Higher Computing Science Summary

Development Methodologies

• Popular Methodologies: Waterfall, Rapid Application Development, Agile.
• Focus: Structure, advantages, and limitations of each methodology.

Analysis

• Purpose: Describing software usage.
• Key Elements: Scope, functional requirements, and boundaries.

Design

• Techniques: Pseudocode, flowcharts, structure diagrams.
• Goal: Identify data flow, constructs, and variables before coding.

Implementation (Computational Constructs)

• Key Constructs: Parameter passing, sub-programs, procedures, functions.
• Purpose: Structuring source code effectively.

Implementation (Algorithm Specification)

• Focus: Creating algorithms for problem-solving.
• Importance: Understanding common algorithms is crucial.

Testing

• Errors: Logic, syntax, execution.
• Tools: Dry runs, trace tables, breakpoints.

Evaluation

• Efficiency: Use of RAM, coding constructs.
• Measurement: Software fitness against functional requirements.

Data Representation

• Process: Data through CPU, usage of main and cache memory.
• Communication: Interfaces for peripherals.

Computer Structure

• Performance Factors: Number of cores, clock speed, memory.
• Memory Types: Volatile and non-volatile.

Environmental Implications

• Impact: Positive and negative environmental effects.
• Solutions: Intelligent systems for reducing energy consumption.

Security Risks and Precautions

• Threats: Spyware, phishing, keylogging, identity theft.
• Solutions: Server-side validation, encryption of network traffic.

Introducing Databases

• Issues: Anomalies in flat file databases.
• Solutions: Relational databases with primary and foreign keys.

Analysis for Databases

• Focus: Inputs, processes, outputs, and end-user needs.

Design for Databases

• Key Elements: Queries, data dictionary, attributes, relationships.

Implementation in Databases

• Language: Structured Query Language (SQL).
• Keywords: SELECT, FROM, WHERE, AND, OR.

Testing and Evaluation in Databases

• Criteria: Fitness for purpose, functionality.
• Methods: Testing queries, output comparison.

Analysis for Web Design

• Focus: End-user and functional requirements.

Design for Web Pages

• Elements: Page layout, wireframes, graphic/audio file formats.

Implementation in Web Design (HTML)

• Language: HyperText Markup Language (HTML).
• Function: Directing browser page layout.

Implementation in Web Design (JavaScript)

• Language: JavaScript for client-side scripting.
• Functions: Create, delete, manipulate HTML elements.

Testing and Evaluation in Web Design

• Usability Testing: Personas, test cases, scenarios.
• Compatibility Testing: Ensures functionality across different browsers and devices.