DSA Tracker

Medium

Pow(x, n)

A medium Math problem included in Love Babbar 450, Striver A2Z. Below: the roles whose interviews prioritise this topic, and how to practise it.

Topic
Math
Sheets
2
Core for
13 roles
Platform
LeetCode

The problem

Implement the power function to calculate x raised to the power n (i.e., x^n). Handle positive, negative, and zero exponents efficiently.

Example 1

Input
x = 2.0, n = 10
Output
1024.0
Why
2^10 = 1024.

Example 2

Input
x = 2.1, n = 3
Output
9.261
Why
2.1^3 = 2.1 * 2.1 * 2.1 = 9.261.

Example 3

Input
x = 2.0, n = -2
Output
0.25
Why
2^(-2) = 1 / 2^2 = 1/4 = 0.25.

Example 4

Input
x = 0.00001, n = 2147483647
Output
0.0
Why
A very small base raised to a very large power approaches 0.

Constraints

  • -100.0 < x < 100.0
  • -2^31 <= n <= 2^31 - 1
  • -10^4 <= x^n <= 10^4

How to think about it

Updated 2026-09-09

Multiplying x by itself one step at a time is far too slow for exponents near 2 × 10^9. Instead, note that x^n equals (x^2)^(n/2) for even exponents and x × x^(n-1) for odd ones, halving the remaining exponent at every step and converting linear work into logarithmic steps.

Approaches, worst first

  1. Linear multiplicative loop

    time O(|n|) · space O(1)

    Iterate |n| times multiplying an accumulator by x. When n reaches 2^31 - 1, running billions of multiplications causes a timeout.

  2. Binary exponentiationWrite this one

    time O(log |n|) · space O(1)

    Maintain base x and result 1.0. While n > 0, if the lowest bit of n is 1, multiply result by current base; then square the base and shift n right by 1. For negative n, invert the base and negate n safely.

Where people lose marks · 3
  • Negating n when n is -2^31: in 32-bit signed integers, -(-2^31) cannot be represented and overflows; cast n to a 64-bit integer before negating.
  • Dividing by zero when base x is 0.0 with a negative exponent.
  • Precision loss from repeatedly computing 1 / x; inverting the accumulated result once at the end is more stable than repeatedly multiplying by (1 / x).

The theory behind it

Math — the ground this problem stands on. All Math problems

What Math is

Algorithmic math is the application of number properties, modular arithmetic, and geometric patterns to compute results without simulating every step. Rather than filling memory buffers with millions of simulated counters or walking endless loops, mathematical formulation uses identities like prime factorization, digit extraction, and greatest common divisors to jump directly to target answers through closed-form rules.

When to reach for it

Reach for mathematical techniques when problem bounds are massive, such as constraints reaching ten to the eighteenth power where simulation is impossible. Strong prompts mention prime generation, greatest common divisor calculations, modular inverses, fast exponentiation, digit reversals, or combinatorial arrangements. If brute-force counting produces memory overflow or time limit exceeded warnings, algebraic reorganization is the intended path.

How the pattern works

Focus on numeric constraints and potential overflows before writing expressions. Break numbers into constituent digits using modulo ten to peel least significant figures and integer division to shrink scale. For divisibility, apply Euclid's remainder theorem repeatedly until remainder drops to zero. Apply modulo arithmetic at every intermediate addition and multiplication stage rather than once at the end, preventing values from spilling beyond standard numeric register limits.

What each operation costs

OperationTime
greatest common divisor via euclidean algorithmO(log(min(a, b)))
modular exponentiation by repeated squaringO(log n)
prime sieve of eratosthenes up to nO(n log log n)
What usually goes wrong with Math
  • Allowing 32-bit signed integer overflow during intermediate multiplications before modulo reduction is applied, producing negative or truncated results.
  • Failing to handle negative inputs in modulo arithmetic, producing negative remainders in languages that implement truncated rather than floored division.
  • Dividing by zero when the denominator or remainder becomes zero at unexpected edge boundary values like empty sets or singletons.

Which roles need this problem

Math is a core topic for these 13 roles — if you're targeting one of them, this problem is early in your path, not optional.

Secondary for 7 more roles, including Security Engineer, Performance Engineer, Site Reliability Engineer.

Track this in your role's order

Pick your target role and all 370 problems — including this one — resequence to what that interview actually asks. Free.

Start free

More Math problems

Problem set and role mapping as of .