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Why is it so hard to understand software? Or to put it more to the point: What makes it so hard to write understandable software? This question is the driving theme of this article: the quest to uncover techniques of complexitiy management that go beyond established principles of software engineering such as information hiding and modularization and which are unbound to specific paradigms like object-orientation or functional programming. For that reason I studied two kinds of software systems in depth: telecommunication systems, modeling and programming languages. I did so for two reasons: First, telecommunication systems are among the oldest, largest and most successful systems. They are highly reliable, roboust and scalable. What are their key design principles that make them stand such demanding requirements? Second, each modeling and programming language is its creators attempt to provide a set of language conceptions to address and manage complexity. A language – be it a prog...

Es gibt dieses wunderbare Bild der Hacker! Ich meine die Geeks, nicht die Kriminellen. Hacker leben mit dem Computer, sie scheinen eins mit ihm zu sein. Computer und Hacker gehen eine Symbiose ein. Hacken ist Leben, Leben ist Hacken. Menschen und soziale Kontakte sind eine wunderbare Sache -- sofern man mit ihnen im Chat oder in anderen virtuellen Welten kommuniziert und sie dort trifft. Hacker sind mindestens 10x produktiver als normal sterbliche Programmierer. Und Hacker sind nicht nur produktiver, ihr Code scheint nicht von dieser Welt zu sein. Kein Mensch versteht die Kryptik und die Gedankengänge im Code eines Hackers. Kurzum, wir bewundern die Hacker. Ein bissel hätten wir gerne von ihnen "vererbt" bekommen, wir, denen das Programmieren nicht ganz so locker von der Hand geht. Gibt es die Hacker überhaupt? Oder sind sie ein Mythos? Ja und nein. Es gibt Menschen, die das Bedienen ihrer Maschinen gründlich erlernt haben. Die 1000 Tastenkürzel kennen, mit Emacs arbeit...

It was an experiment -- and it went much better than I had imagined: I used Factor (a concatenative programming language) as the subject of study in a project week at Heilbronn University in a course called "Software Engineering of Complex Systems" (SECS). Maybe we are the first university in the world, where concatenative languages in general and Factor in specific are used and studied. Factor is the most mature concatenative programming language around. Its creator, Slava Pestov, and some few developers have done an excellent job. Why concatenative programming? Why Factor? Over the years I experimented with a lot of different languages and approaches. I ran experiments using Python, Scheme and also Prolog in my course. It turned out that I found myself mainly teaching how to program in Python, Scheme or Prolog (which still is something valuable for the students) instead of covering my main issue of concern: mastering complexity. In another approach I used XML as a tool ...

Recently, I had an interesting discussion about "What's the distinguishing feature of so-called scripting languages?" We easily agreed on calling Python, Ruby, Groovy, Tcl, Perl etc. as scripting languages. But then the trouble started: What distinguishes Python, Ruby etc. from Java, C#, C++ and similar languages? Is it dynamic typing? Are they more introspective? Isn't it so that meta-programming is no difficulty at all with scripting languages? Some whisper that a Python or Ruby programmer is as much as 2-5 times more productive than a Java/C# programmer. As a matter of fact, programs written in so-called scripting languages tend to be significantly shorter than their "unscripted" counterparts. Such a discussion typically moves over into an almost religious debate about static and dynamic typing. Programs in Python and Ruby might be shorter but they are unsafe because of dynamic typing. Static typing is the way to go for large programs being developed with...