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I found this post arguing that one can draw inspiration for writing code from poetry:

Poetry (…) is an abstract block of words in which every one must carry meaning if the poem is to be any good. We value the poem for the beauty not only of the story or image given, but of the way in which it is constructed as well. It tends to be much denser and more compact than prose. When you read it, you must proceed carefully and consider the meaning of each word, and each group of words, and pay attention for double meanings and allusions if you are to grasp it fully.

Larry Wall has written a post on scripting languages titled “Programming is Hard, Let’s Go Scripting…” in which he challenges the preconception that programming and scripting are different endeavors. As always Perl 6 is at the core of the message. And as always it’s worth reading.

Colin Percival wrote two comprehensive how-tos on keep FreeBSD updated.

The first is for minor upgrades, the second for major version changes.

Very neat thing, this freebsd-update tool, indeed. But beware, it only works for Releases and only with generic kernels, so perhaps you are in for a make && make insallkernel && make installworld routine for one last time.

This is great: ISO and UTC are neither acronyms nor initials, more like kind of false friends.

So again the question about the best programming language was put up. This time for an aspiring 13-year old.

The answer given by Ned Batchelder is concise and in my opinion a great starting point not just for children. The main point is that there is no single best choice and that the language would be a means to an end and not an academic pursuit in itself. This is quite close to the general definition of a sound choice of a programming language and every developer should ask himself this question for every job at hand!

Testing, especially when doing test driven developement, is only effective if the tests cover 100% of the code, i.e. running all tests means all of the production code has been executed.

But coverage testing is not so easy as it seems. One can give simplistic examples which have 100% test coverage but still are buggy. The reason is simple: branching (and combination of paths) can produce a plethora of possibilities. But once every line of code is executed once, by definition, the coverage is 100%, although not every permutation has been tried.

An introduction to this topic can be found in Ned Batchelder’s blog, more at Wikipedia and here.

A roundup on the old struggle between too simple and too complicated development strategies: On the one side there are the quick fixes on the other the overly perfect designs. Obviously, these extremes are rarely reality but a constant threat to every project.

Keeping the design simplicistic means risking extensibility and maintainability. Even though it’s easy now, no one will remember the ad-hoc decisions made during coding.

The opposite extreme is over-engineering, the fiddling with the design to make it even more pluggable or extensible or use the newest patterns. Especially seasoned developers are prone to this behavior.

To counteract these extremes and in particular the second there is the “Make it Work First!” motto. It helps to get a first look and feel of the program while requiring to keep an eye on the ease of refactoring since the first version will have to be modified almost surely.

I like this very personal history of reverse engineering and the suggested test driven approach taken by S. Lott as a solution.

The idea is to extract an object structure from procedural code, cover it by unit tests to ensure its functionality and then take on the next piece of code. The question the author puts up, if this really is test driven in the strictest sense. I would not be this picky about it, since reverse engineering is a far more painstaking process than starting from scratch.

Like with computers, multi-tasking is a mere illusion for humans. There are not so many things one can do simultaneously at any given time. So we (computers and humans, especially when in front of the machines) have to simulate it by constantly switching from one task to another and then back again. But these context-switches cost time and energy, giving an upper limit of how well we can put up with more than one thing to do. And in contrast to machines our context switching is dependent on the complexity of the task we want to jump into and of its familiarity with the task we are trying to get out of.

It is then not very surprising that if we cram in our daily schedule lots of different things, little gets done. What is surprising though is that neither the project planning tools nor any of the calendar programs allow to schedule for these context-switches in an easy straight-forward way: there is no benefit in trying to schedule as large chunks as possible for any given task, so they create the illusion that 5 times one hour is as productive as one times 5 hours work!

So back to your schedule and tidy up!

There are quite a few parallel programming environments around: MPI, OpenMP, Ct, HPF, TBB,Shmemm, Portals, ZPL, BSP, CHARM++, Cilk, NESL, PVM, Pthreads, mpC, Tstreams, GA, TPIE, UPC, Titanium, Parlog, Split-C …

This creates a problem of choice for programmers, where one can argue that less choice would be beneficial; that it would allow to focus on improving the remaining languages.

An other argument is that a new and hence “yet another” parallel programming language will solve the problem.

This alone is an example of the problem of choice.