The Demand for Software Quality

A Conversation with Bertrand Meyer, Part I

by Bill Venners
October 27, 2003

Bertrand Meyer talks with Bill Venners about the increasing importance of software quality, the commercial forces on quality, and the challenges of complexity.

Bertrand Meyer is a software pioneer whose activities have spanned both the academic and business worlds. He is currently the Chair of Software Engineering at ETH, the Swiss Institute of Technology. He is the author of numerous papers and many books, including the classic Object-Oriented Software Construction (Prentice Hall, 1994, 2000). In 1985, he founded Interactive Software Engineering, Inc., now called Eiffel Software, Inc., a company which offers Eiffel-based software tools, training, and consulting.

On September 28, 2003, Bill Venners conducted a phone interview with Bertrand Meyer. In this interview, which will be published in multiple installments on, Meyer gives insights into many software-related topics, including quality, complexity, design by contract, and test-driven development. In this initial installment, Meyer discusses the increasing importance of software quality, the commercial forces on quality, and the challenges of complexity.

The Importance of Software Quality

Bill Venners: In a 2001 interview with InformIT, you said, "The going has been so good that the software profession has been able to treat quality as one issue among many. Increasingly it will become the dominant issue." Why?

Bertrand Meyer: As the use of computers pervades more and more of what society does, the effects of non-quality software just becomes unacceptable. Software is becoming more ambitious, and we rely on it more and more. Problems that could be dismissed quite easily before are now coming to the forefront.

There is a very revealing quote by Alan Perlis in his preface to the MIT book on Scheme, The Structure and Interpretation of Computer Programming, by Abelson and Sussman. Alan Perlis wrote:

I think that it's extraordinarily important that we in computer science keep fun in computing. When it started out, it was an awful lot of fun. Of course, the paying customer got shafted every now and then, and after a while we began to take their complaints seriously. We began to feel as if we really were responsible for the successful, error-free perfect use of these machines. I don't think we are. I think we're responsible for stretching them, setting them off in new directions, and keeping fun in the house.

That is typical of the kind of attitude that says "Sure, we can do whatever we like. If there's a problem we'll fix it." But that's simply not true anymore. People depend on software far too fundamentally to accept this kind of attitude. In a way we had it even easier during the dot-com boom years, between 1996 and 2000, but this is not 1998 anymore. The kind of free ride that some people were getting in past years simply doesn't exist anymore.

The Harvard Business Review published an article in May 2003, "IT Doesn't Matter" by Nicholas Carr, that stated that IT hasn't delivered on its promises. It is a quite telling sign of how society at large is expecting much more seriousness and is holding us to our promises much more than used to be the case. Even though it may still seem like we do have a free ride, in fact that era is coming to a close. People are watching much more carefully what we're doing and whether they're getting any return for their money. And the heart of that is quality.

Commercial Forces on Software Quality

Bill Venners: In your paper, The Grand Challenge of Trusted Components, you write "There is a quality incentive, but it only leads to the acceptability point: the stage at which remaining deficiencies do not endanger [the product's] usefulness to the market. Beyond that point, most managers consider that further quality enhancing measures yield a quickly diminishing return on investment." How do commercial pressures affect software quality?

Bertrand Meyer: Commercial pressures affect software quality partly positively and partly negatively. It is almost tempting to use as an analogy the Laffer Curve, which was popular for a while in so-called Reaganomics. I'm not an economist, and I hear that the theory has been by now discredited, so I really don't want to imply that the Laffer Cruve is fundamentally true in economics. Nevertheless, the Laffer Curve is the idea that if you tax people at zero percent, the state suffers because it doesn't get any revenue. If you tax people at 100%, it's in the end no better, because if people are not making any money, they will stop working, and the state will also not get any revenue. It's a rather simplistic argument. Although it is pretty clear the Laffer Curve has an element of truth, I'm not sure how precise or accurate it is in economics. But as an analogy, it describes well the commercial pressures on software quality.

If you produce a software system that has terrible quality, you lose because no one will want to buy it. If on the other hand you spend infinite time, extremely large effort, and huge sums of money to build the absolutely perfect piece of software, then it's going to take so long to complete and it will be so expensive to produce that you'll be out of business anyway. Either you missed the market window, or you simply exhausted all your resources. So people in industry try to get to that magical middle ground where the product is good enough not to be rejected right away, such as during evaluation, but also not the object of so much perfectionism and so much work that it would take too long or cost too much to complete.

The Challenge of Complexity

Bill Venners: You said in your book, Object Oriented Software Construction, "The single biggest enemy of reliability and perhaps of software quality in general is complexity." Could you talk a bit about that?

Bertrand Meyer: I think we build in software some of the most complex artifacts that have ever been envisioned by humankind, and in some cases they just overwhelm us. The only way we can build really big and satisfactory systems is to put a hold on complexity, to maintain a grasp on complexity. Something like Windows XP, which is 45 million lines of code or so, is really beyond any single person's ability to comprehend or even imagine. The only way to keep on top of things, the only way to have any hope for a modicum of reliability, is to get rid of unnecessary complexity and tame the remaining complexity through all means possible.

Taming complexity is really fundamental in the Eiffel approach. Eiffel is there really to help people build complex, difficult things. You can certainly build easy or moderately difficult systems using Eiffel better than using other approaches, but where Eiffel really starts to shine is when you have a problem that is more complex than you would like and you have to find some way of taming its complexity. This is where, for example, having some relatively strict rules of object modularity and information hiding is absolutely fundamental. The kinds of things that you find in just about every other approach to circumvent information hiding don't exist in Eiffel. Such strict rules sometimes irritate programmers at first, because they want to do things and they feel they can't, or they have to write a little more code to achieve the result. But the strictness is really a major guard against the catastrophes that start to come up when you're scaling up your design.

For example, in just about every recent object-oriented language, you have the ability, with some restriction, of directly assigning to a field of an object: x.a = 1, where x is an object, a is a field. Everyone who has been exposed to the basics of modern methodology and object technology understands why this is wrong. And then almost everyone says, "Yes, but in many cases I don't care. I know exactly what I'm doing. They are my objects and my classes. I control all the accesses to them, so don't bother me. Don't force me to write a special routine to encapsulate the modification of field a." And on the surface, people are correct. In the short term, on a small scale, it's true. Who cares?

But direct assignment is a typical kind of little problem that takes up a completely new dimension as you start having tens of thousands, hundreds of thousands, or millions of lines of code; thousands or tens of thousands of classes; many people working on the project; the project undergoing many changes, many revisions, and ports to different platforms. This kind of thing, direct assignment of object fields, completely messes up the architecture. So it's a small problem that becomes a huge one.

The problem is small in the sense that fixing it is very easy in the source. You just prohibit, as in Eiffel, any direct access to fields and require that these things be encapsulated in simple procedures that perform the job—procedures which, of course, may then have contracts. So it's really a problem that is quite easy to kill in the bud. But if you don't kill it in the bud, then it grows to a proportion where it can kill you.

Another example is overloading: giving the same name to different operations within the same class. I know this is controversial. People have been brainwashed so much that overloading is a good thing that it is kind of dangerous to go back to the basics and say that it's not a good thing. Again, every recent language has overloading. Their libraries tend to make an orgy of overloading, giving the same name to dozens of different operations. This kind of apparent short-term convenience buys a lot of long-term complexity, because you have to find out in each particular case what exactly is the signature of every variant of an operation. The mechanisms of dynamic binding as they exist in object technology and of course in Eiffel are much more effective than overloading to provide the kind of flexibility that people really want in the end.

So these are examples of cases in which being a little more careful in the language design can make a large contribution to the goal of taming complexity. It's also sometimes why people haven't believed our claims about Eiffel. The use of Eiffel is quite simple, but the examples that we publish are simple not necessarily because the underlying problems are simple, but because the solutions are. Eiffel is really a tool for removing artificial complexity and finding the essential simplicity that often lies below it. What we realize now is that sometimes people just don't believe it. They don't believe in simple solutions. They think we must be either hiding something or that the language and methods don't actually solve the real practical problems of software development, because they know there has to be more complexity there. As this horrible cliche goes, "if it looks too good to be true, then it must not be true," which is certainly the stupidest utterance ever proffered by humankind. This is the kind of cliche we hear from many people, and it's just wrong in the case of Eiffel. If you have the right tools for approaching problems, then you can get rid of unnecessary complexity and find the essential simplicity behind it.

This is the key issue that anyone building a significant system is facing day in and day out: how to organize complexity both by removing unnecessary, artificial, self-imposed complexity, and by organizing what remains of inevitable complexity. This is where the concepts of inheritance, contracts, genericity, object-oriented development in general, and Eiffel in particular, can play a role.

Bill Venners: It sounds to me that you're talking about two things: getting rid of unnecessary complexity and dealing with inherent complexity. I can see that tools, such as object-oriented techniques and languages, can help us deal with inherent complexity. But how can tools help us get rid of self-imposed complexity? What did you mean by "getting at the simplicity behind the complexity?"

Bertrand Meyer: Look at modern operating systems. People bash the complexity of Windows, for example, but I'm not sure the competition is that much better. There's no need for any bashing of any particular vendor, but it's clear that some of these systems are just too messy. A clean, fresh look at some of the issues would result in much better architecture. On the other hand, it's also true that an operating system—be it Windows XP, RedHat Linux, or Solaris—has to deal with Unicode, with providing a user interface in 100 different languages. Especially in the case of Windows, it has to deal with hundreds of thousands of different devices from lots of different manufacturers. This is not a kind of self-inflicted complexity that academics like to criticize. In the real world, we have to deal with requirements that are imposed on us from the outside. So there are two kinds of complexity: inherent complexity, which we have to find ways to deal with through organization, through information hiding, through modularization; and artificial complexity, which we should just get rid of by simplifying the problem.

Next Week

Come back Monday, November 3 for the fifth installment of a conversation with C# creator Anders Hejlsberg If you'd like to receive a brief weekly email announcing new articles at, please subscribe to the Artima Newsletter.


Bertrand Meyer is the author of Object-Oriented Software Construction, which is available on at:

Bertrand Meyer's Home Page at ETH, the Swiss Institute of Technology:

The Grand Challenge of Trusted Components, presented by Bertrand Meyer at the International Conference on Software Engineering, May 2003:

The Structure and Interpretation of Computer Programs, by Harold Abelson and Gerald Jay Sussman with Julie Sussman:

Find out more about Eiffel at:

The Eiffel language FAQ:

The 2001 Interview with Programming Expert Bertrand Meyer in InformIT:
(Gratuitously long URL omitted...)

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About the author

Bill Venners is president of Artima Software, Inc. and editor-in-chief of He is author of the book, Inside the Java Virtual Machine, a programmer-oriented survey of the Java platform's architecture and internals. His popular columns in JavaWorld magazine covered Java internals, object-oriented design, and Jini. Bill has been active in the Jini Community since its inception. He led the Jini Community's ServiceUI project that produced the ServiceUI API. The ServiceUI became the de facto standard way to associate user interfaces to Jini services, and was the first Jini community standard approved via the Jini Decision Process. Bill also serves as an elected member of the Jini Community's initial Technical Oversight Committee (TOC), and in this role helped to define the governance process for the community. He currently devotes most of his energy to building into an ever more useful resource for developers.