I was working through some more example algorithms to determine their respective runtimes in Big O Notation. The optimal runtime of a comparison sort algorithm was mentioned and it got me thinking. I wanted to ideally write my own comparison sort algorithm so that I could compare my initial solution to the optimal solution. I have been trying to work out how they got an optimal runtime of O(N * log N) I think this might be another great problem to look into.

TLDR;

Okay, so here are the highlights of what I did:

• Still reading through the book “Cracking the Coding Interview” by Gayle Laakmann McDowell. I got through examples four through seven. I got stumped on example eight because of the “Comparison Sort Algorithm” mentioned. I have written a few comparison sort algorithms in my day but I have never really checked to see if they ran at the optimal runtime. I think that will be my objective before I move on to another example.
• Got through the first section in the “Introduction to Microsoft Power Platform”. So far it seems like a number of the tools are built with the least amount of coding required. I am not sure how I feel about this. Part of me, isn’t a fan but the other part of me recognizes that it can be valuable to non-developer users. I still have a lot more work to do on the subject but hopefully it all makes sense. I am going to keep an open mind as I go through the material.

Conclusion

That’s all for today. If you are interested in the MIT course you can check out the video lecture I’m currently going through. The lecture is helpful but isn’t sufficient by itself. Anyways, until next time PEACE!