Data Structures","back":"A structure that grows or shrinks at runtime, e.g. linked lists; adaptable but complex to manage."},{"id":"fc-1.4.3-001","topicId":"1.4.3","front":"Boolean Logic","back":"A branch of algebra where logical operators (AND, OR, NOT) are used to process true or false values, underpinning digital circuits."},{"id":"fc-1.4.3-002","topicId":"1.4.3","front":"Boolean Expressions","back":"An expression composed of Boolean variables and logical operators that evaluates to either TRUE or FALSE, e.g. A ∧ B ∨ ¬C."},{"id":"fc-1.4.3-003","topicId":"1.4.3","front":"Association Laws","back":"Rules stating that the grouping of terms does not affect the result: A ∧ (B ∧ C) = (A ∧ B) ∧ C and A ∨ (B ∨ C) = (A ∨ B) ∨ C, simplifying expressions."},{"id":"fc-1.4.3-004","topicId":"1.4.3","front":"Commutation Laws","back":"Rules stating that the order of operands does not affect the result: A ∧ B = B ∧ A and A ∨ B = B ∨ A, showing symmetry in logic."},{"id":"fc-1.4.3-005","topicId":"1.4.3","front":"Distribution Laws","back":"Rules defining how AND and OR operations distribute: A ∧ (B ∨ C) = (A ∧ B) ∨ (A ∧ C) and A ∨ (B ∧ C) = (A ∨ B) ∧ (A ∨ C), key for simplification."},{"id":"fc-1.4.3-006","topicId":"1.4.3","front":"De Morgan's First Law","back":"The negation of a disjunction is the conjunction of the negations: ¬(A ∨ B) = ¬A ∧ ¬B, used in circuit design and proofs."},{"id":"fc-1.4.3-007","topicId":"1.4.3","front":"De Morgan's Second Law","back":"The negation of a conjunction is the disjunction of the negations: ¬(A ∧ B) = ¬A ∨ ¬B, essential for logical equivalence."},{"id":"fc-1.4.3-008","topicId":"1.4.3","front":"Double Negation Law","back":"States that negating a value twice results in the original value: A = ¬¬A, simplifying negated expressions."},{"id":"fc-1.4.3-009","topicId":"1.4.3","front":"D-Type Flip Flops","back":"A sequential circuit that stores a single bit of data, switching states on a clock edge based on input, e.g. used in registers."},{"id":"fc-1.4.3-010","topicId":"1.4.3","front":"Half Adders","back":"A combinational circuit that adds two single-bit binary numbers, outputting a sum bit and a carry bit, e.g. 1 + 1 = 10 (sum 0, carry 1)."},{"id":"fc-1.4.3-011","topicId":"1.4.3","front":"Full Adders","back":"A combinational circuit that adds three bits (including a carry input), producing a sum and carry output, e.g. 1 + 1 + 1 = 11 (sum 1, carry 1)."},{"id":"fc-1.4.3-012","topicId":"1.4.3","front":"Karnaugh Maps","back":"A visual technique for simplifying Boolean expressions by grouping 1s in a grid to minimise logical operations, e.g. reducing A ∧ B ∨ A ∧ ¬B to A."},{"id":"fc-1.4.3-013","topicId":"1.4.3","front":"Logic Gate Diagrams","back":"Graphical representations of Boolean expressions using standard symbols for logic gates (AND, OR, NOT), e.g. A ∧ B as an AND gate."},{"id":"fc-1.5.1-001","topicId":"1.5.1","front":"Computer Misuse Act (1990)","back":"A UK law introduced in 1990 to combat unauthorised computer activities, prohibiting actions like hacking and malware distribution, e.g. penalties up to 7 years for illegal access; protects digital systems and data security but struggles with evolving cyber threats."},{"id":"fc-1.5.1-002","topicId":"1.5.1","front":"Unauthorised Access","back":"Defines and criminalises gaining access to computer material without proper permission, e.g. hacking into a system, punishable by up to 7 years."},{"id":"fc-1.5.1-003","topicId":"1.5.1","front":"Cybercrimes","back":"Covers activities such as hacking, malware distribution, and digital fraud, addressed under the Act to protect systems and data."},{"id":"fc-1.5.1-004","topicId":"1.5.1","front":"Electronic Vandalism","back":"Makes it illegal to modify data or interfere with computer systems without consent, e.g. deleting files or spreading viruses."},{"id":"fc-1.5.1-005","topicId":"1.5.1","front":"Information Theft","back":"Prohibits the unlawful acquisition of personal or confidential data through digital means, e.g. stealing login credentials."},{"id":"fc-1.5.1-006","topicId":"1.5.1","front":"Copyright, Designs and Patents Act (1988)","back":"A UK law from 1988 protecting intellectual property like software, music, and designs. Copyright is automatic. Permission can be granted by the creator or purchased if the creator chooses."},{"id":"fc-1.5.1-007","topicId":"1.5.1","front":"Intellectual Property Protection","back":"Establishes legal ownership rights for literary, dramatic, musical, and artistic works, including software, preventing unauthorised use."},{"id":"fc-1.5.1-008","topicId":"1.5.1","front":"Copyright Duration","back":"Ensures copyright protection for 70 years after the creator's death or creation if anonymous, e.g. software protected until 2095 if created in 2025."},{"id":"fc-1.5.1-009","topicId":"1.5.1","front":"Illegal Distribution","back":"Prevents the unauthorised copying or sharing of protected works, e.g. pirating software or music, with fines or imprisonment."},{"id":"fc-1.5.1-010","topicId":"1.5.1","front":"Digital Copyright","back":"Applies copyright laws to digital content, including music, films, and software, e.g. protecting a downloaded game from being copied."},{"id":"fc-1.5.1-011","topicId":"1.5.1","front":"Data Protection Act (2018 - UK GDPR)","back":"A UK law from 2018, aligned with GDPR, regulating personal data processing, storage, and access, e.g. requires consent for data collection; ensures privacy and user rights but imposes compliance costs on organisations."},{"id":"fc-1.5.1-012","topicId":"1.5.1","front":"Regulation","back":"Determines how personal data is processed, stored, and accessed, aligning with GDPR to ensure lawful handling, e.g. consent for data collection."},{"id":"fc-1.5.1-013","topicId":"1.5.1","front":"User Rights","back":"Introduces strict guidelines for users to access, modify, and delete their personal data, e.g. right to erasure or data portability."},{"id":"fc-1.5.1-014","topicId":"1.5.1","front":"Security Requirements","back":"Mandates data controllers and processors to ensure data is protected, e.g. encryption or secure storage to prevent breaches."},{"id":"fc-1.5.1-015","topicId":"1.5.1","front":"Accountability","back":"Requires organisations to justify and document data collection and processing practices, e.g. maintaining records for audits."},{"id":"fc-1.5.1-016","topicId":"1.5.1","front":"Regulation of Investigatory Powers Act (2000)","back":"A UK law from 2000 allowing authorised surveillance and interception of communications for security, e.g. monitoring emails with warrants; enhances public safety but raises privacy concerns with oversight challenges."},{"id":"fc-1.5.1-017","topicId":"1.5.1","front":"Surveillance Powers","back":"Grants government bodies the authority to monitor electronic communications with warrants, e.g. for national security."},{"id":"fc-1.5.1-018","topicId":"1.5.1","front":"Interception of Communications","back":"Allows agencies to intercept phone calls, emails, and internet activity with proper authorisation, e.g. tracking terrorism suspects."},{"id":"fc-1.5.1-019","topicId":"1.5.1","front":"Data Access","back":"Permits access to encrypted communications and stored data for national security purposes, e.g. requiring decryption keys from providers."},{"id":"fc-1.5.1-020","topicId":"1.5.1","front":"Public Safety & Privacy","back":"Balances law enforcement capabilities with individual rights and privacy protections, e.g. oversight by judicial bodies."},{"id":"fc-1.5.2-001","topicId":"1.5.2","front":"Artificial Intelligence & Bias","back":"Examines ethical concerns in AI to ensure fairness, e.g. biased hiring algorithms misjudging candidates; promotes equitable decision-making but challenging to eliminate bias due to data or design flaws."},{"id":"fc-1.5.2-002","topicId":"1.5.2","front":"Automation & Job Loss","back":"Assesses the social and economic impact of automation replacing human tasks, e.g. self-checkouts reducing cashier jobs; increases productivity but leads to workforce displacement and retraining needs."},{"id":"fc-1.5.2-003","topicId":"1.5.2","front":"Privacy Issues","back":"Addresses ethical risks of data collection and consent in digital systems, e.g. tracking via cookies without user approval; safeguards personal autonomy but weak enforcement hinders protection."},{"id":"fc-1.5.2-004","topicId":"1.5.2","front":"Environmental Impact","back":"Evaluates the ecological consequences of computing, e.g. e-waste from obsolete devices; encourages sustainable tech practices but high implementation costs delay progress."},{"id":"fc-1.5.2-005","topicId":"1.5.2","front":"Digital Divide","back":"Explores social inequity in technology access, e.g. rural areas lacking broadband vs. urban connectivity; fosters inclusion through wider access but resource demands slow efforts."},{"id":"fc-1.5.2-006","topicId":"1.5.2","front":"Monitor Behaviour","back":"Involves using computers to ethically track actions, e.g. CCTV for security; enhances public safety but risks privacy invasion if unregulated."},{"id":"fc-1.5.2-007","topicId":"1.5.2","front":"Analyse Personal Information","back":"Processing personal data with ethical oversight, e.g. medical records improving healthcare; enhances service quality but risks misuse if data security fails."},{"id":"fc-1.5.2-008","topicId":"1.5.2","front":"Piracy and Offensive Communications","back":"Addresses ethical and legal issues of illegal copying and harmful content, e.g. pirated software or hate speech; protects intellectual rights and social harmony but control is difficult online."},{"id":"fc-1.5.2-009","topicId":"1.5.2","front":"Layout, Colour Paradigms and Character Sets","back":"Considers cultural influences on software design, e.g. red symbolising danger in the West, luck in China; improves user experience through cultural adaptation but increases design complexity."},{"id":"fc-1.5.2-010","topicId":"1.5.2","front":"Computers in the Workforce","back":"Opportunities: safer, cheaper and round-the-clock production, new technical jobs, remote working. Risks: job losses and deskilling, need for retraining, workers monitored, a widening digital divide."},{"id":"fc-1.5.2-011","topicId":"1.5.2","front":"Automated Decision Making","back":"Computers making decisions without a human, e.g. loan approval or self-driving cars. Fast and consistent, but can inherit bias from training data, be hard to explain, and leave accountability unclear."},{"id":"fc-1.5.2-012","topicId":"1.5.2","front":"Censorship and the Internet","back":"Governments or ISPs blocking content. For: protects people from illegal or harmful material. Against: restricts free speech, can hide legitimate information and be misused for political control."},{"id":"fc-2.1.1-001","topicId":"2.1.1","front":"Abstraction","back":"Simplifying a problem by focusing on essential details and removing irrelevant ones, reduces complexity for design but may overlook context-specific details."},{"id":"fc-2.1.1-002","topicId":"2.1.1","front":"Data Abstraction","back":"Representing data based on its logical behavior and operations, hiding implementation, e.g. stacks with push/pop."},{"id":"fc-2.1.1-003","topicId":"2.1.1","front":"Graph Theory","back":"Using abstract models of nodes and edges to solve complex problems, e.g. shortest path in a network; enables efficient problem-solving."},{"id":"fc-2.1.1-004","topicId":"2.1.1","front":"Abstraction vs Reality","back":"Distinguishing simplified models from real-world complexity, e.g, a map omits minor roads; abstraction aids focus but loses fine detail."},{"id":"fc-2.1.1-005","topicId":"2.1.1","front":"Representational Abstraction","back":"Removing unnecessary detail so that only the features needed for the problem remain, e.g. the London Underground map shows connections between stations but not real distances."},{"id":"fc-2.1.1-006","topicId":"2.1.1","front":"Abstraction by Generalisation","back":"Grouping similar things under a common concept by their shared characteristics, e.g. treating cars, vans and lorries as 'vehicles' in a car park system, or a class hierarchy in OOP."},{"id":"fc-2.1.1-007","topicId":"2.1.1","front":"Procedural Abstraction","back":"Using a procedure or function without needing to know how it works inside, e.g. calling sort(). The implementation is hidden behind its interface."},{"id":"fc-2.1.1-008","topicId":"2.1.1","front":"Need for Abstraction","back":"Reduces complexity so problems are easier to understand and solve; programs are smaller and faster to write; programmers work at a high level without hardware detail; models can be reused."},{"id":"fc-2.1.1-009","topicId":"2.1.1","front":"Abstract Model","back":"A simplified representation of a real situation that keeps only the essential features, e.g. a traffic simulation that models cars as points moving along a network of roads."},{"id":"fc-2.1.1-010","topicId":"2.1.1","front":"Devising an Abstract Model","back":"Decide the purpose, identify the entities and attributes that matter, discard irrelevant detail, choose data structures (e.g. a graph for a road network) and define the operations needed."},{"id":"fc-2.1.1-011","topicId":"2.1.1","front":"Layers of Abstraction","back":"Systems are built in layers, each hiding the one below: the TCP/IP stack, or high-level language, assembly language and machine code. Each layer only needs the interface to the next."},{"id":"fc-2.1.1-012","topicId":"2.1.1","front":"Example: Chess Program","back":"Board as a 2D array, pieces as objects with a type and position; ignores the material and size of the physical set, the players' names and the time of day."},{"id":"fc-2.1.2-001","topicId":"2.1.2","front":"Caching","back":"Storing frequently accessed data in fast memory for quicker retrieval, e.g. browser caching images; speeds up performance but consumes memory."},{"id":"fc-2.1.2-002","topicId":"2.1.2","front":"Inputs","back":"Data required for a system to process an algorithm, e.g. user form data; defines system scope but incorrect inputs lead to errors."},{"id":"fc-2.1.2-003","topicId":"2.1.2","front":"Outputs","back":"Results produced after processing inputs, e.g. a sorted list from an algorithm."},{"id":"fc-2.1.2-004","topicId":"2.1.2","front":"Preconditions","back":"Conditions required before execution to ensure correct outcomes, e.g. non-empty array for search."},{"id":"fc-2.1.2-005","topicId":"2.1.2","front":"Reusable Program Components","back":"Pre-written, tested code reused across programs, e.g. a sorting function; accelerates development and reliability but may need adaptation for specific use cases."},{"id":"fc-2.1.2-006","topicId":"2.1.2","front":"Identifying Inputs and Outputs","back":"Inputs are the data a solution needs from users, sensors, files or other programs; outputs are the results it produces on screen, in files or as signals. Listing them first defines the scope of the problem."},{"id":"fc-2.1.2-007","topicId":"2.1.2","front":"Benefits of Caching","back":"Frequently used data or instructions are kept in fast memory so they can be reused without recomputing or refetching: faster responses, less network and disk traffic, less processor work."},{"id":"fc-2.1.2-008","topicId":"2.1.2","front":"Drawbacks of Caching","back":"Cached data can become stale or out of date; it uses memory; deciding what to cache is difficult; a cache miss adds overhead; sensitive data held in a cache is a security risk."},{"id":"fc-2.1.2-009","topicId":"2.1.2","front":"Web Caching Example","back":"A browser stores a site's images and CSS so revisits load faster; a server caches the results of common database queries so many users get the same page without re-running the query."},{"id":"fc-2.1.2-010","topicId":"2.1.2","front":"Reusable Components: Benefits","back":"Already written and tested so fewer bugs; saves development time and cost; behaviour is consistent across programs. Examples: libraries, APIs, classes and functions."},{"id":"fc-2.1.2-011","topicId":"2.1.2","front":"Reusable Components: Drawbacks","back":"May not match the exact requirements; can be larger or slower than a custom solution; relies on a third party for updates and security fixes; may carry licensing costs."},{"id":"fc-2.1.2-012","topicId":"2.1.2","front":"Preconditions in Practice","back":"A precondition states what must be true before a procedure is called, e.g. the list is sorted before a binary search. Either document it for the caller or check it in code and handle failures."},{"id":"fc-2.1.3-001","topicId":"2.1.3","front":"Procedural Abstraction","back":"Breaking a problem into sequential steps with specific functions, e.g. recipe steps; structures solutions but requires clear step definition."},{"id":"fc-2.1.3-002","topicId":"2.1.3","front":"Components of a Problem","back":"Dividing a problem into modular, testable sub-procedures, e.g. login and display modules; enhances manageability but increases initial planning."},{"id":"fc-2.1.3-003","topicId":"2.1.3","front":"Decomposition","back":"Breaking a large problem into smaller sub-problems that are easier to understand, solve and test. Repeat until each part is simple enough to implement as a single sub-procedure."},{"id":"fc-2.1.3-004","topicId":"2.1.3","front":"Sub-procedure","back":"A named block of code (procedure or function) that solves one sub-problem, e.g. validateLogin(). It can be written and tested separately, reused, and called from the main program."},{"id":"fc-2.1.3-005","topicId":"2.1.3","front":"Components of a Solution","back":"The sub-procedures, data structures and interfaces that together solve the problem. For a quiz program: load questions, ask a question, check the answer, update the score, show results."},{"id":"fc-2.1.3-006","topicId":"2.1.3","front":"Order of Steps","back":"Some steps depend on earlier ones (a file must be opened before it is read), so their sequence is fixed. Independent steps can be ordered for clarity or even run concurrently."},{"id":"fc-2.1.3-007","topicId":"2.1.3","front":"Top-down Design","back":"Start with the overall problem and refine it step by step into smaller sub-problems, producing a hierarchy of procedures that can be implemented one at a time."},{"id":"fc-2.1.3-008","topicId":"2.1.3","front":"Structure (Hierarchy) Chart","back":"A diagram showing how a program is broken into modules and sub-modules, which module calls which, and the data passed between them."},{"id":"fc-2.1.3-009","topicId":"2.1.3","front":"Benefits of Thinking Procedurally","back":"Easier to plan, test and debug; work can be shared across a team; sub-procedures can be reused in other programs; changes are contained within one module."},{"id":"fc-2.1.3-010","topicId":"2.1.3","front":"Interface of a Sub-procedure","back":"The parameters it accepts and the value it returns. Defining interfaces clearly lets modules be developed and tested independently."},{"id":"fc-2.1.3-011","topicId":"2.1.3","front":"Example: Checkout Sub-procedures","back":"scanItem(), applyDiscount(), calculateTotal(), takePayment() and printReceipt(), each a separate sub-procedure called in order by the main program."},{"id":"fc-2.1.3-012","topicId":"2.1.3","front":"Prerequisite Step","back":"A step that must be completed before another can begin, e.g. input must be validated before it is stored. Identifying prerequisites determines the order of the steps."},{"id":"fc-2.1.4-001","topicId":"2.1.4","front":"Flowcharts","back":"Diagrams visually representing a program's logical flow with decision points, e.g. diamond for if-then-else."},{"id":"fc-2.1.4-002","topicId":"2.1.4","front":"Logical Conditions","back":"Boolean statements guiding program flow via control structures, e.g. x > 0."},{"id":"fc-2.1.4-003","topicId":"2.1.4","front":"Decision Points in a Solution","back":"Moments where a program chooses paths based on conditions, e.g. if x > 0."},{"id":"fc-2.1.4-004","topicId":"2.1.4","front":"Selection (Branching)","back":"A construct where the program chooses between paths based on a Boolean condition: if / elseif / else, or switch/case when comparing one value against several options."},{"id":"fc-2.1.4-005","topicId":"2.1.4","front":"Boolean Operators in Conditions","back":"AND, OR and NOT combine simple conditions, e.g. if age >= 18 AND hasID then allow entry. Brackets and the order of evaluation change the result."},{"id":"fc-2.1.4-006","topicId":"2.1.4","front":"Nested Decisions","back":"A decision placed inside another decision; the inner condition is only tested if the outer one is true. Reduce deep nesting with elseif or by combining conditions."},{"id":"fc-2.1.4-007","topicId":"2.1.4","front":"Decisions and Program Flow","back":"Each decision point splits the flow into alternative paths. Tracing which path is taken for given inputs predicts the output and reveals logic errors."},{"id":"fc-2.1.4-008","topicId":"2.1.4","front":"Loop Conditions","back":"Decisions that control iteration: while checks the condition before each pass, do-until (repeat) checks after so the body runs at least once, for counts a fixed number of times."},{"id":"fc-2.1.4-009","topicId":"2.1.4","front":"Trace Table","back":"A table recording the value of each variable and condition line by line as an algorithm runs. Used to follow logic, test decisions and find errors."},{"id":"fc-2.1.4-010","topicId":"2.1.4","front":"Validation as a Decision","back":"Checking that input meets rules (presence, range, type, length, format) before it is used. The decision determines whether to accept it, reject it or ask again."},{"id":"fc-2.1.4-011","topicId":"2.1.4","front":"Comparison Operators","back":"== equal to, != not equal to, <, <=, >, >=. Writing = (assignment) instead of == (comparison) in a condition is a common logic error in OCR pseudocode."},{"id":"fc-2.1.4-012","topicId":"2.1.4","front":"Flowchart Decision Symbol","back":"A diamond containing the condition, with labelled Yes/No (True/False) exits showing how the outcome of the decision affects the flow of the program."},{"id":"fc-2.1.5-001","topicId":"2.1.5","front":"Concurrent Processing","back":"Running multiple tasks simultaneously to boost efficiency, e.g. multi-threading in games; improves performance but not all tasks can be run concurrently."},{"id":"fc-2.1.5-002","topicId":"2.1.5","front":"Concurrent vs Parallel Processing","back":"Concurrent: several tasks make progress in overlapping time periods, e.g. time-sliced on one core. Parallel: tasks execute at the same instant on multiple cores or processors. Parallel processing is one way to achieve concurrency."},{"id":"fc-2.1.5-003","topicId":"2.1.5","front":"Thread","back":"A single sequence of instructions inside a process that can be scheduled on its own. Threads of the same process share memory, so they can work concurrently on the same data."},{"id":"fc-2.1.5-004","topicId":"2.1.5","front":"Identifying Parts That Can Run Concurrently","back":"Look for parts of a problem that do not depend on each other's results, e.g. downloading several files or applying a filter to different regions of an image. A task that needs another's output must wait for it."},{"id":"fc-2.1.5-005","topicId":"2.1.5","front":"Dependency Between Tasks","back":"When one task needs the result of another before it can start, e.g. data must be sorted before a binary search. Dependencies limit which parts of a problem can be tackled at the same time."},{"id":"fc-2.1.5-006","topicId":"2.1.5","front":"Benefits of Concurrent Processing","back":"Independent tasks finish sooner; makes use of every core; programs stay responsive (a UI thread keeps working while a file loads); many users can be served at once, e.g. a ticketing website."},{"id":"fc-2.1.5-007","topicId":"2.1.5","front":"Trade-offs of Concurrent Processing","back":"Overhead of creating and coordinating threads; harder to write, test and debug; shared data must be protected, which can slow things down; not every problem can be split; results may need recombining."},{"id":"fc-2.1.5-008","topicId":"2.1.5","front":"Race Condition","back":"A bug where the result depends on the timing of two concurrent tasks using shared data, e.g. two threads both read a balance of 100 and each add 10, leaving 110 instead of 120."},{"id":"fc-2.1.5-009","topicId":"2.1.5","front":"Deadlock","back":"Two or more tasks each wait for a resource held by the other, so none can continue. Avoided by acquiring locks in a fixed order, using timeouts, or never holding more than one lock at a time."},{"id":"fc-2.1.5-010","topicId":"2.1.5","front":"Lock (Mutual Exclusion)","back":"A mechanism that allows only one thread to use a shared resource at a time; others wait until it is released. Prevents race conditions but can create bottlenecks and deadlock if misused."},{"id":"fc-2.1.5-011","topicId":"2.1.5","front":"Concurrency in a Multi-user System","back":"Each user's request is handled at the same time for speed, but shared data such as a seat count must be locked or updated atomically so the same seat is never sold twice."},{"id":"fc-2.1.5-012","topicId":"2.1.5","front":"When Concurrency Is Not Worth It","back":"Gains are limited by the sequential parts of a problem and by coordination costs. For small tasks the overhead of setting up threads can make a concurrent solution slower than a sequential one."},{"id":"fc-2.2.1-001","topicId":"2.2.1","front":"Branching","back":"A control structure selecting paths based on Boolean conditions, e.g. if x > 0 print 'positive'; enables decisions but complex nesting reduces readability."},{"id":"fc-2.2.1-002","topicId":"2.2.1","front":"Functions","back":"Reusable subroutines returning a value, e.g. def add(a, b): return a + b; promotes modularity."},{"id":"fc-2.2.1-003","topicId":"2.2.1","front":"Global Variables","back":"Variables declared globally, accessible anywhere, e.g. score = 0; simplifies access but risks unintended changes."},{"id":"fc-2.2.1-004","topicId":"2.2.1","front":"Integrated Development Environment (IDE)","back":"A tool aiding coding with debugging and testing features, streamlines development."},{"id":"fc-2.2.1-005","topicId":"2.2.1","front":"Iterations","back":"Repeating code until a condition or count is met, e.g. while loop; automates repetition but risks infinite loops."},{"id":"fc-2.2.1-006","topicId":"2.2.1","front":"Local Variables","back":"Variables scoped to a subroutine, e.g. temp in a function; reduces conflicts but limits scope."},{"id":"fc-2.2.1-007","topicId":"2.2.1","front":"Modularity","back":"Dividing a program into reusable modules, e.g. input/processing files; enhances maintenance but requires planning."},{"id":"fc-2.2.1-008","topicId":"2.2.1","front":"Parameter Passing by Reference","back":"Passing a variable's address to modify it, e.g. altering a list; efficient but risks accidental overwriting of original variable."},{"id":"fc-2.2.1-009","topicId":"2.2.1","front":"Parameter Passing by Value","back":"Passing a copy of a variable, safe but memory-intensive."},{"id":"fc-2.2.1-010","topicId":"2.2.1","front":"Parameters","back":"Inputs to functions/procedures, e.g. x, y in multiply(x, y); customises behavior but requires correct passing."},{"id":"fc-2.2.1-011","topicId":"2.2.1","front":"Procedures","back":"Code blocks performing tasks without return, e.g. def print_message(); organizes logic but no output."},{"id":"fc-2.2.1-012","topicId":"2.2.1","front":"Recursion","back":"A function calling itself with a base case; elegant but memory intensive."},{"id":"fc-2.2.1-013","topicId":"2.2.1","front":"Sequences","back":"Executing statements in order, e.g. print 'A' then 'B'."},{"id":"fc-2.2.1-014","topicId":"2.2.1","front":"Subroutines","back":"Independent code performing tasks, e.g. calculate_total()."},{"id":"fc-2.2.2-001","topicId":"2.2.2","front":"Backtracking","back":"Exploring paths and retreating from dead-ends, e.g. maze solving; finds solutions but slow for large problems."},{"id":"fc-2.2.2-002","topicId":"2.2.2","front":"Computable Problems","back":"Problems solvable with finite steps, e.g. sorting; enables automation but excludes undecidable issues."},{"id":"fc-2.2.2-003","topicId":"2.2.2","front":"Computational Methods","back":"Algorithmic techniques for problem-solving."},{"id":"fc-2.2.2-004","topicId":"2.2.2","front":"Data Mining","back":"Extracting patterns from large datasets, e.g. sales trends; reveals insights but computationally intensive."},{"id":"fc-2.2.2-005","topicId":"2.2.2","front":"Divide and Conquer","back":"Splitting problems into sub-problems, e.g. merge sort."},{"id":"fc-2.2.2-006","topicId":"2.2.2","front":"Heuristics","back":"Approximating solutions for complex problems, e.g. A* pathfinding; fast but not always optimal."},{"id":"fc-2.2.2-007","topicId":"2.2.2","front":"Performance Modelling","back":"Simulating system behavior under conditions, e.g. network load; predicts performance, not always accurate."},{"id":"fc-2.2.2-008","topicId":"2.2.2","front":"Problem Decomposition","back":"Breaking problems into manageable parts, e.g. game graphics/logic."},{"id":"fc-2.2.2-009","topicId":"2.2.2","front":"Problem Recognition","back":"Identifying solution patterns, understanding common inputs, processes and outputs."},{"id":"fc-2.2.2-010","topicId":"2.2.2","front":"Visualisation","back":"Using diagrams to model algorithms, e.g, flowcharts; aids understanding but time-consuming."},{"id":"fc-2.2.2-011","topicId":"2.2.2","front":"Pipelining","back":"Splitting a process into stages so that different items are at different stages at the same time, like a production line; e.g. the CPU fetching one instruction while decoding another. Increases throughput."},{"id":"fc-2.2.2-012","topicId":"2.2.2","front":"Abstraction in Computational Methods","back":"Stripping a problem down to a model a computer can solve, e.g. representing delivery routes as a weighted graph so that Dijkstra's algorithm can find the shortest path."},{"id":"fc-2.3.1-001","topicId":"2.3.1","front":"A* Algorithm","back":"An informed search estimating shortest paths with distance and cost, e.g. game pathfinding; efficient but heuristic-dependent. A good enough approach to pathfinding."},{"id":"fc-2.3.1-002","topicId":"2.3.1","front":"Big O Notation","back":"Classifying efficiency by worst-case time/space complexity. Describes the time and space complexity of a given algorithm based on the size of the input/dataset."},{"id":"fc-2.3.1-003","topicId":"2.3.1","front":"Binary Search","back":"A logarithmic search dividing sorted lists, O(log n); fast but requires data to be sorted first."},{"id":"fc-2.3.1-004","topicId":"2.3.1","front":"Bubble Sort","back":"Swapping adjacent elements until sorted, O(n²), simple but slow for large data sets."},{"id":"fc-2.3.1-005","topicId":"2.3.1","front":"Dijkstra's Shortest Path Algorithm","back":"Finding shortest paths by exploring all options, e.g. network routing; optimal but slow for large graphs."},{"id":"fc-2.3.1-006","topicId":"2.3.1","front":"Insertion Sort","back":"Building a sorted list incrementally, O(n²), intuitive but inefficient for data that has no order to it already."},{"id":"fc-2.3.1-007","topicId":"2.3.1","front":"Linear Search","back":"Checking each item sequentially, O(n), simple but slow."},{"id":"fc-2.3.1-008","topicId":"2.3.1","front":"Merge Sort","back":"Dividing and merging sublists, O(n log n), efficient but space-heavy."},{"id":"fc-2.3.1-009","topicId":"2.3.1","front":"O(1) (Constant Time/Space)","back":"Fixed time/space regardless of input, e.g. array access; fastest but rare in algorithm design."},{"id":"fc-2.3.1-010","topicId":"2.3.1","front":"O(2ⁿ) (Exponential Time/Space)","back":"Exponential growth with input, e.g. recursive Fibonacci; powerful but impractical."},{"id":"fc-2.3.1-011","topicId":"2.3.1","front":"O(log(n)) (Logarithmic Time/Space)","back":"Logarithmic growth, e.g. binary search; scalable but needs structure."},{"id":"fc-2.3.1-012","topicId":"2.3.1","front":"O(n) (Linear Time/Space)","back":"Proportional growth, e.g. linear search; predictable but scales poorly."},{"id":"fc-2.3.1-013","topicId":"2.3.1","front":"O(nᵏ) (Polynomial Time/Space)","back":"Polynomial growth, e.g. O(n²) for loops; manageable but slow for high k."},{"id":"fc-2.3.1-014","topicId":"2.3.1","front":"Quick Sort","back":"Partitioning around a pivot, O(n log n) average; fast but worst-case O(n²)."},{"id":"fc-2.3.1-015","topicId":"2.3.1","front":"Space Complexity","back":"Memory required by an algorithm."},{"id":"fc-2.3.1-016","topicId":"2.3.1","front":"Time Complexity","back":"Time taken as a function of input size."}]}]]}]}],["$L18"],"$L19"]}] </article></body></html>

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