November 2008 – keeping simple

The last time I went to a “Supercomputing” conference, Jim Gray came by to talk to me and Cort about PowerPC Linux. That must have been in 2000 or 1999. We had gone by the AIX booth and been roundly sneered at by IBMs Operating System Gurus and were walking away, somewhat crestfallen, when Gray stopped by to talk and to illustrate why he was such a widely admired person. Yesterday, I went by SC08 here in the Capital of Texas, snuck into a talk by one of the poor people who survived my Operating System class back before 2000 and roamed the floor looking at all that, as we highly trained and educated technical people say, “stuff” on the floor.

The problem of parallel computing is, of course, the standard topic of SupercomputingÂ and currently Supercomputing seems to be a celebration of MPI. I was amazed to see that people have added parallel constructs and even MPI to Mathematica. Why not just try to automatically extract parallelism from the high level constructs?

Not as strange as the Tokyo University use of parallel Ruby for scientific computing though.

Dijkstra versus Perlis (updated)

Dijkstra wrote:

He [Perlis] published a very obnoxious paper arguing against a mathematical approach to programming cite

The paper by De Millo, Lipton and Perlis starts as follows:

Many people have argued that computer programming should strive to become more like mathematics. Maybe so, but not in the way they seem to think. The aim of program verification, an attempt to make programming more mathematics-like, is to increase dramatically one’s confidence in the correct functioning of a piece of software, and the device that verifiers use to achieve this goal is a long chain of formal, deductive logic. In mathematics, the aim is to increase one’s confidence in the correctness of a theorem, and it’s true that one of the devices mathematicians could in theory use to achieve this goal is a long chain of formal logic. But in fact they don’t. What they use is a proof, a very different animal. Nor does the proof settle the matter; contrary to what its name suggests, a proof is only one step in the direction of confidence. We believe that, in the end, it is a social process that determines whether mathematicians feel confident about a theorem–and we believe that, because no comparable social process can take place among program verifiers, program verification is bound to fail.

To me, the problem with Dijkstra is that he was so sharp and such a good writer that he was able to make persuasive cases out of obviously wrong ideas. Dijkstra wanted to be a scientist in the model of theoretical physics, not an engineer. I’m pretty confident that Dijkstra was wrong: programming is engineering – in fact, physics is not as far from engineering as some people would like to believe. I’m not a huge fan of the engineering discipline as it exists in the USA. It has all sorts of negative aspects – including those Dijkstra railed against. But the vision of a programmer as, not a mathematician, but a formal logician flying far above the grubby compromises and trade-offs of mere engineering in a platonic bubble of pure reasoning is wrongheaded.

Dijkstra published some criticism of the Demillo paper at the time and in their response the authors stated something that, as far as I know, remains true

We must begin by refusing to concede that our confidence in a piece of real software has ever been increased by a proof of its correctness

When I was in graduate school (a long time ago), a famous formal methods scholar came for a talk and explained to us that formal methods were needed if we were ever going to develop fault tolerant software. I pointed out that, for example, the Tandem Software worked pretty well in practice. “It cannot”, retorted the famous scholar.

So there.

Here’s Edsger Dijkstra discussing the birth of the use of axiomatics in computer science – the start of “formal methods” research. What’s striking is the assumed choice between “axiomatic” and “mechanistic” as if there was no other way. In a later note he writes:

And now we are back at our old dilemma. Either we take by definition all properties of the model as relevant, or we specify in one way or another which of its properties are the relevant ones. In the first case we have failed to introduce in the name of “divide et impera” an interface that would allow us to divide and rule and the study of how we could build upon the (only implicitly defined) interface seems bound to deteriorate into a study of the model itself; in the second case we are again close to the axiomatic method….

[…]

Or, to put it in another way: if the traditional automata theory tends to make us insensitive to the role interfaces could and should play in coping with complex designs, should it then (continue to) occupy a central position in computing science curricula?

And I’m struck by the idea that seems utterly wrong to me, that one either uses the methods of formal logic OR one is stuck without any ability to abstract or underspecify, And it’s also interesting to see this impoverished view of automata theory that underpins so much of the formal methods literature.

The reason mathematics has advanced so much was not because of the Euclidean axioms-lemma-theorem straitjacket, but in spite of it. Luckily, when we actually discover mathematics, we do it the Babylonian way, empirically and algorithmically. It is only when it is time to present it, that we put on the stifling Greek formal attire.

so says Doron Zeilberger

Updated: with minor format improvements 2/16/2016 and merged with an earlier article 10.2.2016 Erev RH.