# Recurrence Relation Cheat Sheet

Easily Solve Common Recurrences

Have you found it hard to solve the time complexity of recurrence relations ? I will show you how to solve some of the most common recurrence relations fast and easily without using any techniques other than memorization.

Below are the common recurrences.

**Note:** a, b, d and k are all constant values.

- T(n) = T(n-1)+b, T(1) = a

T(n) = O(n) - T(n) = T(n-1) + bn, T(1) = a

T(n) = O(n²) - T(n) = T(n/2) + b, T(1) = a

T(n) = O( log n) - T(n) = T(n/2) + bn, T(1) = a

T(n) = O(n) - T(n) = kT(n/k) + b, T(1) = a

T(n) = O(n) - T(n) = kT(n/k) + bn, T(1) = a

T(n) = O(n log n) - T(n) = T(n-1) + T(n-2) + d, T(1) = a, T(2) = b

T(n) = O(2^n) - T(n) = T(n-1) + b n^k, T(1) = a

T(n) = O(n^(k+1))

If you would like to learn more about Algorithm Analysis , you can take my online course here. I also have a course on Udemy.com called Recurrence Relation Made Easy where I help students to understand how to solve recurrence relations and asymptotic terms such as Big-O, Big Omega, and Theta. You can check out my YouTube channel of videos where I solve recurrence relations and perform algorithm analysis on code that anyone can check out for free !

Thanks for reading this article I hope its helpful to you all ! Keep up the learning, and if you would like more computer science, programming and algorithm analysis videos please visit and subscribe to my YouTube channels (randerson112358 & compsci112358 )

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Resources:

http://www.cs.cornell.edu/courses/cs211/2005sp/Lectures/L14-BigO/L14-15-Complexity.4up.pdf