DSA · Theory

How to Analyze Time and Space Complexity

Theory

803/810

How to Analyze Time and Space Complexity

How to Analyze Time and Space Complexity is a DSA topic. In plain words you use it for n vs n² on 10k rows in a viva. Don’t start with a slogan — start with that picture.

Smallest example: best / average / worst + extra memory. Type it, run it, and say what you see. If you can do that from memory, you know How to Analyze Time and Space Complexity.

From the example next to this theory: How to Analyze Time and Space Complexity — big-O describes how work grows with input size — ignore constants.

Trap — saying ‘fast’ with no Big-O. Fix that before you talk about advanced DSA.

Viva: what is How to Analyze Time and Space Complexity? Then show best / average / worst + extra memory. Then name the trap.

Exam tip

What is How to Analyze Time and Space Complexity? Show this: best / average / worst + extra memory. Trap: saying ‘fast’ with no Big-O.

Example

def demo(n):
    # O(1)
    x = n + 1
    # O(n)
    total = sum(range(n))
    # O(n^2)
    pairs = 0
    for i in range(n):
        for j in range(n):
            pairs += 1
    return x, total, pairs

print(demo(3))

How to Analyze Time and Space Complexity — big-O describes how work grows with input size — ignore constants.

Short notes

DefHow to Analyze Time and Space Complexity — n vs n² on 10k rows in a viva.
Rulebest / average / worst + extra memory
Trapsaying ‘fast’ with no Big-O
Usea viva

DSA · Theory

How to Analyze Time and Space Complexity

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Theory

803/810

How to Analyze Time and Space Complexity

How to Analyze Time and Space Complexity is a DSA topic. In plain words you use it for n vs n² on 10k rows in a viva. Don’t start with a slogan — start with that picture.

Smallest example: best / average / worst + extra memory. Type it, run it, and say what you see. If you can do that from memory, you know How to Analyze Time and Space Complexity.

From the example next to this theory: How to Analyze Time and Space Complexity — big-O describes how work grows with input size — ignore constants.

Trap — saying ‘fast’ with no Big-O. Fix that before you talk about advanced DSA.

Viva: what is How to Analyze Time and Space Complexity? Then show best / average / worst + extra memory. Then name the trap.

Exam tip

What is How to Analyze Time and Space Complexity? Show this: best / average / worst + extra memory. Trap: saying ‘fast’ with no Big-O.

Example

def demo(n):
    # O(1)
    x = n + 1
    # O(n)
    total = sum(range(n))
    # O(n^2)
    pairs = 0
    for i in range(n):
        for j in range(n):
            pairs += 1
    return x, total, pairs

print(demo(3))

How to Analyze Time and Space Complexity — big-O describes how work grows with input size — ignore constants.

Short notes

DefHow to Analyze Time and Space Complexity — n vs n² on 10k rows in a viva.
Rulebest / average / worst + extra memory
Trapsaying ‘fast’ with no Big-O
Usea viva

How to Analyze Time and Space Complexity

Example

Short notes

Questions

How to Analyze Time and Space Complexity

Example

Short notes

Questions