COMP SCIENCE REVISION PDF

1.1 Computer Systems 1.1.1 Structure and Function of the Processor ​ Key Components: 1.​ Control Unit: Manages the execution of instructions by coordinating data flow and operations within the CPU. 2.​ Arithmetic Logic Unit (ALU): Executes arithmetic (e.g., addition, s...

1.1 Computer Systems 1.1.1 Structure and Function of the Processor ​ Key Components: 1.​ Control Unit: Manages the execution of instructions by coordinating data flow and operations within the CPU. 2.​ Arithmetic Logic Unit (ALU): Executes arithmetic (e.g., addition, subtraction) and logical (e.g., AND, OR) operations. 3.​ Registers: Small, high-speed storage locations for intermediate data (e.g., Program Counter for tracking instructions, Accumulator for storing results of operations). 4.​ Cache: High-speed storage that stores frequently accessed instructions or data, reducing latency. 5.​ Buses: ​ Data Bus: Transfers data. ​ Address Bus: Carries memory addresses for read/write operations. ​ Control Bus: Sends control signals to coordinate actions. ​ Fetch-Decode-Execute Cycle: 1.​ Fetch: Instruction is fetched from memory using the Program Counter. 2.​ Decode: Instruction is interpreted into control signals. 3.​ Execute: Instruction is carried out (e.g., calculation, data movement). 1.1.2 Types of Processor ​ CISC (Complex Instruction Set Computing): ○​ Large set of instructions, some performing complex tasks. ○​ Easier for programmers but slower execution due to more cycles per instruction. ​ RISC (Reduced Instruction Set Computing): ○​ Simplified instruction set; each instruction executes in one clock cycle. ○​ Requires more instructions but is faster and more power-efficient. ​ Parallel Processing: ○​ Uses multiple cores or processors to perform tasks simultaneously, enhancing performance for multi-threaded applications. 1.1.3 Input, Output, and Storage ​ Input Devices: Convert user input into digital signals (e.g., keyboards, microphones, sensors). ​ Output Devices: Present processed data to users (e.g., monitors, speakers, printers). ​ Primary Storage: ○​ RAM: Volatile memory used for temporary data storage during processing. ○​ ROM: Non-volatile memory storing permanent data like the BIOS. ​ Secondary Storage:  ○​ HDD: Magnetic storage, slower but cost-effective for large capacities. ○​ SSD: Flash-based storage, faster and more durable but more expensive per GB. ​ Tertiary Storage: ○​ Used for archiving and backups (e.g., optical discs, magnetic tape). 1.2 Software Development 1.2.1 Systems Software ​ Operating Systems (OS): ○​ Provides an interface between hardware and software. ○​ Key Functions: ​ Memory Management: Allocates and deallocates memory. ​ Multitasking: Manages multiple programs simultaneously. ​ File System Handling: Organizes and retrieves files from storage. ○​ Examples: Windows, macOS, Linux. ​ Utility Software: ○​ Performs maintenance tasks (e.g., antivirus scans, disk defragmentation, file compression). 1.2.2 Applications Generation ​ Types of Applications: ○​ Custom: Built for a specific user or task (e.g., bespoke business software). ○​ Off-the-Shelf: Pre-made, generic solutions (e.g., Microsoft Office). ○​ Open Source: Free to use and modify (e.g., LibreOffice). ○​ Proprietary: Licensed, closed-source software (e.g., Adobe Photoshop). 1.2.3 Software Development ​ Stages: ○​ Analysis: Determine user requirements and constraints. ○​ Design: Create diagrams (e.g., flowcharts, UML) and pseudocode to plan solutions. ○​ Implementation: Write code in a suitable programming language. ○​ Testing: ​ White-box: Tests internal logic. ​ Black-box: Tests inputs and expected outputs. ○​ Maintenance: ​ Corrective: Fix bugs. ​ Adaptive: Modify for new environments. ​ Perfective: Improve performance or features. ​ Methodologies: ○​ Waterfall: Linear and sequential, good for small, well-defined projects.  ○​ Agile: Iterative and collaborative, better for dynamic requirements. 1.2.4 Types of Programming Language ​ Low-Level Languages: ○​ Machine Code: Binary instructions directly executed by the CPU. ○​ Assembly Language: Human-readable mnemonics translated into machine code. ​ High-Level Languages: ○​ Easier to code and debug (e.g., Python, Java). ○​ Portable across systems. ​ Declarative Languages: ○​ Focus on the desired outcome, not the process (e.g., SQL for databases). ​ Imperative Languages: ○​ Specify step-by-step instructions for solving problems. 1.3 Data Representation and Networks 1.3.1 Compression, Encryption, and Hashing ​ Compression: ○​ Lossless: Reconstructs original data perfectly (e.g., PNG, ZIP). ○​ Lossy: Discards non-essential data for smaller file sizes (e.g., MP3, JPEG). ​ Encryption: ○​ Symmetric: Uses the same key for encryption and decryption; faster but less secure. ○​ Asymmetric: Uses a pair of keys (public and private) for secure communication (e.g., HTTPS). ○​ Applications: Securing online transactions, emails. ​ Hashing: ○​ Converts input data into fixed-size hashes (e.g., SHA-256). ○​ Used for password storage, data integrity checks. 1.3.2 Databases ​ Key Concepts: ○​ Primary Key: Unique identifier for a record. ○​ Foreign Key: Ensures referential integrity by linking tables. ○​ Normalization: ​ 1NF: Eliminate repeating groups. ​ 2NF: Remove partial dependencies. ​ 3NF: Remove transitive dependencies. ○​ SQL Commands: ​ SELECT, INSERT, UPDATE, DELETE for data manipulation. ​ CREATE, ALTER, DROP for structure definition. 1.3.3 Networks ​ Network Types: ○​ LAN: Connects devices in a limited area (e.g., office). ○​ WAN: Connects devices over large areas (e.g., the internet). ​ Topologies: ○​ Star: Devices connect to a central hub. ○​ Mesh: Devices connect to each other directly, offering redundancy. ​ Protocols: ○​ HTTP/HTTPS: Web communication. ○​ FTP: File transfer. ○​ SMTP: Email communication. ​ Network Security: ○​ Firewalls: Block unauthorized access. ○​ VPNs: Secure remote access. ○​ MAC Address Filtering: Restricts network access to authorized devices. 1.4 Computational Thinking and Programming 1.4 Data Types ​ Common Types: ○​ Integer, Real/Float, Boolean, Character, String. ○​ Casting: Explicitly converting between data types (e.g., int to string). 1.4.2 Data Structures ​ Arrays: Contiguous memory locations; fast for indexed access. ​ Records: Structured grouping of related data. ​ Stacks: LIFO; useful for backtracking, recursion. ​ Queues: FIFO; used in scheduling, buffering. ​ Linked Lists: Dynamic memory allocation; efficient insertion/deletion. ​ Graphs: Represent networks; nodes connected by edges. ​ Trees: Hierarchical; binary trees commonly used in searching. SLR 14: Data Structures ​ Binary trees: Enable efficient searching and sorting. ​ Hash tables: Map keys to values for quick lookups (e.g., dictionaries in Python). SLR 8: Introduction to Programming ​ Key Concepts: ○​ Variables, constants, and data types. ○​ Iteration: Loops (for, while). ○​ Selection: Conditional statements (if-else). ○​ Functions: Modularize code for reusability and clarity. ○​ Recursion: Solve problems by defining smaller instances of the same problem.