Bertrand Meyer's technology blog

In the next few days I will post a few comments about a topic of particular relevance to the future of our field: empirical software engineering. I am starting by reposting two entries originally posted on my blog at Communications of the ACM. Here is the first (originally published as [1]). Let me use this opportunity to mention the LASER summer school [2] on this very topic — it is still possible to register.

Empirical software engineering papers, at places like ICSE (the International Conference on Software Engineering), used to be terrible.

There were exceptions, of course, most famously papers by Basili, Zelkowitz, Rombach, Tichy, Berry, Humphrey, Gilb, Boehm, Lehmann, Belady and a few others, who kept hectoring the community about the need to base our opinions and practices on evidence rather than belief. But outside of these cases the typical ICSE empirical paper — I sat through a number of them — was depressing: we made these measurements in our company, found these results, just believe us. A question here in the back? Can you reproduce our results? Access our code? We’d love you to, but unfortunately we work for a company — the Call for Papers said industry contributions were welcome, didn’t it? — and we can’t give you the details. So sorry. But trust us, we checked our results.

Actually, there was another kind of empirical paper, which did not suffer from such secrecy: the university study. Hi, I am professor Bright, the well-known author of the Bright method of software development. Everyone knows it’s the best, but we wanted to assess it scientifically through a rigorous empirical study. I gave the same programming problem to two groups of third-year undergraduates; one group was told to use the Bright method, the other not. Guess what? The Bright group performed 67.94% better! I see the session chair wanting to move to the next speaker; see the details in the paper.

For years, this was most of what we had: unverifiable industry reports and unconvincing student experiments.

And suddenly the scene has changed. Empirical software engineering studies are in full bloom; the papers are flowing, and many are good!

What triggered this radical change is the availability of open-source repositories. Projects such as Linux, Eclipse, Apache, EiffelStudio and many others have records going back 10, 15, sometimes 20 years. These records contain the true history of the project: commits (into the configuration management system), bug reports, bug fixes, test runs and their results, developers involved, and many more elements of project data. All of a sudden empirical research has what any empirical science needs: a large corpus of objects to analyze.

Open-source projects have given the decisive jolt, but now we can rely on industrial data as well: Microsoft and other companies have started making their own records selectively available to researchers. In the work of authors such as Zeller from Sarrebruck, Gall from Uni. Zurich or Nagappan from Microsoft, systematic statistical techniques yield answers, sometimes surprising, to questions on which we could only speculate. Do novices or experts cause more bugs? Does test coverage correlate with software quality, and if so, positively or negatively? Little by little, we are learning about the true properties of software products and processes, based not on fantasies but on quantitative analysis of meaningful samples.

The trend is unmistakable, and irreversible.

Not all is right yet; in the second installment of this post I will describe some of what still needs to be improved for empirical software engineering to achieve full scientific rigor.

References

[1] Original version of this post, here.

[2] LASER summer school 2010, at http://se.ethz.ch/laser.

In the decades since structured programming, many of the advances in software engineering have come out of non-university sources, mostly of four kinds:

• Start-up technology companies  (who played a large role, for example, in the development of object technology).
• Industrial research labs, starting with Xerox PARC and Bell Labs.
• Independent (non-university-based) author-consultants. 
• Independent programmer-innovators, who start open-source communities (and often start their own businesses after a while, joining the first category).

 Academic research has had its part, honorable but limited.

Why? In earlier posts [1] [2] I analyzed one major obstacle to software engineering research: the absence of any obligation of review after major software disasters. I will come back to that theme, because the irresponsible attitude of politicial authorities hinders progress by depriving researchers of some of their most important potential working examples. But for university researchers there is another impediment: the near-impossibility of developing serious software.

If you work in theory-oriented parts of computer science, the problem is less significant: as part of a PhD thesis or in preparation of a paper you can develop a software prototype that will support your research all the way to the defense or the publication, and can be left to wither gracefully afterwards. But software engineering studies issues that arise for large systems, where  “large” encompasses not only physical size but also project duration, number of users, number of changes. A software engineering researcher who only ever works on prototypes will be denied the opportunity to study the most significant and challenging problems of the field. The occasional consulting job is not a substitute for this hands-on experience of building and maintaining large software, which is, or should be, at the core of research in our field.

The bodies that fund research in other sciences understood this long ago for physics and chemistry with their huge labs, for mechanical engineering, for electrical engineering. But in computer science or any part of it (and software engineering is generally viewed as a subset of computer science) the idea that we would actually do something , rather than talk about someone else’s artifacts, is alien to the funding process.

The result is an absurd situation that blocks progress. Researchers in experimental physics or mechanical engineering employ technicians: often highly qualified personnel who help researchers set up experiments and process results. In software engineering the equivalent would be programmers, software engineers, testers, technical writers; in the environments that I have seen, getting financing for such positions from a research agency is impossible. If you have requested a programmer position as part of a successful grant request, you can be sure that this item will be the first to go. Researchers quickly understand the situation and learn not even to bother including such requests. (I have personally never seen a counter-example. If you have a different experience, I will be interested to learn who the enlightened agency is. )

The result of this attitude of funding bodies is a catastrophe for software engineering research: the only software we can produce, if we limit ourselves to official guidelines, is demo software. The meaningful products of software engineering (large, significant, usable and useful open-source software systems) are theoretically beyond our reach. Of course many of us work around the restrictions and do manage to produce working software, but only by spending considerable time away from research on programming and maintenance tasks that would be far more efficiently handled by specialized personnel.

The question indeed is efficiency. Software engineering researchers should program as part of their normal work:  only by writing programs and confronting the reality of software development can we hope to make relevant contributions. But in the same way that an experimental physicist is helped by professionals for the parts of experimental work that do not carry a research value, a software engineering researcher should not have to spend time on porting the software to other architectures, performing configuration management, upgrading to new releases of the operating system, adapting to new versions of the libraries, building standard user interfaces, and all the other tasks, largely devoid of research potential, that software-based innovation requires.

Until  research funding mechanisms integrate the practical needs of software engineering research, we will continue to be stymied in our efforts to produce a substantial effect on the quality of the world’s software.

References

[1] The one sure way to advance software engineering: this blog, see here.
[2] Dwelling on the point: this blog, see here.

Part of the experience of being a scientist, in the industrial age of publication, is the rejection letter; especially the damning review whose author, anonymous of course, does not appear particularly competent. I have my own treasured collection, which I will publish one day. For a fiction so artfully designed as to be almost as good as the real thing, you can check  Simone Santini’s hilarious parody [1], a true classic.

Although there are a few references to it around the Web, I do not think it is as well known as it deserves to be. What Santini did was to imagine rejection letters for famous papers. He stated [2] that:

The reviews are a collage of reviews that I have seen of some papers (mine and of other people) that have been rejected because, I thought, the reviewer had completely misunderstood the paper. After a rejection at a database conference for what I thought were completely preposterous reasons, I had the idle thought that today even Codd’s paper on relational data bases (the foundation of the whole field) would never make it into a major data base conference…Many of the sentences that I use in the article are from actual reviews.

A sample from the imaginary Codd rejection letter:

E.F. CODD “A Relational Model of Data for Large Shared Data Banks.”  … The formalism is needlessly complex and mathematical, using concepts and notation with which the average data bank practitioner is unfamiliar. The paper doesn’t tell us how to translate its arcane operations into executable block access.

Adding together the lack of any real-world example, performance experiment, and implementation indication or detail, we are left with an obscure exercise using unfamiliar mathematics and of little or no practical consequence. It can be safely rejected.

All the others are gems too: Turing’s Entscheidungsproblem paper (“If the article is accepted, Turing should remember that the language of this journal is English and change the title accordingly”); Dijstra’s Goto considered harmful; Hoare’s 1969 axiomatic semantics paper (the author “should also extend the method to be applicable to a standard programming language such as COBOL or PL/I and provide the details of his implementation, possibly with a few graphics to show how the system works in practice”) etc.

To avoid a spoiler I will  cite no more;  you should read the paper if you do not know it yet. It rings so true.

References

[1] Simone Santini: We Are Sorry to Inform You …, in IEEE Computer, vol. 38, no. 12, pp. 128, 126-127, December 2005,  online on the IEEE site. There is also a copy here.

 [2] http://www.omlettesoft.com/newjournal.php3?who=Lord+Omlette&id=1134629858.

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).