{"id":414819,"date":"2024-06-29T23:59:33","date_gmt":"2024-06-29T23:59:33","guid":{"rendered":"http:\/\/savepearlharbor.com\/?p=414819"},"modified":"-0001-11-30T00:00:00","modified_gmt":"-0001-11-29T21:00:00","slug":"","status":"publish","type":"post","link":"https:\/\/savepearlharbor.com\/?p=414819","title":{"rendered":"Algorithms in Go<\/span>"},"content":{"rendered":"
<\/div>\n
\n
\n
\n
\n

Most solutions to algorithmic problems can be grouped into a rather small number of patterns. When we start to solve some problem, we need to think about how we would classify them. For example, can we apply\u00a0fast and slow<\/code> \u0430lgorithmic pattern or do we need to use\u00a0cyclic sort<\/code>pattern? Some of the problems have several solutions based on different patterns. In this series, we discuss the most popular algorithmic patterns that cover more than 90% of the usual problems.<\/p>\n

It is different from High-School Algorithms 101 Course, as it is not intended to cover things like Karatsuba algorithm (fast multiplication algorithm) or prove different methods of sorting. Instead, Algorithmic Patterns focused on practical skills needed for the solution of common problems. For example, when we set up a Prometheus alert for high request latency we are dealing with Sliding Window Pattern<\/a>. Or let say, we organize a team event and need to find an available time slot for every participant. At the first glance, it is not obvious that in this case, we are actually solving an algorithmic<\/a> problem. Actually, during our day we usually solve a bunch of algorithmic problems without realizing that we dealing with algorithms.<\/p>\n

The knowledge about Algorithmic Patterns helps one to classify a problem and then apply the appropriate method.<\/p>\n

But probably most importantly learning algorithmic patterns boost general programming skills. It is especially helpful when you are debugging some production code, as it trains you to understand the execution flow.<\/p>\n

Patterns covered so far:<\/p>\n