Lecture on Abstraction

Introduction to Abstraction

• Abstraction Definition: Managing complexity by focusing on relevant concepts and omitting unnecessary details.

Example of Abstraction in Daily Life

• Basketball Game Summary:
  • High-level summary: "The Warriors won by 10 points."
  • Detailed actions: Descriptions of player actions (e.g., Steph Curry's muscle movements).
• Purpose: Avoid overwhelming detail; keep focus on relevant information.

Abstraction in Computer Science

• Procedural Abstraction:
  • Define steps of a program without detailing each step's internal processes.
  • Example: Writing high-level instructions instead of detailed muscle movements in the "Hokey Pokey" dance.

Levels of Abstraction

• In Programming (e.g., Karel Program):
  • High-level: "Move" command in Karel.
  • Low-level: Translates to Assembly language, then to Machine code (binary).
• Purpose: Simplify programming by abstracting complex operations and providing high-level commands.

Historical Context and Progress

• Early programming (e.g., Roller Coaster Tycoon) done in low-level Assembly.
• Modern programming languages offer higher levels of abstraction.

Key Quote on Abstraction

• John Guttag: "Preserving information relevant in a given context and forgetting information that is irrelevant."

Practical Application: Functions

• Functions as Abstractions:
  • Simplify complex operations (e.g., "Build Tower" function in Karel).
  • Abstract away detailed steps, focusing on high-level operations.
  • Multiple functions can achieve the same result, showing flexibility.

Conclusion

• Abstraction as a Skill:
  • Essential for managing complexity in computer science.
  • Focuses on high-level ideas to efficiently "get the job done."
• Continued Learning: Abstraction is a key concept that will be explored further throughout the course.