What is Big O notation? Explain with examples.
Big O notation describes how an algorithm's time or space requirements grow as input size (n) grows. It gives an upper bound on complexity. **Common complexities (best → worst):**...
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Big O notation describes how an algorithm's time or space requirements grow as input size (n) grows. It gives an upper bound on complexity. **Common complexities (best → worst):**...
Recursion is when a function calls itself to solve smaller instances of the same problem. Here's a classic example with factorial: ```python def factorial(n): if n <= 1: # ba...
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