Lecture on Computational Thinking: Decomposition

Definition of Decomposition

• Decomposition refers to breaking a complex problem down into smaller, more manageable parts.
• Essential skill for successful programming.
• Solving smaller parts simplifies the overall problem.

Everyday Examples of Decomposition

• Everyday activities involve decomposition, often unconsciously:
  • Morning routine: getting dressed, brushing teeth.
  • Navigating to school.
  • Approaching and completing homework.
• Example: Crossing a road involves multiple steps:
  • Stop and assess traffic.
  • Make decisions based on traffic conditions.
  • Engage with pedestrian crossing signals if necessary.
  • Final check before crossing.

Decomposition in Computer Game Design

• Example: Designing a breakout clone game.
  • Player controls a paddle to prevent a ball from falling.
  • Objective: Clear all tiles on screen.
• Decomposing the game design:
  • Display paddle on screen.
  • Program user interaction for paddle movement.
  • Implement movement boundaries (paddle cannot go off screen).
  • Draw and animate the ball.
  • Detect ball collisions with tiles.
  • Program win/lose conditions.
  • Add enhancements like graphics and sound effects.

Advantages of Problem Decomposition

• Simplifies problem-solving process.
• Enables parallel development:
  • Different teams can work on different components simultaneously.
  • Reduces development time and cost.
• Reusability:
  • Components developed once can be reused in future programs.
  • Facilitates quicker development of future iterations.

Conclusion

• Decomposition is a key aspect of computational thinking, aiding in efficient problem-solving and collaborative development.
• Reduces complexity and enhances manageability of projects.

End of Lecture Notes