We’ve seen how to do the naive approach towards pattern matching. So what about other algorithms that are much more better at doing this task? This is the Knuth-Morris-Pratt (KMP) algorithm for pattern matching.

We all should all know what string searching is. We have a pattern p and some string s, and we wish to see if p exists in s. There are a number of ways to do this, and this is one of those many ways; the naive approach.

Okay, I didn’t see that James had made a video about the very same subject. Great minds think alike I guess? Sigh. Well, here it is: The Dynamic Programming method for solving a 0/1 Knapsack Problem explained, in depth, by me in under 11 minutes!

Bug 1: Ignore the “The cell with the green circle around has a capacity of” blah blah etc. because I uploaded the wrong version ._. The green circle should be around cell (3,1).
Bug 2: I circle item ’1′ when I should circle item ’3′ at the end when we’re going through the keep array. I fail.
Bug 3: I say ’2′ somewhere instead of ’3′. See if you can spot it.

We’ve all used those horrible SATNAV’s to get from one place to another. But how do they calculate the path we must follow in order to minimize the time needed.

This is a shortest distance problem, which shall be covered in this post via Dijkstra’s Algorithm.

We have seen some of the key concepts to Graphs; What a node is, an edge – as well as definitions for Digraphs and Undirected Graphs – and other bits ‘n’ bobs :) .

But one question stills looms; How do we traverse a Graph?

Here we shall look at two of the key traversing algorithms for Graphs: