# Maximum Sum Subarray Problem

It has been some time in my career since I had to really analyze an algorithm and come up with an efficient way to solve a problem. When I do, it can really tax my brain.

Perhaps you have the same issue. It would bring me comfort to know that I am not the only one with this problem.

Perhaps you were never presented with a particular type of problem. Perhaps you never learned how to create an algorithm and determine how efficient it is. Perhaps it has just been a really long time since you had a real world problem that required a really smart and efficient solution and "good enough" has been, well, good enough. Let's face it, there are plenty of us that do not work in a life-or-death environment or where the pressure to optimize everything is paramount.

After being stumped on how to compute the largest sub-array with a maximum sum I decided to do a little research on how this could be solved.

There are several ways you can implement this solution. We will consider a few of them.

- Brute-Force. Just look at every possible combination and choose the best one.
- Divide and Conquer. This approach will divide the problem into a smaller problem and solve the smaller problems.
- Kadane's algorithm

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