Lecture Notes: Introduction to Computer Science

Misconceptions in Computer Science

• Computer Science is often misunderstood as:
  • The study of computers.
  • How to write computer programs.
  • Uses and applications of computers and software.
• True Definition: The study of algorithms.

Algorithms

• Definition: An ordered sequence of instructions guaranteed to solve a specific problem.
  • Example: Step-by-step instructions to complete a task.
• Importance: Central to solving problems in computer science.

Types of Operations in Algorithms

• Sequential Operations

  • Executes a single, well-defined task in order.
  • Sequential Algorithm: Completed from start to finish without parallel processing.

• Conditional Operations

  • Involves decision-making based on conditions (e.g., "if" statements).
  • Boolean Data: Used to evaluate conditions as true or false.

• Iterative Operations

  • Involves repeating a set of instructions (loops).
  • Keywords: while, repeat, for, do until.

Examples in Everyday Life

• Algorithms are used in everyday tasks (e.g., assembling, baking, balancing checkbooks).
• DVR Programming Example:
  • Sequential Steps: Steps 3, 4, 5, 7.
  • Conditional Steps: Steps 1, 6.
  • Iterative Step: Step 2.

Formal Algorithms in Mathematics

• Example of addition taught in school:
  • Sequential, conditional, and iterative steps used.
• Importance of formal algorithms:
  • They ensure the solution is automated correctly by a computing agent.

Computing Agents

• Can be a machine, robot, person, or any entity executing an algorithm.
• Capability: They do not need to understand underlying concepts, just follow steps.

Unsolved Problems in Computer Science

• Some problems are unsolvable or too slow.
• Others have solutions that are not yet known.

Summary

• Importance of algorithms and computing agents in automating solutions.
• Understanding different operations and examples helps grasp computer science fundamentals.