Algorithm Complexity

Algorithm Complexity

By Shahbaz Farooq

​Big O Notation

Multiple Choice

What is meant by the time complexity of an algorithm?

• The amount of time required to solve a particular problem
• How difficult a problem is to solve
• How many lines of code are required to solve a problem
• How quickly a solution can be developed

Multiple Select

What two pieces of information allow you to analyse an algorithm?

• Time Complexity
• Space Complexity
• Size Complexity
• Complex Complexity
• Simplicity Complex

Multiple Choice

What is space complexity?

• The space complexity is the amount of storage space an algorithm takes up
• How many times a certain number (base) is multiplied together to reach another number.
• An algorithm is a series of steps that complete a task

Multiple Choice

What does the big-O notation show?

• The effectiveness of an algorithm
• The amount of time required to solve a particular problem
• How difficult a problem is to solve
• How many lines of code are required to solve a problem
• How quickly a solution can be developed

What do you think ?​

Multiple Choice

If for an algorithm time complexity is given by O(1) then complexityof it is:

• constant

• polynomial

• exponential

• none of the mentioned

Multiple Choice

• O(n)

• O(m)

• O(n+m)

• O(n*m)

Multiple Choice

If for an algorithm time complexity is given by O(n) then complexityof it is:

• A. constant

• B. linear

• C. exponential

• D. none of the mentioned

Multiple Choice

What is the time complexity of this algorithm?

• O(n)

• O(2ⁿ)

• O(log n)

• O(n²)

• O(1)

Multiple Choice

What is the time complexity of this algorithm?

• O(n)

• O(2ⁿ)

• O(log n)

• O(n²)

• O(1)

Multiple Choice

Why is this not a sequence?

Start car

Put in key

Turn key

Drive away

• There are spelling mistakes

• The instructions are in the correct order

• The instructions are in the wrong order

• It is a sequence

Multiple Choice

Time Complexity of this program:

def f():

a = 0

for i = 1 to n:

a += i;

b = 0

for i = 1 to m:

b += i;

• O(n)

• O(m)

• O(n+m)

• O(n*m)

Multiple Choice

If for an algorithm time complexity is given by O(1) then complexityof it is:

• constant

• polynomial

• exponential

• none of the mentioned

Multiple Choice

If for an algorithm time complexity is given by O(n) then complexityof it is:

• A. constant

• B. linear

• C. exponential

• D. none of the mentioned

Multiple Choice

Indicate constant time complexity in terms of Big-O notation

• O(n)

• O(1)

• O(log n)

• O (n^2)

Multiple Choice

Indicate exponential time complexity in terms of big-O notation

• O (n)

• O (n^2)

• O (2^n)

• O (log n)

Multiple Choice

Find the slowest time complexity

• O (n)

• O (n^2)

• O (n!)

• O (2^n)

Multiple Choice

Which notation is consistent for every execution?

• O (n)

• O (n^2)

• O (1)

• O (2^n)

Multiple Choice

The O (n!) is so inefficient, there is no practical use for it

• True

• False

Multiple Choice

O (n log n) is the worst case scenario for

• Merge Sort

• Bubble Sort

• Binary Search

• Linear Search

Multiple Choice

O  $$n^2$$  is the worst case scenario for

• Merge Sort

• Bubble Sort

• Binary Search

• Linear Search