6.1.1. Definition of Input Size

Try these first

1. 1.

   Define input size in relation to algorithms.

   Hint

   Think about how we quantify the data in an algorithm.

2. 2.

   What does worst-case analysis help us understand?

   Hint

   Consider scenarios where inputs might be challenging.

3. 3.

   What does 'input size' refer to in algorithm analysis?

   • The amount of data
   • The time an algorithm takes
   • The programming language used

   Hint

   Focus on what metrics influence algorithm performance.

4. 4.

   True or False: The average case analysis is always more informative than the worst-case analysis.

   • True
   • False

   Hint

   Think about when you would want maximum performance assurance.

5. 5.

   In an algorithm that sorts an array, what is the worst-case scenario when determining the time complexity? Illustrate this with an example.

   Hint

   Think of sorting methods and how they operate on data.

6. 6.

   Discuss how changing the representation of graphs (adjacency matrix vs. adjacency list) affects the complexity of operations and the definition of input sizes.

   Hint

   Visualize how graph data structures differ and their relationship with operations.