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O Level · Computer Science 0478

Development Life Cycle

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Cambridge (CIE) IGCSE · Computer Science

Program Development Life Cycle

Big idea: Good software isn't just "written" — it's understood, planned, built and checked in four deliberate stages (Analysis → Design → Coding → Testing), so nothing important gets missed and the final program actually solves the right problem.

The Four Stages at a Glance

1. Analysis
→
2. Design
→
3. Coding
→
4. Testing

In real projects this isn't strictly one-way — testing often sends developers back to fix coding, and even design, before moving on. Think of it as a cycle, not just a straight line.

Summary — The Whole Chapter in 5 Bullets

  • Analysis = figuring out exactly what problem needs solving, using abstraction to strip away irrelevant detail and focus on core functionality and requirements.
  • A requirements document is produced during analysis — it lists each requirement with a description and a success criteria so everyone knows when it's "done."
  • Design = turning the understood problem into a blueprint, shown using structure diagrams, flowcharts, or pseudocode.
  • Coding = writing the actual program in modules, with iterative testing happening constantly as each module is built and re-tested.
  • Testing (the final stage) = running the whole finished program repeatedly with varied test data to check it meets requirements and handles invalid input correctly.

Stage 1: Analysis

What actually happens here?

Before anyone writes a single line of code, the team has to be brutally clear about what problem they're actually solving. This sounds obvious, but it's the stage most beginner programmers skip — and it's exactly why their programs end up solving the wrong problem, or missing half the features the client actually wanted.

The analysis stage is defined as: precisely understanding the problem the program is intended to solve. Not "roughly understanding" — . That word matters in exam answers.

Abstraction The act of removing unimportant details from a problem so you can focus on what actually matters — the core functionality and the requirements. Abstraction is about deciding what to ignore just as much as what to include.
The London Underground analogy (straight from the syllabus): When you look at a Tube map, you don't see the real geography of London — the actual curves of tunnels, the exact distances between stations, or how deep underground each line runs. All of that detail is abstracted away because it's irrelevant to what you actually need: knowing that getting on at Stop A will eventually get you to Stop B. The map keeps only the useful information (which lines connect, which stations interchange) and throws away everything else. That's exactly what abstraction does to a programming problem — it keeps the "core functionality and requirements" and discards the noise.

Core Functionality

Using abstraction helps identify the fundamental components of what the program is actually going to solve — i.e. the essential jobs the program must do, stripped of extra detail.

Two things need to be nailed down before any coding starts:

  • clearly understood by everyone working on it
  • overall goal constraints platform

Requirements Document

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Also in the full note
  • Stage 2: Design
  • Stage 3: Coding
  • Stage 4: Testing
  • What to Memorise
  • Concepts Checklist
  • Exam Tips
  • Practice Questions
  • Practice Question
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