Tag Archives: computer science

Architectural Recovery – Georgia Tech – Software Development Process

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And sometimes architectural drift and erosion get you so far away from the point where your software architecture should be that your architecture is completely degraded, at this point, you have two main options. The first option is to keep frantically tweaking the code, And this normally leads to disaster. Why? Because you only make things worse, You don’t know exactly what you are changing and therefore you’re stabbing in the dark trying to fix your system. The other possibility is that you can try to determine […]

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Types of Architectural Styles – Georgia Tech – Software Development Process

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  So what does it mean to know architectural styles? There are many many, many architectural styles. So we cannot cover them all here. What I want to do instead is, I want to mention a few of those. And then I want to go in more depth, on one of them. So the first item I want to mention is pipes and filters. And pipes and filters indicate an architectural style in which a chain of processing elements, which can be processes, threads, or co-routines, is […]

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A Philosophy of Software Design | John Ousterhout | Talks at Google

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  [MUSIC PLAYING] SPEAKER 1: OK. So, welcome. Good morning, everyone. It’s my pleasure to welcome Professor Ousterhout for this Talk at Google presentation. My name is [INAUDIBLE]. I work in the Technical Infrastructure Cloud. A very quick intro to John to get things started here– John is a Professor of Computer Science at Stanford University. He spent, before that, 14 years in industry where he founded two companies, Scriptics and Electric Cloud and, before that, 14 years as a professor at UC Berkeley. Anybody here who […]

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Data Mining with Weka (2.3: Repeated training and testing)

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  Hello again! In the last lesson, we looked at training and testing. We saw that we can evaluate a classifier on an independent test set, or using a percentage split, with a certain percentage of the dataset used to train and the rest used for testing, or — and this is generally a very bad idea — we can evaluate it on the training set itself, which gives misleadingly optimistic performance figures. In this lesson, we’re going to look a little bit more at training and […]

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