Finally, you get to see a tree :D
This post will cover the basics of what Deep and Surface Structure trees are, as well as a little bit on moved words – only little though!
Finally, you get to see a tree :D
This post will cover the basics of what Deep and Surface Structure trees are, as well as a little bit on moved words – only little though!
This is the second part to the Basic Lambda Calculus 1. In this we’ll go through a proper example.
This post will explain some of the basics of Lambda Calculus, mainly Alpha-Conversion and Beta-Reduction. We’ll also see a quick example of a simple sentence.
This post is being written with me being slightly ill… so some bits may make no sense whatsoever – sorry :(
This is going to be a very quick post, mainly because so many people have asked me what ACID means.
This post applies to a lot of topics / modules; but mainly to Databases and Distributed Computing.
Now for the final section about these architectures. This post will cover the aspects concerning the REST Architecture. It really simple to grasp the concept of it, so lets take a look!
No, this post is not about the slippery block of nice smelling soap! SOAP in Distributed Computing is another form of message exchanging between peers, and here we describe how it does this.
This is the second part to SOA’s, in this post we’ll have a look at Message-Oriented Middleware (MOM’s) and other various things to finish of this section.
Over the next – possibly – 2 or 3 posts, i am going to be posting about SOA, Services and MOM’s. Then they’ll be a post about SOAP, then finally one about REST. All of which are Architectures for Computing in their own right.
However, this post will mark the start – explaining in detail what SOA really is, what a Service is, as well as MOM’s (i will try a reframe from ‘ya mom’ jokes) :)
Distributed Systems
A complete revision summary by James Bedford.
This summary now contains everything.
Last updated:
11:38pm - 25/05/10.
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.
This post will be brief. It just contains a load of terminology for parts of graphs, such as:
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:
Nodes can be connected to other nodes – otherwise it would be a bleeding useless graph! :D
But how do we know which node is connected to which nodes? Welcome to the wonderful world of Adjacency Lists and Matrices!
Also, i apologise for the long pause in posts! :(