DSA · Theory

What is Logarithmic Time Complexity

Theory

798/810

What is Logarithmic Time Complexity

Logarithmic Time Complexity (what is) 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 Logarithmic Time Complexity (what is).

From the example next to this theory: What is Logarithmic Time 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 Logarithmic Time Complexity (what is)? Then show best / average / worst + extra memory. Then name the trap.

Exam tip

What is Logarithmic Time Complexity (what is)? 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))

What is Logarithmic Time Complexity — big-O describes how work grows with input size — ignore constants.

Short notes

DefLogarithmic Time Complexity (what is) — n vs n² on 10k rows in a viva.
Rulebest / average / worst + extra memory
Trapsaying ‘fast’ with no Big-O
Usea viva

DSA · Theory

What is Logarithmic Time Complexity

← All stacks

Theory

798/810

What is Logarithmic Time Complexity

Logarithmic Time Complexity (what is) 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 Logarithmic Time Complexity (what is).

From the example next to this theory: What is Logarithmic Time 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 Logarithmic Time Complexity (what is)? Then show best / average / worst + extra memory. Then name the trap.

Exam tip

What is Logarithmic Time Complexity (what is)? 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))

What is Logarithmic Time Complexity — big-O describes how work grows with input size — ignore constants.

Short notes

DefLogarithmic Time Complexity (what is) — n vs n² on 10k rows in a viva.
Rulebest / average / worst + extra memory
Trapsaying ‘fast’ with no Big-O
Usea viva

What is Logarithmic Time Complexity

Example

Short notes

Questions

What is Logarithmic Time Complexity

Example

Short notes

Questions