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Time Complexity

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Time Complexity

Asha only reaches for Time Complexity when n vs n² on 10k rows has to stay correct in a viva.

For Time Complexity, a dry-run table is in play. Don’t blame it until you have traced n vs n² on 10k rows.

Time Complexity exists so Asha can keep n vs n² on 10k rows correct in a viva.

Asha ships Time Complexity in a viva. That is the use case worth saying.

Time Complexity trap — saying ‘fast’ with no Big-O. Asha loses marks for that every viva.

After Time Complexity, Asha should still remember saying ‘fast’ with no Big-O.

Close Time Complexity with — “If I skip it, n vs n² on 10k rows goes wrong like this: saying ‘fast’ with no Big-O.”

Exam tip

Board: n vs n² on 10k rows. Dry-run Time Complexity. Name the 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))

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

Short notes

DefTime Complexity — Asha uses it for n vs n² on 10k rows in a viva.
RuleTime Complexity → best / average / worst + extra memory.
RememberTime Complexity + a dry-run table (a viva).
UseTime Complexity in a viva (n vs n² on 10k rows).
TrapTime Complexity — saying ‘fast’ with no Big-O.
ExTime Complexity → n vs n² on 10k rows.

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))

Time Complexity

Example

Short notes

Questions

Time Complexity

Example

Short notes

Questions