Bugs in food and software

What is an acceptable probability of finding bug parts in a box of cereal? You can’t say zero. As the acceptable probability goes to zero, the price of a box of cereal goes to infinity. In practice, the FDA sets very small but non-zero limits on the probability of finding bug parts in food. This is unsettling at first, but there’s no rational way around it.

What is an acceptable probability of finding bugs in your software? Again, you can’t say zero. The cost increases without bound as the quality requirements increase. In my previous post, I wrote about the extraordinary quality procedures for writing software for space probes. And yet even these projects have to tolerate some non-zero probability of error. It’s not worthwhile to spend 10 billion dollars to prevent a bug in a billion dollar mission.

Bugs are a fact of life. We can insist that they are unacceptable or we can pretend they don’t exist, but neither approach is constructive. It’s better to focus on the probability of running into bugs and consequences of running into bugs.

Not all bugs have the same consequences. It’s distasteful to find a piece of a roach leg in your can of green beans, but it’s not the end of the world. Toxic microscopic bugs are more serious. Along the same lines, a software bug that causes incorrect hyphenation is hardly the same as a bug that causes a plane crash. To get an idea of the potential economic cost of  running into a bug, and therefore the resources worthwhile to detect and fix it, multiply the probability by the consequences.

How do you estimate the probabilities of software bugs? The same way you estimate the probability of bugs in food: by conducting experiments and analyzing data. Some people find this very hard to accept. They understand that testing is necessary in the physical world, but they think software is entirely different and must be proven correct in some mathematical sense. They object that computer programs are complex systems, too complex to test. Computer programs are complex, but human bodies are far more complex, and yet we conduct tests on human subjects all the time to estimate different probabilities, such as the probabilities of drug toxicity.

Another objection to software testing is that it can only test paths through the software that are actually taken, not all potential paths. That’s true, but the most important data when estimating the probability of running into a bug is data from people using the software under normal conditions. A bug that you never run into has no consequences.

But what about people using software in unanticipated ways? I certainly find it frustrating when I uncover bugs when I use a program in an atypical way. But this is not terribly different from physical systems. Bridges may fail when they’re subject to loads they weren’t designed for. There is a difference, however. Most software is designed to permit far more uses than can be tested, whereas there’s less of a gap in physical systems between what is permissible and what is testable. Unit testing helps. If every component of a software system works correctly in isolation, it more likely, though not certain, that the components will work correctly together in a new situation. Still, there’s no getting around the fact that the best tested uses are the most likely to succeed.

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