Specification points

Edexcel International AS and A level Computer Science XCP01/YCP01

629 points in 4 topics, with Edexcel's codes and titles.

Codes and titles are read by a script from Edexcel's published specification and have not been checked by a person. What each point covers is in the specification itself: Edexcel’s specification.

U1 Principles of Computer Science

1 Computer systems
1.1 Computer architecture
1.1.1 Stored-program concept
1.1.2 von Neumann architecture
1.1.3 Internal components of a computer system
1.1.3.a Central processing unit (CPU)
1.1.3.b Memory
1.1.3.c Input/output
1.1.3.d Buses
1.1.4 Components of the CPU
1.1.4.a Control unit (CU)
1.1.4.b Arithmetic logic unit (ALU)
1.1.4.c General-purpose registers
1.1.4.d Special-purpose registers
1.1.4.e Clock
1.1.5 Fetch-decode-execute (FDE) cycle
1.1.5.a Stages
1.1.5.b Role of components
1.1.5.c Use of read/write control signals
1.1.6 Memory hierarchy
1.1.6.a CPU registers
1.1.6.b Cache
1.1.6.c Main memory
1.1.6.d Secondary storage
1.1.7 Data transmission
1.1.7.a Serial
1.1.7.b Parallel
1.2 The operating system (OS)
1.2.1 Role of the OS
1.2.1.a User interface
1.2.1.b User management
1.2.1.c Peripheral management
1.2.1.d Process management
1.2.1.e Memory management
1.2.2 Multitasking
1.2.2.a Time sharing
1.2.2.b Context switching
1.2.2.c Interrupt handling in multitasking
1.2.3 Process management
1.2.3.a Process
1.2.3.b Process states
1.2.3.c Scheduling
1.2.3.d Scheduling algorithms
1.2.4 Memory management
1.2.4.a Operations
1.2.4.b Allocation techniques
1.2.4.c Stack frame
2 Data representation
2.1 Numbers
2.1.1 Number bases
2.1.1.a Binary
2.1.1.b Denary
2.1.1.c Hexadecimal
2.1.2 Units of measurement
2.1.2.a Binary numbers
2.1.2.b IEC binary prefixes
2.1.2.c SI decimal prefixes
2.1.3 Two’s complement representation of signed numbers
2.1.4 Fixed-point representation of signed fractional numbers
2.2 Binary arithmetic
2.2.1 Addition and subtraction
2.2.2 Bitwise manipulation
2.2.2.a Logical shift
2.2.2.b Arithmetic shift
2.2.2.c Bit masks
2.2.3 Overflow and underflow
2.3 Text
2.3.1 Character encoding systems
2.3.1.a ASCII/extended ASCII
2.3.1.b UTF-8/Unicode
3 Networks and encryption
3.1 Network fundamentals
3.1.1 Network components
3.1.1.a Network interface card (NIC)
3.1.1.b Switch
3.1.1.c Home router
3.1.1.d Modem
3.1.1.e Wireless access point (WAP)
3.1.1.f Transmission media
3.1.1.g Firewall
3.1.2 Bandwidth, transfer rate, latency and range
3.1.2.a Bandwidth
3.1.2.b Speed/transfer rate
3.1.2.c Latency
3.1.2.d Range
3.1.3 Network addressing
3.1.3.a Internet protocol (IP)
3.1.3.b Media access control (MAC)
3.2 Encryption
3.2.1 Encryption fundamentals
3.2.2 Methods of encryption
3.2.2.a Symmetric
3.2.2.b Asymmetric
3.2.3 Monoalphabetic substitution cipher
3.2.4 Vernam cipher algorithm
4 Structuring data
4.1 Relational databases
4.1.1 Entity-relationship model (ERM)
4.1.1.a Entity
4.1.1.b Attribute
4.1.1.c Key
4.1.1.d Relationship cardinality
4.1.1.e Ways of representing
4.1.2 Logical schema
4.1.2.a Table/relation
4.1.2.b Column/attribute
4.1.2.c Row/tuple
4.1.2.d Data types
4.1.2.e Integrity constraints
4.2 Data structures
4.2.1 Data structures
4.2.1.a Array
4.2.1.b List
4.2.1.c Dictionary
4.2.1.d Record
4.2.1.e Tuple
4.2.1.f Set
4.3 Abstract data types (ADTs)
4.3.1 Stack
4.3.1.a Structure
4.3.1.b Operations
4.3.2 Queue
4.3.2.a Structure
4.3.2.b Operations
5 Problem solving
5.1 Tools and techniques
5.1.1 Algorithms
5.1.2 Trace table
5.1.3 Recursion
5.2 Searching and sorting algorithms
5.2.1 Linear search algorithm
5.2.1.a Unsorted array
5.2.1.b Sorted array
5.2.2 Binary search algorithm
5.2.2.a Iterative
5.2.2.b Recursive
5.2.3 Bubble sort algorithm
5.2.4 Insertion sort algorithm
5.3 Boolean logic
5.3.1 Boolean expressions
5.3.1.a Boolean operators
5.3.1.b Order of precedence
5.3.2 Truth table
5.4 Programming paradigms
5.4.1 Procedural programming paradigm
5.4.2 Declarative programming paradigm
6 Enabling technologies
6.1 Data science
6.1.1 Big data
6.1.1.a Five Vs (volume, velocity, variety, veracity, value)
6.1.1.b Infrastructure
6.1.2 Tools and techniques of data science
6.1.2.a Collection
6.1.2.b Storage
6.1.2.c Web scraping
6.1.2.d Cleaning
6.1.2.e Analysis
6.1.2.f Visualisation
6.2 Artificial intelligence (AI)
6.2.1 Categories of AI
6.2.1.a Narrow
6.2.1.b General
6.2.1.c Super
6.2.2 Machine learning (ML)
6.2.2.a Supervised
6.2.2.b Unsupervised
6.2.3 Large language model (LLM)
6.2.3.a Context and query accuracy
6.2.3.b Knowledge limitations
6.2.3.c Bias/subjectivity
6.3 Tools
6.3.1 Integrated development environment (IDE)
6.3.1.a Text editor
6.3.1.b Autocomplete
6.3.1.c Syntax checker
6.3.1.d Debugger
6.3.1.e Memory inspection
6.3.2 Version control system (VCS)
6.3.3 Open-source technologies
6.3.4 Application programming interface (API)

U2 Practical Programming and Problem-solving

7 Programming
7.1 Constructs
7.1.1 Flow control constructs
7.1.1.a Sequence
7.1.1.b Selection
7.1.1.c Count-controlled iteration
7.1.1.d Condition-controlled iteration
7.1.1.e Exception handling for built-in exceptions
7.1.2 Variables and constants
7.1.2.a Creation
7.1.2.b Assignment
7.1.2.c Access
7.1.3 Operators
7.1.3.a Arithmetic
7.1.3.b Relational
7.1.3.c Boolean
7.1.3.d Bitwise
7.1.4 Subprograms
7.1.4.a Parameter
7.1.4.b Argument
7.1.4.c Function
7.1.4.d Procedure
8 Organising and handling data
8.1 Data types and structures
8.1.1 Data types
8.1.1.a Integer
8.1.1.b Real
8.1.1.c Character
8.1.1.d Boolean
8.1.1.e String
8.1.2 Data structures
8.1.2.a Array
8.1.2.b List
8.1.2.c Dictionary
8.1.2.d Record
8.1.2.e Tuple
8.1.2.f Set
8.2 Data handling methods
8.2.1 Methods to handle numeric data
8.2.1.a Rounding
8.2.1.b Truncation
8.2.1.c Randomisation
8.2.1.d Data type conversions
8.2.2 Methods to handle string data
8.2.2.a Length
8.2.2.b Indexing
8.2.2.c Formatting
8.2.2.d Examining
8.2.2.e Manipulating
8.2.3 Methods to handle text files
8.2.3.a Open
8.2.3.b Reading from a file
8.2.3.c Writing to a file
8.2.3.d Appending to a file
8.2.3.e Close
8.2.4 Methods to handle data structures
8.2.4.a Create
8.2.4.b Insert
8.2.4.c Update
8.2.4.d Retrieve
8.2.4.e Delete
8.2.4.f Traverse
8.2.5 Methods to represent and handle a stack implemented as a fixed-length list
8.2.5.a Create
8.2.5.b Push
8.2.5.c Pop
8.2.5.d IsEmpty
8.2.5.e IsFull
8.2.5.f Size
8.2.6 Methods to represent and handle a queue implemented as a fixed-length list
8.2.6.a Create
8.2.6.b Enqueue
8.2.6.c Dequeue
8.2.6.d IsEmpty
8.2.6.e IsFull
8.2.6.f Size
8.2.7 Methods to handle a set
8.2.7.a Membership
8.2.7.b Union
8.2.7.c Intersection
8.2.7.d Difference
8.3 Relational databases
8.3.1 Methods to administer an SQLite database
8.3.2 Methods to manipulate data from an SQLite database
8.3.3 Methods to retrieve data from an SQLite database
8.3.4 Methods to filter and refine data retrieved from an SQLite database
9 Best practice
9.1 Program design
9.1.1 Methods to produce correct outcomes
9.1.1.a Problem decomposition into component parts
9.1.1.b Clear and appropriate logic
9.1.1.c Variables, constants, data types and data structures appropriate to the problem
9.1.1.d Programming constructs appropriate to the problem
9.1.2 Methods to implement good practice in program design
9.1.2.a Modularity
9.1.2.b Separation of concerns
9.1.2.c Minimisation of side effects
9.1.2.d Scope isolation
9.1.2.e Fitness for purpose of input and output
9.1.2.f Efficient solutions in terms of execution time and memory usage
9.1.3 Methods to implement modularity in source code
9.1.3.a Blocked code
9.1.3.b User-defined subprograms
9.1.3.c Built-in subprograms
9.1.3.d Libraries of subprograms
9.1.3.e Files
9.1.3.f Procedures
9.1.3.g Functions
9.2 Clean code
9.2.1 Consistency
9.2.1.a Use of white space
9.2.1.b Line breaks layout
9.2.1.c Naming conventions
9.2.1.d Fixed line length
9.2.2 Readability
9.2.2.a Meaningful identifiers
9.2.2.b Informative comments
9.2.2.c Named constants
9.2.2.d Subprograms
9.2.3 Methods to control the behaviour of program code
9.2.3.a Boundary value analysis
9.2.3.b Exception handling
9.2.3.c Minimising nested conditionals
9.2.3.d Minimising loops
9.2.3.e Using guard clauses
9.2.3.f Managed conversion of data types
9.3 Functionality
9.3.1 Ensuring code is fit for purpose
9.3.1.a Testing and debugging
9.3.1.b Reviewing and refining
10 Computational thinking and algorithms
10.1 Computational thinking
10.1.1 Abstraction
10.1.2 Decomposition
10.1.3 Pattern recognition
10.1.4 Generalisation
10.2 Implementing algorithms
10.2.1 Create programmed solutions from algorithms
10.2.1.a Expressed in words
10.2.1.b Expressed in diagrams
10.2.1.c Expressed in flowcharts
10.3 Search and sort algorithms
10.3.1 Linear search algorithm
10.3.1.a Worst-case on unsorted list
10.3.1.b Early exit when found on unsorted list
10.3.1.c Early exit when found on sorted list
10.3.1.d Early exit when not in list on sorted list
10.3.2 Binary search algorithm
10.3.2.a Iterative
10.3.2.b Recursive
10.3.3 Bubble sort algorithm
10.3.3.a Worst case
10.3.3.b Exit with no swaps
10.3.3.c Reduce upper bound on each pass
10.3.4 In-place insertion sort algorithm
10.4 Recursion
10.4.1 Recursive algorithms

U3 Advanced Principles of Computer Science

11 Computer systems and data representation
11.1 Computer architecture
11.1.1 Harvard architecture
11.1.1.a Memory structure
11.1.1.b Difference between Harvard and von Neumann architecture
11.1.2 Complex instruction set (CISC) and reduced instruction set computer (RISC)
11.1.2.a Architecture
11.1.2.b Difference between RISC and CISC
11.1.3 Five-stage instruction pipelining
11.1.3.a Stages
11.1.3.b Branch hazards
11.1.4 Parallel processing
11.1.4.a Multicore processors
11.1.4.b Graphic processing units (GPUs)
11.1.5 Embedded systems
11.1.5.a Hardware components
11.1.5.b Software components
11.2 The operating system
11.2.1 Input/output (I/O) device management
11.2.1.a Role of device drivers
11.2.1.b Basic I/O system (BIOS)
11.2.1.c Role of buffering
11.2.1.d Role of caching
11.2.1.e Interrupt handling in device management
11.2.2 Virtualisation
11.2.2.a Containerisation
11.2.2.b Virtual machines
11.3 Data representation
11.3.1 Floating-point representation (IEEE-754)
12 Networks and cybersecurity
12.1 Networking
12.1.1 Open systems interconnection (OSI) reference model
12.1.1.a Layers
12.1.1.b Encapsulation/decapsulation
12.1.2 Protocol stacks
12.1.2.a TCP/IP
12.1.2.b SSL/TLS
12.1.3 Packet switching
12.1.3.a Packet components
12.1.3.b Internet router
12.1.3.c Protocols
12.1.4 Domain name system (DNS)
12.2 The Internet of Things (IoT)
12.2.1 The IoT stack
12.2.1.a Device hardware
12.2.1.b Device software
12.2.1.c Connectivity
12.2.1.d Cloud platform
12.2.1.e Cloud applications
12.3 Cybersecurity
12.3.1 CIA triad model
12.3.2 RSA encryption algorithm
12.3.2.a Prime numbers
12.3.2.b Key exchange
12.3.2.c Vulnerabilities
12.3.3 Error detection
12.3.3.a Parity bit
12.3.3.b Two-dimensional parity block
12.3.3.c Checksum
12.4 Computing paradigms
12.4.1 Cloud computing
12.4.1.a Infrastructure
12.4.1.b Services
12.4.2 Edge computing
12.4.2.a Infrastructure
12.4.2.b Services
13 Programming languages
13.1 Types of programming languages
13.1.1 Object-oriented programming (OOP) paradigm
13.1.1.a Concepts
13.1.1.b Unified modelling language (UML) class diagrams
13.1.2 Functional programming paradigm
13.1.2.a Concepts
13.1.3 Assembly language
13.1.3.a Mnemonics
13.1.3.b Instructions
13.1.3.c Addressing modes
13.1.3.d Operations
13.1.3.e Comments
14 Structuring data
14.1 Abstract data types (ADTs)
14.1.1 Linked list
14.1.1.a Structure
14.1.1.b Ways to represent
14.1.1.c Operations
14.1.2 Hash table
14.1.2.a Structure
14.1.2.b Ways to represent
14.1.2.c Operations
14.1.3 Graph
14.1.3.a Structure
14.1.3.b Ways to represent
14.1.3.c Types
14.1.3.d Operations
14.1.4 Tree
14.1.4.a Structure
14.1.4.b Types
14.1.4.c Operations
14.1.5 Circular queue
14.1.5.a Structure
14.1.5.b Operations
15 Problem solving
15.1 Algorithm design
15.1.1 Problem-solving techniques
15.1.1.a Brute force/exhaustive
15.1.1.b Divide and conquer
15.1.1.c Greedy algorithms
15.1.1.d Heuristics
15.1.1.e Backtracking
15.1.1.f Recursion
15.1.1.g Tracing algorithms
15.2 Algorithms
15.2.1 Merge sort algorithm
15.2.2 Quick sort algorithm
15.2.3 Shortest path algorithms
15.2.3.a Dijkstra’s algorithm
15.2.3.b A* algorithm
15.3 Algorithmic efficiency
15.3.1 Big O notation
15.3.1.a Time complexity
15.4 Boolean logic
15.4.1 Boolean algebra
15.4.1.a Commutative
15.4.1.b Associative
15.4.1.c Absorption
15.4.1.d Distributive
15.4.1.e De Morgan’s
15.4.1.f Double negation
15.4.2 Karnaugh map
16 Emerging technologies and professional practice
16.1 Emerging technologies
16.1.1 Encryption
16.1.1.a Digital signatures and certificates
16.1.1.b Hash digest and use of public/private keys
16.1.2 Blockchain
16.1.3 Quantum computing
16.1.3.a Qubits
16.1.3.b Principles
16.1.3.c Threat
16.1.3.d Cryptography
16.1.4 Deep learning
16.1.4.a Neural networks
16.2 Professionalism
16.2.1 Responsible practice
16.2.1.a Ethical issues
16.2.1.b Legal frameworks
16.2.1.c Codes of conduct

U4 Advanced Practical Programming and Problem-solving

17 Programming
17.1 Fundamental concepts
17.1.1 Select and use appropriate operators and flow control constructs
17.1.2 Select and use appropriate data types, variables and constants
17.1.3 Select and use appropriate one- and two-dimensional data structures
17.2 Creating solutions
17.2.1 Using computational thinking techniques
17.2.2 Using IDEs and other tools
17.2.3 Using libraries, files, modules and subprograms
18 Representing and handling data
18.1 Data handling methods
18.1.1 Methods to handle floating-point data
18.1.1.a Decimal module
18.1.1.b Rounding
18.1.1.c Decimal class
18.1.1.d Data type conversions
18.1.1.e Exception handling
18.1.1.f Compare
18.1.2 Methods to handle regular expressions (re)
18.1.2.a Finding
18.1.2.b Validating
18.1.3 Methods to handle numerical arrays (NumPy)
18.1.3.a Array
18.1.3.b Arithmetic
18.1.3.c Rounding
18.1.3.d Shape
18.1.3.e Load and save text files
18.1.4 Methods to handle data analysis (Pandas)
18.1.4.a Load CSV
18.1.4.b Measures of central tendency
18.1.4.c Information about data
18.1.4.d Clean data
18.1.4.e Load and save text files
18.2 Methods to represent and handle ADTs
18.2.1 Circular queues as fixed-length lists
18.2.1.a Create
18.2.1.b Enqueue
18.2.1.c Dequeue
18.2.1.d IsEmpty
18.2.1.e IsFull
18.2.2 Methods to represent and handle a linked list
18.2.2.a Represent
18.2.2.b Handle
18.2.3 Methods to represent and handle a hash table
18.2.3.a Represent
18.2.3.b Handle
18.2.4 Hash algorithm
18.2.5 Methods to handle collisions in a hash table
18.2.5.a Separate chaining
18.2.5.b Linear probing
18.2.5.c Rehashing
18.2.6 Methods to represent a graph
18.2.6.a Adjacency matrix
18.2.6.b Adjacency list
18.2.7 Methods to represent and handle a binary search tree
18.2.7.a Represent
18.2.7.b Handle
18.2.8 Recursive tree traversal algorithms
18.2.8.a Pre-order traversal
18.2.8.b In-order traversal
18.2.8.c Post-order traversal
19 Best practice
19.1 Program design
19.1.1 Methods to produce correct outcomes
19.1.1.a Problem decomposition into component parts
19.1.1.b Clear and appropriate logic
19.1.1.c Variables, constants, data types and data structures appropriate to the problem
19.1.1.d Programming constructs appropriate to the problem
19.1.2 Methods to implement good practice in program design
19.1.2.a Modularity
19.1.2.b Separation of concerns
19.1.2.c Minimisation of side effects
19.1.2.d Scope isolation
19.1.2.e Fitness for purpose of input and output
19.1.2.f Efficient solutions in terms of execution time and memory usage
19.1.3 Methods to implement modularity in source code
19.1.3.a Blocked code
19.1.3.b User-defined subprograms
19.1.3.c Built-in subprograms
19.1.3.d Libraries of subprograms
19.1.3.e Files
19.1.3.f Procedures
19.1.3.g Functions
19.2 Clean code
19.2.1 Consistency
19.2.1.a Use of white space
19.2.1.b Line breaks layout
19.2.1.c Naming conventions
19.2.1.d Fixed-line length
19.2.2 Readability
19.2.2.a Meaningful identifiers
19.2.2.b Informative comments
19.2.2.c Named constants
19.2.2.d Subprograms
19.2.3 Methods to control behaviour of program code
19.2.3.a Boundary value analysis
19.2.3.b Exception handling
19.2.3.c Minimising nested conditionals
19.2.3.d Minimising loops
19.2.3.e Using guard clauses
19.2.3.f Managed conversion of data types
19.3 Functionality
19.3.1 Ensuring code is fit for purpose
19.3.1.a Testing and debugging
19.3.1.b Reviewing and refining
20 Additional programming paradigms
20.1 Object-oriented programming (OOP) and functional programming
20.1.1 Methods for object-oriented programming (OOP)
20.1.1.a Classes
20.1.1.b Attributes
20.1.1.c Methods
20.1.1.d Objects (instance)
20.1.1.e Encapsulation
20.1.1.f Getters
20.1.1.g Setters
20.1.1.h Aggregation
20.1.1.i Composition
20.1.1.j Inheritance
20.1.1.k Polymorphism
20.1.2 Methods for functional programming
20.1.2.a Pure functions
20.1.2.b First-class functions
20.1.2.c Higher-order functions
20.1.2.d Immutable variables
20.1.2.e Avoid side effects
20.1.2.f Lazy evaluation
20.1.2.g Lambda functions
20.1.2.h Recursion
20.1.2.i Map
20.1.2.j Filter
20.1.2.k Reduce
20.1.2.l List comprehension
20.1.2.m Dictionary comprehension
20.1.2.n Zip
21 Algorithms
21.1 Sorting algorithms
21.1.1 Recursive merge sort algorithm
21.1.2 Recursive quick sort algorithm
21.2 Shortest path and compression
21.2.1 Dijkstra’s shortest path algorithm
21.2.2 Run-length encoding compression algorithm