📚 Year 13 AQA Computer Science: Glossary Quick Reference Guide | AQA 计算机 Year 13 词汇术语速记指南
A strong command of technical vocabulary is essential for success in the AQA A‑level Computer Science examinations. This guide brings together the most important terms you will encounter in Year 13, from abstract data structures to computational theory. Each entry provides a concise English definition immediately followed by its Chinese equivalent, helping bilingual learners reinforce understanding and recall key concepts efficiently.
在 AQA A-level 计算机科学考试中，扎实掌握专业术语是取得成功的关键。本指南汇集了你将在 Year 13 遇到的最重要的词汇，从抽象数据结构到计算理论。每个词条先给出简洁的英文定义，紧跟着中文释义，帮助双语学习者巩固理解、高效记忆核心概念。
1. Abstract Data Structures | 抽象数据结构
Stack: A stack is a linear abstract data type that follows Last In, First Out (LIFO). Elements are added and removed from the same end, called the top. The fundamental operations are push (add) and pop (remove), often supplemented by peek or isEmpty.
栈：栈是一种遵循后进先出（LIFO）的线性抽象数据类型。所有元素的添加和删除都在同一端进行，这一端称为栈顶。基本操作包括入栈（push，添加）和出栈（pop，删除），通常还配有查看栈顶元素（peek）和判断是否为空的操作。
Queue: A queue is a linear abstract data type operating on First In, First Out (FIFO) principle. Items are added at the rear (enqueue) and removed from the front (dequeue). Circular queues and priority queues are common variations that avoid wasted space or process elements based on urgency.
队列：队列是一种基于先进先出（FIFO）原则的线性抽象数据类型。元素从队尾加入（入队，enqueue），从队头移除（出队，dequeue）。循环队列和优先队列是常见变体，前者避免空间浪费，后者按优先级处理元素。
Binary Tree: A binary tree is a hierarchical data structure where each node has at most two children, referred to as the left child and the right child. A binary search tree (BST) maintains an ordering property: for any node, all values in the left subtree are smaller, and all values in the right subtree are larger, enabling efficient search, insertion, and deletion.
二叉树：二叉树是一种层次型数据结构，每个节点最多有两个子节点，分别称为左孩子和右孩子。二叉搜索树（BST）维持有序性：对于任意节点，左子树中的所有值都小于该节点，右子树中的所有值都大于该节点，从而能够高效地进行查找、插入和删除。
Hash Table: A hash table stores key–value pairs and uses a hash function to compute an index into an array of buckets. Ideally, it offers O(1) average-time complexity for lookup, insertion, and deletion. Collisions are resolved by techniques such as chaining (linked lists in each bucket) or open addressing (probing for the next free slot).
哈希表：哈希表存储键值对，使用哈希函数计算数组桶的索引。理想情况下，查找、插入和删除操作的平均时间复杂度为 O(1)。冲突通过链地址法（每个桶中存放链表）或开放地址法（探查下一个空闲位置）来解决。
Graph: A graph is a collection of vertices (nodes) and edges (connections). Graphs can be directed or undirected, weighted or unweighted. They are commonly represented by an adjacency matrix or an adjacency list. Graphs model networks, routes, and dependencies in computing problems.
图：图是由顶点（节点）和边（连接）构成的集合。图可分为有向/无向和加权/无权。常用表示方法有邻接矩阵和邻接表。图用于模拟计算机网络、路由问题以及计算中的依赖关系。
2. Algorithm Complexity & Performance | 算法复杂度与性能
Big-O Notation: Big-O notation expresses the upper bound of an algorithm’s time or space requirements as the input size n grows. For example, O(n²) means the running time grows quadratically. It allows us to compare algorithms independently of hardware or implementation details.
大O符号：大O符号表示随着输入规模 n 的增长，算法时间或空间需求的上界。例如 O(n²) 表示运行时间呈二次增长。它让我们能够在忽略硬件和实现细节的情况下比较算法的效率。
P and NP Classes: P (polynomial time) problems can be solved by a deterministic Turing machine in time that grows polynomially with the input size. NP (nondeterministic polynomial time) problems can have their solutions verified in polynomial time. The question “P = NP?” is one of the great unsolved problems in computer science.
P 类与 NP 类：P 类（多项式时间）问题可由确定性图灵机在随输入规模多项式增长的时间内解决。NP 类问题可以在多项式时间内验证其解是否正确。“P = NP？”是计算机科学中最著名的未解决问题之一。
NP-Hard and NP-Complete: An NP-hard problem is at least as hard as the hardest problems in NP; it does not have to be in NP itself. An NP-complete problem is both in NP and NP-hard. Common NP-complete problems include the travelling salesman problem (decision version) and the Boolean satisfiability problem (SAT).
NP 难与 NP 完全：NP 难问题至少和 NP 中最难的问题一样难；它本身不一定属于 NP。NP 完全问题既属于 NP 同时又是 NP 难。常见的 NP 完全问题包括旅行商问题（判定版）和布尔可满足性问题（SAT）。
Recursive Algorithm: A recursive algorithm calls itself on a smaller instance of the problem until a base case is reached. While often elegant, recursion can lead to stack overflow if the depth is too great. Many recursive solutions can be transformed into iterative ones using loops and stacks.
递归算法：递归算法调用自身去解决规模更小的子问题，直到达到基准情形。递归通常简洁优雅，但如果深度过大可能会导致栈溢出。许多递归解可以用循环和栈转换为迭代形式。
3. Graph Algorithms | 图算法
Dijkstra’s Algorithm: Dijkstra’s algorithm finds the shortest path from a single source node to all other nodes in a weighted graph with non‑negative edge weights. It uses a priority queue to greedily select the unvisited node with the smallest tentative distance and updates its neighbours.
迪杰斯特拉算法：迪杰斯特拉算法用于在具有非负边权的加权图中找到从单个源节点到所有其他节点的最短路径。它利用优先队列贪心地选取当前暂定距离最小的未访问节点，并更新其邻居的距离。
A* Search: A* is an informed search algorithm that uses a heuristic to estimate the cost from a node to the goal. The evaluation function is f(n) = g(n) + h(n), where g(n) is the actual cost from the start to n, and h(n) is the heuristic estimate. If the heuristic is admissible (never overestimates), A* guarantees an optimal path.
A* 搜索：A* 是一种启发式搜索算法，利用启发函数估算从节点到目标的代价。评估函数为 f(n) = g(n) + h(n)，其中 g(n) 是从起点到 n 的实际代价，h(n) 是启发式估计。若启发函数是可采纳的（不会高估），A* 保证找到最优路径。
Depth‑First Search (DFS): DFS explores a graph by going as deep as possible along a branch before backtracking. It can be implemented recursively or using an explicit stack. DFS is used for topological sorting, detecting cycles, and solving maze puzzles.
深度优先搜索（DFS）：DFS 尽可能深地沿着一条分支探索图，直到无法继续才回溯。它可以用递归或显式栈实现。DFS 常用于拓扑排序、检测环以及求解迷宫问题。
Breadth‑First Search (BFS): BFS visits all neighbours of a node before moving to the next level of neighbours, using a queue to maintain the frontier. It finds the shortest path in an unweighted graph and is the basis for many network broadcasting protocols.
广度优先搜索（BFS）：BFS 先访问当前节点的所有邻居，再移向下一层邻居，使用队列维护边界节点集。它可在无权图中找到最短路径，也是许多网络广播协议的基础。
4. Computer Architecture | 计算机体系结构
Von Neumann Architecture: The Von Neumann architecture stores both program instructions and data in a shared memory unit. A single bus (or set of buses) connects the memory to the processor, creating the “Von Neumann bottleneck” when the CPU idles waiting for data. Most general‑purpose computers still follow this model.
冯·诺依曼体系结构：冯·诺依曼体系将程序指令和数据存储在同一内存单元中。一条总线（或一组总线）将内存与处理器相连，CPU 因等待数据而空闲的现象称为“冯·诺依曼瓶颈”。大多数通用计算机至今仍沿用此模型。
Pipelining: Pipelining is a processor design technique that overlaps the execution of multiple instructions by splitting the instruction cycle into stages (e.g. fetch, decode, execute, write‑back). While it increases throughput, hazards such as data dependencies or branch mispredictions can cause pipeline stalls.
流水线：流水线是一种处理器设计技术，将指令周期拆分为多个阶段（如取值、译码、执行、写回），使得多条指令的执行可以重叠。虽然流水线提高了吞吐量，但数据相关或分支预测错误等风险会导致流水线停顿。
Registers: Registers are small, extremely fast storage locations within the CPU. Key registers include the program counter (PC), memory address register (MAR), memory data register (MDR), current instruction register (CIR), and accumulator (ACC). They hold data and control information during instruction execution.
寄存器：寄存器是 CPU 内部容量小、速度极快的存储单元。关键寄存器包括程序计数器（PC）、内存地址寄存器（MAR）、内存数据寄存器（MDR）、当前指令寄存器（CIR）和累加器（ACC）。它们在指令执行期间暂存数据和控制信息。
Interrupt: An interrupt is a signal sent to the processor to request immediate attention. Interrupts can be generated by hardware (e.g. I/O completion) or software (e.g. system calls). Upon receiving an interrupt, the CPU saves its state, executes an interrupt service routine (ISR), and then resumes the original task.
中断：中断是发送给处理器请求立即处理的信号。中断可由硬件（如 I/O 完成）或软件（如系统调用）产生。接收到中断后，CPU 保存当前状态，执行中断服务程序（ISR），然后恢复原任务。
5. Networking & Security | 网络与安全
TCP/IP Stack: The TCP/IP model is a four‑layer protocol suite used for internet communication. Application (HTTP, FTP), Transport (TCP, UDP), Internet (IP), and Link (Ethernet, Wi‑Fi) layers handle everything from application‑data segmentation to physical transmission. TCP provides reliable, ordered delivery; UDP is connectionless and faster but without guarantees.
TCP/IP 协议栈：TCP/IP 模型是互联网通信使用的四层协议套件。应用层（HTTP、FTP）、传输层（TCP、UDP）、互联网层（IP）和链路层（以太网、Wi‑Fi）分别处理从应用数据分段到物理传输的各种任务。TCP 提供可靠、有序的交付；UDP 是无连接的，速度更快但无可靠性保证。
Encryption: Encryption transforms plaintext into ciphertext using an algorithm and a key. Symmetric encryption (e.g. AES) uses the same key for encryption and decryption; asymmetric encryption (e.g. RSA) uses a public‑private key pair, enabling secure key exchange and digital signatures without sharing a secret key in advance.
加密：加密利用算法和密钥将明文转换为密文。对称加密（如 AES）使用相同密钥进行加密和解密；非对称加密（如 RSA）使用公钥‑私钥对，无需事先共享秘密即可实现安全密钥交换和数字签名。
Firewall: A firewall is a network security system that monitors and controls incoming and outgoing traffic based on predetermined rules. It can be hardware‑ or software‑based, filtering packets by IP address, port number, or protocol. Firewalls help prevent unauthorised access to private networks.
防火墙：防火墙是一种网络安全系统，根据预定规则监控和控制进出网络流量。它可以是硬件或软件形式，按 IP 地址、端口号或协议来过滤数据包。防火墙有助于防止对私有网络的未授权访问。
SQL Injection: SQL injection is a code‑injection technique where an attacker inserts malicious SQL statements into an entry field for execution. It exploits improper validation of user input and can lead to data theft, modification, or deletion. Parameterised queries and input sanitisation are essential countermeasures.
SQL 注入：SQL 注入是一种代码注入技术，攻击者在输入字段中插入恶意 SQL 语句并执行。它利用了对用户输入验证不当的漏洞，可导致数据窃取、修改或删除。参数化查询和输入净化是必要的防范措施。
6. Databases & SQL | 数据库与 SQL
Normalisation: Normalisation is the process of organising database tables to reduce data redundancy and improve integrity. It involves decomposing a table into well‑structured relations. The most common normal forms are First Normal Form (1NF – atomic values), Second Normal Form (2NF – no partial dependencies), and Third Normal Form (3NF – no transitive dependencies).
规范化：规范化是组织数据库表以减少数据冗余、提高数据完整性的过程。它将表分解为结构良好的关系。最常见的范式包括第一范式（1NF，原子值）、第二范式（2NF，无部分依赖）和第三范式（3NF，无传递依赖）。
Primary and Foreign Keys: A primary key uniquely identifies each record in a table; it must be not null and unique. A foreign key is a column (or set of columns) that links to the primary key of another table, establishing a relationship between the two tables and enforcing referential integrity.
主键与外键：主键唯一标识表中的每条记录，必须非空且唯一。外键是一列（或多列），它链接到另一张表的主键，建立两表之间的关系并维护参照完整性。
SQL JOIN: JOIN clauses combine rows from two or more tables based on a related column. INNER JOIN returns only rows where the condition is true in both tables. LEFT JOIN returns all rows from the left table plus matching rows from the right; non‑matching right side columns are filled with NULL.
SQL JOIN：JOIN 子句根据相关列合并两个或多个表中的行。INNER JOIN 仅返回两表中条件为真的匹配行。LEFT JOIN 返回左表所有行以及右表匹配的行，右表无匹配的列以 NULL 填充。
Transaction and ACID: A transaction is a sequence of database operations treated as a single logical unit. ACID properties ensure reliable processing: Atomicity (all or nothing), Consistency (valid state transitions), Isolation (transactions do not interfere), and Durability (committed changes survive failures).
事务与 ACID：事务是数据库操作的序列，被视为一个单一逻辑单元。ACID 属性保证了可靠的处理：原子性（要么全做要么全不做）、一致性（状态转换有效）、隔离性（事务之间不干扰）和持久性（已提交的更改在故障后依然保留）。
7. Programming Paradigms | 编程范式
Object‑Oriented Programming (OOP): OOP is a paradigm based on the concept of objects that contain data (attributes) and behaviour (methods). Key principles are encapsulation (hiding internal state), inheritance (creating new classes based on existing ones), and polymorphism (using a single interface to represent different underlying forms).
面向对象编程（OOP）：OOP 是一种基于对象的编程范式，对象包含数据（属性）和行为（方法）。核心原则包括封装（隐藏内部状态）、继承（基于现有类创建新类）和多态（通过统一接口表示不同底层形态）。
Functional Programming: Functional programming treats computation as the evaluation of mathematical functions and avoids mutable state and side effects. Core concepts include first‑class functions, higher‑order functions (functions that take or return other functions), pure functions (no side effects), and recursion over iteration.
函数式编程：函数式编程将计算视为数学函数的求值，避免可变状态和副作用。核心概念包括一等函数、高阶函数（接受或返回函数的函数）、纯函数（无副作用）以及用递归代替迭代。
Recursion vs Iteration: Recursion solves a problem by calling a function within itself; iteration uses loops. Recursion often offers clearer code for problems with self‑similar structure (e.g. tree traversal) but consumes stack memory. Tail‑call optimisation can reduce the memory overhead of recursion in some languages.
递归与迭代：递归通过函数调用自身来解决问题；迭代则使用循环。对于具有自相似结构的问题（如树遍历），递归通常代码更清晰，但会消耗栈内存。某些语言中的尾调用优化可以降低递归的内存开销。
8. Theory of Computation | 计算理论
Turing Machine: A Turing machine is a theoretical model of computation that consists of an infinite tape divided into cells, a read/write head, a state register, and a finite set of rules. It reads a symbol, writes a symbol, and moves left or right based on the current state. A Turing machine can simulate any algorithm, forming the basis of the Church–Turing thesis.
图灵机：图灵机是一种理论计算模型，由一条分成单元格的无限长纸带、读写头、状态寄存器和一组有限规则组成。它根据当前状态读取一个符号、写入一个符号，并向左或向右移动。图灵机可以模拟任何算法，构成了丘奇‑图灵论题的基础。
Halting Problem: The halting problem asks whether it is possible to write a program that determines, for any given program and input, if the program will eventually stop. Turing proved that such a program cannot exist, making the halting problem undecidable. This demonstrates fundamental limitations of computation.
停机问题：停机问题询问能否写出一个程序，对于任意的程序和输入，判定该程序最终是否会停止。图灵证明了这样的程序不可能存在，因此停机问题是不可判定的。这展示了计算的根本性限制。
Finite State Machine (FSM): An FSM is a mathematical model of computation with a finite number of states, transitions between those states, and actions. Deterministic FSMs have exactly one transition for each input symbol from a state; non‑deterministic FSMs may have multiple. FSMs are used in lexical analysis, control systems, and protocol design.
有限状态机（FSM）：FSM 是一种具有有限数量状态、状态间转换以及行动的计算数学模型。确定性 FSM 对于每个状态和输入符号只有一个转换；非确定性 FSM 则可能有多个。FSM 用于词法分析、控制系统和协议设计。
Regular Expression: A regular expression is a sequence of characters that defines a search pattern. It is used to describe regular languages, which are exactly the languages recognisable by finite state machines. Common operations include concatenation, alternation (|), and Kleene star (*).
正则表达式：正则表达式是一串定义搜索模式的字符序列，用于描述正则语言，而正则语言正是有限状态机所能识别的语言。常见操作包括连接、选择（|）和克林闭包（*）。
9. Big Data | 大数据
Volume, Velocity, Variety: The three Vs capture the defining characteristics of Big Data. Volume refers to the massive scale of data generated. Velocity is the speed at which data is produced and must be processed. Variety describes the different forms of data: structured (databases), semi‑structured (XML, JSON), and unstructured (text, images).
数据量、速度与多样性：三个 V 概括了大数据的定义特征。数据量（Volume）指生成海量数据的规模。速度（Velocity）指数据产生和必须被处理的速度。多样性（Variety）描述数据的不同形态：结构化（数据库）、半结构化（XML、JSON）和非结构化（文本、图像）。
Distributed Computing: To handle Big Data, processing is often distributed across clusters of machines. Frameworks like MapReduce split a task into smaller sub‑tasks, execute them in parallel on many nodes, and aggregate the results. This allows scalable analysis beyond the capacity of a single server.
分布式计算：为了处理大数据，通常将处理任务分布到机器集群上。诸如 MapReduce 这样的框架将任务拆分为更小的子任务，在多个节点上并行执行，然后汇总结果。这使得分析可以扩展，超越单台服务器的能力。
Data Mining: Data mining is the process of discovering patterns, correlations, and anomalies in large datasets using techniques from statistics, machine learning, and database systems. It is used for market basket analysis, fraud detection, and customer segmentation.
数据挖掘：数据挖掘是运用统计学、机器学习和数据库系统技术，在大数据集中发现模式、关联和异常的过程。它常用于购物篮分析、欺诈检测和客户细分。
10. Legal & Ethical Issues | 法律与伦理问题
Data Protection Act (DPA): The DPA (and GDPR in the UK) governs the collection, storage, and processing of personal data. It sets principles such as data must be processed lawfully, kept for no longer than necessary, and held securely. Individuals have rights to access and correct data held about them.
数据保护法（DPA）：数据保护法（及英国的 GDPR）规范了个人数据的收集、存储和处理。其原则包括数据必须合法处理、保存时间不超过必要限度以及安全存放。个人有权访问和更正与其相关的数据。
Computer Misuse Act: This UK law makes it an offence to access or modify computer material without authorisation. It covers hacking, spreading malware, and denial‑of‑service attacks. The act distinguishes between unauthorised access, access with intent to commit further crimes, and unauthorised modification of data.
计算机滥用法：此法将未经授权访问或修改计算机材料定为犯罪行为。涵盖黑客入侵、传播恶意软件和拒绝服务攻击。该法区分了未经授权访问、企图进一步犯罪而访问以及未经授权修改数据等罪行。
Ethical Hacking: Ethical hacking involves authorised professionals attempting to penetrate systems to discover vulnerabilities, so they can be fixed before malicious hackers exploit them. It is governed by a strict code of conduct and often follows a structured penetration testing methodology.
道德黑客：道德黑客是指经授权的专业人员尝试渗透系统以发现漏洞，以便在恶意黑客利用之前进行修复。这种行为受严格的行为准则约束，通常遵循结构化的渗透测试方法。
Digital Divide: The digital divide describes the gap between those who have ready access to computers and the internet, and those who do not. This inequality can be due to economic, geographic, or educational barriers, and it affects opportunities for employment, education, and participation in the digital economy.
数字鸿沟：数字鸿沟描述能够方便使用计算机和互联网的人群与无法使用的人群之间的差距。这种不平等可能源于经济、地理或教育障碍，影响就业、教育机会以及参与数字经济的能力。
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