The book was what I have expected from infrastructure book. There were no source codes, except some configuration scripts. The book contains the collection of experiences about cloud-native solutions. It mostly talks about development and deployment processes on the cloud-native.

Korean Open Source Software Conference has gathered many open source communities and contributors. It has become common for conferences these days have tracks: AI, BigDATA, Blockchain, Cloud. This conference was no exception. I have visited cloud development related topics.

Conference organized by NHN Enterprise (Intercontinental Seoul Parnas 19.11.2018) has encompassed many different topics. I have especially was interested in java related topics. How the big tech companies like NHN itself would approach the issue regarding to Oracle recent declarations about Java becoming non-free anymore.

P and NP is the problem that always comes out while we are studying algorithms, and usually, it comes up at the end of any algorithms book. The reason it comes out at the latest pages is that it is quite an advanced topic.

The book has been written by Cal Newport, a professor at the Georgetown University (Washington D.C). He wrote about the importance of the focusing and concentration on the work, by increasing the limit of the time we usually allocate for it. The Author writes a lot of different use cases for great historical people (some of them are still alive), how they have been going deep into their work. Who used what kind of technique, and how the technique was mastered. While going through the book I have realized that all of these characters had some similar points and patterns. Concentration Technique !!!

Problem

Given a graph which represents a flow network where every edge has a capacity. Also given two vertices source S and sink T in the graph. Find out the maximum possible flow from S to T with following constraints

Usually, the sorting algorithms determine the sort based on comparisons between the input elements. That is why they called comparison sorts algorithms. In here we would like to consider non-comparison sorts.

Algorithm is any well-defined computational procedure that takes some value, or set of values as input and produces some value, or set of values, as output.

The quicksort algorithm has a worst-case running time of O(n^2) on an input array of n numbers, and worst case happens when the array is sorted in descending order. Despite a worst-case running time, quicksort is often the best practical choice for sorting. Its average expected running time is O(n log n), and it has an advantage of sorting in place.