Category Archives: Software Engineering

GNU now developing rack systems

It seems GNU are branching out: from software, into rack systems ;)

When Agile goes wrong

I just received this message from customer support for a product I pay a subscription for (Oh, why not: this is Todoist.com): Unfortunately we don’t have a roadmap for future features. To stay flexible and add features based on requests, we work on a few options, implement them and then decide what’s next so unfortunately […]

An appeal for correct, capable, future-proof math in nascent programming languages

Let me start by saying that, the math in most programming languages is WRONG.  In most cases, there is little to be done about this, except perhaps tack on some new classes which allow new code to be written to fix it. However, nascent languages, like Rust, which I’ll mainly address here, have an opportunity […]

C++, it’s time to go

I’ve been studying a lot of languages lately, looking for a modern, parallel language which is a deserving successor to C/C++/Python as my main, go-to language for Getting Things Done.  Someone on Reddit was specifically asking why C++ isn’t ideal any more, and I wrote up this response based on my research.  So, I thought […]

Projects, old and new

NOTE: See my GitHub page, for a complete list of public projects. I’ve recently taken a few projects out of storage (literally: the mountpoint is called “storage” :), and posted them on GitHub.  So, I thought I’d take a moment to point out each one.  I’m also going to get into some current projects, which […]

Game complexity, and the art of programming

Someone asked on reddit: “How lines of text (coding) can turn into beautiful, complex environments in games?” I wrote up a quick reply, which I liked enough to post here instead.  I should really take the time to write it more carefully, building the explanations, evidence, etc.  That could be a powerful read, or maybe […]

PyPy vs. CPython: Speed and memory usage benchmarks

Following on from part 1 of this article, I’d like to take you through some PyPy vs. CPython benchmarks. Benchmarks: Many Objects Note: in all benchmarks, I’m measuring total memory use for the entire interpreter run, but only measuring time taken across the code I’m actually interested in testing. There’s a subtle (depending on your […]

On the virtues of PyPy as your default interpreter

I get a lot of use out of PyPy. In fact, it’s become my default python interpreter, replacing CPython, at least for Python 2.x code. Python 3.x support in PyPy is coming real soon now; most of the tests are passing, so the next release will probably make it happen. So, I wanted to write […]