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Pow(x, n)

One of the most common interview questions involving recursion, mathematics, and binary thinking is implementing the power function efficiently. Problem…

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One of the most common interview questions involving recursion, mathematics, and binary thinking is implementing the power function efficiently.






Problem



Implement:




pow(x, n)






which calculates:




xⁿ






without using built-in power functions.









Brute Force Approach



Multiply x exactly n times.




double ans = 1.0;

for(int i = 0; i < n; i++) {
ans *= x;
}









Complexity




  • Time: O(n)

  • Space: O(1)



This works for small values but becomes inefficient when n is very large.









Key Observation



Let's calculate:




2¹⁰






Instead of multiplying 2 ten times:




2 × 2 × 2 × 2 × 2 × 2 × 2 × 2 × 2 × 2






we can use:




2¹⁰ = (2²)⁵






and




2² = 4
2⁴ = 16
2⁸ = 256






We're reducing the exponent by half every time.



This is called Binary Exponentiation.









Intuition



For every exponent:






If exponent is even






xⁿ = (x²)ⁿᐟ²






Example:




2¹⁰
→ 4⁵









If exponent is odd



Take one x into the answer and reduce exponent by one.




2⁵
→ 2 × 2⁴












Optimal Solution






class Solution {
public double myPow(double x, int n) {

long power = n;
double ans = 1.0;

if (power < 0) {
x = 1 / x;
power = -power;
}

while (power > 0) {

if (power % 2 == 0) {
x *= x;
power /= 2;
} else {
ans *= x;
power--;
}
}

return ans;
}
}












Dry Run



Input:




x = 2
n = 10






Initial:




ans = 1






Step 1:




10 is even

x = 4
power = 5






Step 2:




5 is odd

ans = 4
power = 4






Step 3:




4 is even

x = 16
power = 2






Step 4:




2 is even

x = 256
power = 1






Step 5:




1 is odd

ans = 1024
power = 0






Answer:




1024












Important Edge Case



Consider:




n = Integer.MIN_VALUE;









-2147483648






Doing:




n = -n;






causes overflow because:




2147483648






cannot fit inside an integer.



Therefore always store the exponent in:




long power = n;






before negating it.









Complexity Analysis






Time Complexity






O(log n)






The exponent is halved at every step.






Space Complexity






O(1)












Interview Takeaway



Whenever you see:




aᵇ






think:




Can I process the exponent bit by bit?




Binary Exponentiation is a powerful pattern that appears in:




  • Fast Power

  • Matrix Exponentiation

  • Modular Arithmetic

  • Competitive Programming

  • System Design Calculations



Remember:




Odd exponent  -> Take one x into answer
Even exponent -> Square x and halve exponent






That's the entire algorithm.



I'm currently solving the Striver SDE Sheet Challenge and documenting my learnings, patterns, mistakes, and interview insights along the way.



LinkedIn: https://www.linkedin.com/in/jaspreetsodhi482/

X (Twitter): https://x.com/Jaspree54799902

GitHub: https://github.com/codewithjaspreet

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