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Algorithm properties

Learn finiteness, definiteness, input, output and effectiveness.

Finiteness and definiteness

Finiteness means the algorithm stops after a fixed number of steps. A procedure with an infinite loop is not an algorithm.

Definiteness means each step has a single interpretation. 'Stir a bit' is ambiguous; 'stir for 5 seconds' is definite.

Input, output and effectiveness

Input is the values given at the start; zero or more. Output is the result produced; at least one is required.

Effectiveness means each step is simple and doable. 'Find the infinite number' is not effective because it cannot be done in finite time.

Practice Square a number

Write square(n). Return n * n and print 36 with print(square(6)).

Starter code

solution.py
def square(n):
    # Square a number

Sample solution

solution.py
def square(n):
    # Square a number
    return n * n
print(square(6))

Expected output

36

Questions and answers

Review the lesson questions together with their answers. To test yourself, solve the lesson interactively.

1 Effectiveness

Question 
Each step must be doable in ____ time.
Answer 
Each step must be doable in finite time.

Explanation: finite is right.

2 Algorithm properties: match the terms

Term Meaning
Finiteness Ends
Definiteness Unambiguous
Input Starting
Effectiveness Doable

3 How many outputs must an algorithm produce at minimum?

  • Zero
  • One Correct answer
  • Two
  • Infinite

Explanation: An algorithm produces at least one output.

All lessons in Beginner

1 What is an algorithm?

  1. Algorithm definition
  2. Algorithm properties
  3. Pseudocode
  4. Summary - Algorithm concept

2 Big-O notation

  1. Time complexity
  2. Big-O definition
  3. Comparing complexities
  4. Summary - Big-O

3 Array

  1. What is an array?
  2. Array access
  3. Looping over an array
  4. Summary - Arrays

4 Linear search

  1. Linear search idea
  2. Implementing search
  3. Best and worst case
  4. Summary - Linear search

5 Search project

  1. Project: Overview
  2. Grades array setup
  3. Search function
  4. Print the result

6 Bubble sort

  1. Bubble sort idea
  2. One pass
  3. Full sort
  4. Summary - Bubble sort

7 Selection sort

  1. Selection sort idea
  2. Finding the minimum
  3. Swapping
  4. Summary - Selection sort

8 Insertion sort

  1. Insertion sort idea
  2. Shifting
  3. Placement
  4. Summary - Insertion sort

9 Sorting project

  1. Project: Overview
  2. Price array
  3. Apply sorting
  4. Print the result

10 Recursion basics

  1. What is recursion?
  2. Base case
  3. Recursive step
  4. Summary - Recursion

11 Fibonacci

  1. Fibonacci sequence
  2. Recursive Fibonacci
  3. Call tree
  4. Summary - Fibonacci

12 Factorial

  1. Factorial definition
  2. Recursive factorial
  3. Choosing the base case
  4. Summary - Factorial

13 Recursion project

  1. Project: Overview
  2. Recursive power
  3. Combination
  4. Print the results

14 Binary search

  1. Binary search idea
  2. Left right pointers
  3. Base case
  4. Summary - Binary search

15 Linked list

  1. What is a linked list?
  2. Node definition
  3. Traversing the list
  4. Summary - Linked list

16 Stack

  1. What is a stack?
  2. Push and pop
  3. Peek and is_empty
  4. Summary - Stack

17 Queue

  1. What is a queue?
  2. Enqueue and dequeue
  3. Front and back
  4. Summary - Queue

18 Hash table

  1. What is a hash table?
  2. Hash function
  3. Collision
  4. Summary - Hash table

19 Set

  1. What is a set?
  2. Add and lookup
  3. Intersection and union
  4. Summary - Set

20 Beginner final

  1. Challenge 1
  2. Challenge 2
  3. Challenge 3
  4. Challenge 4