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There's a mistake in the example that has been provided.  According to the complexity analysis, the current example yields the exponential time complexity, not the previous one.
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Yutharsan
2024-05-22 11:12:31 +05:30
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src/data/roadmaps/computer-science/content/103-asymptotic-notation/103-common-runtimes/104-exponential.md
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@@ -6,7 +6,7 @@ Exponential algorithms are those that grow at a rate of 2^n. This means that for
def exponential(n): def exponential(n):
if n == 0: if n == 0:
return 1 return 1
return 2 * exponential(n - 1) return exponential(n - 1) + exponential(n - 1)
``` ```
As you can see, the algorithm's runtime grows exponentially. For each additional input, the algorithm will take twice as long to run. As you can see, the algorithm's runtime grows exponentially. For each additional input, the algorithm will take twice as long to run.