📚 Core Exam Points for Computer Science Principles | 计算机科学原理备考核心考点梳理
Computer Science Principles is a broad yet rigorous subject that tests both theoretical understanding and practical problem-solving skills. This article condenses the most frequently examined topics into a structured revision guide, helping you target your preparation efficiently.
计算机科学原理是一门覆盖面广且要求严谨的学科，既考查理论理解，也考查实际解题能力。本文将最高频的考点凝练为结构化复习指南，帮助你高效锁定备考方向。
1. Data Representation & Number Systems | 数据表示与进制系统
Number systems form the foundation of all computer science. You must be fluent in converting between binary, decimal, and hexadecimal, and understand how data is stored at the hardware level.
进制系统是计算机科学的基石。你必须熟练地在二进制、十进制和十六进制之间进行转换，并理解数据在硬件层面的存储方式。
Binary to decimal: multiply each bit by 2ⁿ, starting from 2⁰ on the right.
二进制转十进制：从右侧 2⁰ 开始，每位乘以 2ⁿ 并求和。
Hexadecimal to binary: each hex digit maps to exactly 4 binary bits (e.g., A → 1010).
十六进制转二进制：每个十六进制位对应恰好 4 个二进制位（例如 A → 1010）。
Two's complement is the standard method for representing signed integers, with a range of −2ⁿ⁻¹ to 2ⁿ⁻¹ − 1 for n bits.
补码是表示有符号整数的标准方式，n 位的取值范围为 −2ⁿ⁻¹ 至 2ⁿ⁻¹ − 1。
Binary 1011₂ = 1×2³ + 0×2² + 1×2¹ + 1×2⁰ = 11₁₀
2. Boolean Logic & Logic Gates | 布尔逻辑与逻辑门
Boolean algebra is the mathematical language of digital circuits. You need to know the truth tables for AND, OR, NOT, NAND, NOR, XOR, and XNOR, and be able to simplify expressions using laws such as De Morgan's Theorem.
布尔代数是数字电路的教学语言。你需要掌握 AND、OR、NOT、NAND、NOR、XOR、XNOR 的真值表，并能够运用德摩根定律等规则化简表达式。
| Gate | Output = 1 when |
| AND | All inputs are 1 |
| OR | At least one input is 1 |
| NAND | Not all inputs are 1 |
| XOR | Inputs differ |
De Morgan's Theorem states: ¬(A ∧ B) = ¬A ∨ ¬B and ¬(A ∨ B) = ¬A ∧ ¬B. This is a favourite examination question in circuit simplification.
德摩根定律表述为：¬(A ∧ B) = ¬A ∨ ¬B，且 ¬(A ∨ B) = ¬A ∧ ¬B。这是电路化简题中的高频考点。
3. Computer Architecture & von Neumann Model | 计算机体系结构与冯·诺依曼模型
The von Neumann architecture describes a system where data and instructions share the same memory and bus. Key components include the CPU, memory, input/output devices, and the system bus.
冯·诺依曼体系结构描述了一种数据与指令共享同一内存和总线的系统。核心组件包括 CPU、内存、输入/输出设备以及系统总线。
CPU components: ALU (arithmetic logic unit), CU (control unit), registers, and cache.
CPU 组成：ALU（算术逻辑单元）、CU（控制单元）、寄存器和高速缓存。
Fetch-Decode-Execute cycle: the fundamental operation loop of the CPU.
取指-译码-执行周期：CPU 的基本运行循环。
Von Neumann vs Harvard: the latter uses separate memory for instructions and data, enabling simultaneous access.
冯·诺依曼结构与哈佛结构：后者将指令与数据分开存储，可同时访问。
PC → MAR → MDR → IR → CU → ALU → Registers
4. Operating Systems & Memory Management | 操作系统与内存管理
Operating systems manage hardware resources and provide a user interface. Memory management techniques such as paging, segmentation, and virtual memory are core assessment topics.
操作系统负责管理硬件资源并提供用户界面。分页、分段和虚拟内存等内存管理技术是核心考点。
Paging: memory is divided into fixed-size pages; logical addresses are mapped to physical frames.
分页：内存被划分为固定大小的页；逻辑地址映射到物理帧。
Virtual memory uses disk space as an extension of RAM, allowing larger processes to run.
虚拟内存利用磁盘空间扩展 RAM，使更大的进程得以运行。
Process scheduling algorithms: FCFS (First-Come, First-Served), SJF (Shortest Job First), Round Robin.
进程调度算法：先来先服务（FCFS）、短作业优先（SJF）、时间片轮转（Round Robin）。
5. Networking & Protocols | 网络与协议
Understanding network topologies, the OSI model, and key protocols is essential. TCP/IP is the dominant protocol suite, and you must know how data is encapsulated and transmitted.
理解网络拓扑、OSI 模型和关键协议至关重要。TCP/IP 是占主导地位的协议族，你必须了解数据是如何封装和传输的。
| Layer (OSI) | Function |
| 7 Application | User-facing services (HTTP, SMTP) |
| 4 Transport | End-to-end delivery (TCP, UDP) |
| 3 Network | Routing and addressing (IP) |
| 2 Data Link | Framing and MAC addressing |
Packet switching breaks data into packets that travel independently and are reassembled at the destination. This is more robust than circuit switching, which reserves a dedicated path.
分组交换将数据拆分为独立传输的包，并在目的地重新组装。这比预留专用通路的电路交换更加健壮。
6. Data Structures & Algorithms | 数据结构与算法
Arrays, linked lists, stacks, queues, trees, and hash tables are the building blocks of algorithm design. You should be able to compare time and space complexities using Big-O notation.
数组、链表、栈、队列、树和哈希表是算法设计的基石。你应该能够使用大 O 记法比较时间与空间复杂度。
Stack: LIFO (Last-In, First-Out), used in recursion and expression evaluation.
栈：后进先出（LIFO），用于递归和表达式求值。
Queue: FIFO (First-In, First-Out), used in scheduling and buffering.
队列：先进先出（FIFO），用于调度和缓冲。
Binary search tree: average O(log n) for search, insert, and delete.
二叉搜索树：搜索、插入、删除的平均时间复杂度为 O(log n)。
Linear search O(n) vs Binary search O(log n)
7. Programming Paradigms | 编程范式
Procedural, object-oriented, functional, and declarative paradigms each have distinct characteristics. Object-oriented programming (OOP) emphasises encapsulation, inheritance, polymorphism, and abstraction.
过程式、面向对象、函数式和声明式范式各具特点。面向对象编程（OOP）强调封装、继承、多态和抽象。
Encapsulation: hiding internal state and requiring all interaction through public methods.
封装：隐藏内部状态，所有交互通过公共方法进行。
Inheritance: a class can derive from a parent class, reusing and extending behaviour.
继承：子类可以从父类派生，复用并扩展行为。
Polymorphism: the same method name can exhibit different behaviour based on the object type.
多态：同一方法名可根据对象类型表现出不同行为。
8. Databases & SQL | 数据库与SQL
Relational databases store data in tables with rows and columns. SQL (Structured Query Language) is used to query and manipulate that data, and you must understand keys and normalisation.
关系数据库将数据存储在由行和列组成的表中。SQL（结构化查询语言）用于查询和操作数据，你还需要理解键与规范化。
Primary key: uniquely identifies each record in a table.
主键：唯一标识表中的每条记录。
Foreign key: references the primary key of another table to establish relationships.
外键：引用另一张表的主键以建立关系。
First Normal Form (1NF) requires atomic values; Second Normal Form (2NF) removes partial dependencies.
第一范式（1NF）要求属性值不可再分；第二范式（2NF）消除部分依赖。
SELECT name, score FROM students WHERE score ≥ 80 ORDER BY score DESC;
9. Recursion & Computational Thinking | 递归与计算思维
Recursion is a technique where a function calls itself to solve smaller subproblems. Every recursive algorithm must have a base case to terminate, and a recursive case to make progress.
递归是一种函数调用自身以解决更小子问题的技术。每个递归算法都必须有终止的基础情形（base case）和推进的递归情形（recursive case）。
Computational thinking involves four pillars: decomposition (breaking problems into parts), pattern recognition (finding similarities), abstraction (focusing on essential details), and algorithm design (step-by-step solutions).
计算思维包含四大支柱：分解（将问题拆分为部分）、模式识别（发现相似之处）、抽象（关注关键细节）和算法设计（逐步解决方案）。
Factorial: n! = n × (n−1)!, with base case 0! = 1
10. Security & Cryptography | 安全与密码学
Data security protects confidentiality, integrity, and availability (the CIA triad). Common threats include malware, phishing, SQL injection, and denial-of-service (DoS) attacks.
数据安全保护机密性、完整性和可用性（CIA 三元组）。常见威胁包括恶意软件、网络钓鱼、SQL 注入和拒绝服务（DoS）攻击。
Symmetric encryption: the same key encrypts and decrypts (e.g., AES).
对称加密：加密和解密使用同一密钥（如 AES）。
Asymmetric encryption: a public key encrypts and a private key decrypts (e.g., RSA).
非对称加密：公钥加密、私钥解密（如 RSA）。
Hashing creates a fixed-size digest that cannot be reversed; used for password storage.
哈希生成不可逆的固定长度摘要，用于密码存储。
11. Algorithmic Complexity & Sorting | 算法复杂度与排序
Sorting algorithms are a guaranteed examination topic. You should memorise the time complexities of bubble, insertion, merge, and quick sort, and understand their stability and memory usage.
排序算法是必考主题。你应该熟记冒泡、插入、归并和快速排序的时间复杂度，并理解其稳定性和内存使用。
| Algorithm | Best / Average / Worst |
| Bubble Sort | O(n) / O(n²) / O(n²) |
| Merge Sort | O(n log n) for all cases |
| Quick Sort | O(n log n) / O(n log n) / O(n²) |
When answering complexity questions, always state the input size n and count the dominant operations. Constants and lower-order terms should be ignored in Big-O analysis.
回答复杂度问题时，始终明确输入规模 n 并统计主导操作。在大 O 分析中，常数项和低阶项可以忽略不计。
12. Regular Expression & Finite State Machines | 正则表达式与有限状态机
Finite state machines (FSMs) model systems with a finite number of states and transitions. They are used in validation, lexical analysis, and control systems.
有限状态机（FSM）以有限数量的状态和转移来建模系统，广泛应用于验证、词法分析和控制系统。
A regular expression describes a pattern that can be matched against strings, e.g., ^[a-z]+@[a-z]+.[a-z]{2,}$ for basic email validation.
正则表达式描述可在字符串中匹配的模式，例如 ^[a-z]+@[a-z]+.[a-z]{2,}$ 可用于基本邮箱验证。
FSM components: states, transitions (input → next state), start state, and accepting states.
FSM 组成：状态、转移（输入 → 下一状态）、起始状态和接受状态。
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