Bertrand Meyer's technology+ blog

I am blogging live from the “Cloud Futures” conference organized by Microsoft in Redmond [1]. We had two excellent keynotes today, by Ed Lazowska [1] and David Patterson.

Lazowska emphasized the emergence of a new kind of science — eScience — based on analysis of enormous amounts of data. His key point was that this approach is a radical departure from “computational science” as we know it, based mostly on large simulations. With the eScience paradigm, the challenge is to handle the zillions of bytes of data that are available, often through continuous streams, in such fields as astronomy, oceanography or biology. It is unthinkable in his view to process such data through super-computing architectures specific to an institution; the Cloud is the only solution. One of the reasons (developed more explicitly in Patterson’s talk) is that cloud computing supports scaling down as well as scaling up. If your site experiences sudden bursts of popularity — say you get slashdotted — followed by downturns, you just cannot size the hardware right.

Lazowska also noted that it is impossible to convince your average  university president that Cloud is the way to go, as he will get his advice from the science-by-simulation  types. I don’t know who the president is at U. of Washington, but I wonder if the comment would apply to Stanford?

The overall argument for cloud computing is compelling. Of course the history of IT is a succession of swings of the pendulum between centralization and delocalization: mainframes, minis, PCs, client-server, “thin clients”, “The Network Is The Computer” (Sun’s slogan in the late eighties), smart clients, Web services and so on. But this latest swing seems destined to define much of the direction of computing for a while.

Interestingly, no speaker so far has addressed issues of how to program reliably for the cloud, even though cloud computing seems only to add orders of magnitude to the classical opportunities for messing up. Eiffel and contracts have a major role to play here.

More generally the opportunity to improve quality should not be lost. There is a widespread feeling (I don’t know of any systematic studies) that a non-negligible share of results generated by computational science are just bogus, the product of old Fortran programs built by generations of graduate students with little understanding of software principles. At the very least, moving to cloud computing should encourage the use of 21-th century tools, languages and methods. Availability on the cloud should also enhance a critical property of good scientific research: reproducibility.

Software engineering is remarkably absent from the list of scientific application areas that speaker after speaker listed for cloud computing. Maybe software engineering researchers are timid, and do not think of themselves as deserving large computing resources; consider, however, all the potential applications, for example in program verification and empirical software engineering. The cloud is a big part of our own research in verification; in particular the automated testing paradigm pioneered by AutoTest [3] fits ideally with the cloud and we are actively working in this direction.

Lazowska mentioned that development environments are the ultimate application of cloud computing. Martin Nordio at ETH has developed, with the help of Le Minh Duc, a Master’s student at Hanoi University of Technology, a cloud-based version of EiffelStudio: CloudStudio, which I will present in my talk at the conference tomorrow. I’ll write more about it in later posts; just one note for the moment: no one should ever be forced again to update or commit.

References

[1] Program of the Cloud Futures conference.

[2] Keynote by Ed Lazowska. You can see his slides here.

[3] Bertrand Meyer, Arno Fiva, Ilinca Ciupa, Andreas Leitner, Yi Wei, Emmanuel Stapf: Programs That Test Themselves. IEEE Computer, vol. 42, no. 9, pages 46-55, September 2009; online version here.

Once in a while one hits a tool that is just right. An example worth publicizing is the EasyChair system for conference management [1], which  — after a first experience as reviewer —  I have selected whenever I was in a position to make the choice for a new conference in recent years.

At first sight, a conference management system does not seem so hard to put together; it is in fact a traditional project topic for software engineering courses. But this apparent simplicity is deceptive, as a usable system must accommodate countless small and large needs. To take just one example, you can be a member of a program committee for a conference and also submit a paper to it; this implies strict rules about what you can see, for example reviews of other people’s papers with the referees’ names, and what you should not see. Taking care of myriad such rules and requirements requires in-depth domain knowledge about conferences, and a thorough analysis.

EasyChair is based on such an analysis. It knows what a conference is, and understands what its users need. Here for example is my login screen on EasyChair:

EasyChair knows about me: I only have one user name and one password. It knows the conferences in which I have been involved (and found them by itself). It knows about my various roles: chair, author etc., and will let me do different things depending on the role I choose.

The rest of the tool is up to the standards set by this initial screen. Granted, the Web design is very much vintage 1994; a couple of hours on the site by a professional graphics designer would not hurt, but, really, who cares? What matters is the functionality, and it is not by accident that EasyChair’s author is a brilliant logician [2]. Here is someone who truly understands the business of organizing and refereeing a conference, has translated this understanding into a solid logical model, and has at every step put himself in the shoes of the participants in the process. As a user you feel that everything has been done to make you feel comfortable  and perform efficiently, while protecting you from hassle.

Because this is all so simple and natural, you might forget that the system required extensive design. If you need proof, it suffices to consider, by contrast, the ScholarOne system, which as punishment for our sins both ACM and IEEE use for their journals.

Even after the last user still alive has walked away, ScholarOne will remain in the annals of software engineering, as a textbook illustration of how not to design a system and its user interface. Not the visuals; no doubt that site had a graphics designer. But everything is designed to make the system as repellent as possible for its users. You keep being asked for information that you have already entered. If you are a reviewer for Communications of the ACM and submit a paper to an IEEE Computer Society journal, the system does not remember you, since CACM has its own sub-site; you must re-enter everything. Since your identifier is your email address, you will have two passwords with the same id, which confuses the browser. (I keep forgetting the appropriate password, which the site obligingly emails me, in clear.) IEEE publications have a common page, but here is how it looks:

See the menu on the right? It is impossible  to see the full names of each of the “Transactio…”. (No tooltips, of course.) Assume you just want to know what one of them is, for example “th-cs”: if you select it you are prompted to provide all kinds of information (which you have entered before for other publications), before you can even proceed.

This user interface design (the minuscule menu, an example of what Scott Meyers calls the “Keyhole problem” [3]) is only a small part of usability flaws that plague the system. The matter is one of design: the prevailing viewpoint is that of the  designers and administrators, not the users. I was not really surprised when I found out that the system comes from the same source as the ISI Web of Science system (which should never be used for computer science, see [4]).

It is such a pleasure in contrast to see a system like EasyChair  — for all I know a one-man effort — with its attention to user needs, its profound understanding of the problem domain, and its constant improvements over the years.

References

[1] EasyChair system, at http://www.easychair.org.

[2] Andrei Voronkov, http://www.voronkov.com/.

[3] Scott Meyers, The Keyhole Problem, at http://www.aristeia.com/TKP/draftPaper.pdf; see also slides at http://se.ethz.ch/~meyer/publications/OTHERS/scott_meyers/keyhole.pdf

[4]  Bertrand Meyer, Christine Choppy, Jan van Leeuwen, Jørgen Staunstrup: Research Evaluation for Computer Science, in  Communications  of the ACM, vol. 52, no. 4, pages 131-134, online at http://portal.acm.org/citation.cfm?id=1498765.1498780 (requires subscription). Longer version, available at http://www.informatics-europe.org/docs/research_evaluation.pdf (free access).