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The myth of code-centricity

Break through productivity barriers with a new software model

By Jack Harich, JavaWorld.com, 08/24/01

Standing on the shores of the software development industry today, we see an ocean of endless code. The average developer spends most of his or her time coding or supporting code production. Developers earn respect based primarily on their coding abilities and obtain jobs based on the languages they know; a super developer is really a super coder.

The two major productivity advances of the 1990s were both code-centric: Java, a new language to produce even more code, and the Internet, which required an abundance of code to implement. The industry's problems are rooted in code management; they include code quality (bugs), code completion time (schedules), code capacity (how much you can produce), obsolete code (legacies), and, among many others, complexity in the ever-growing bodies of code. In short, the industry is so code-centric that it sees most problems and opportunities as best resolved with more handwritten code or more efficient code-production activities, such as requirements, design, and testing.

Before we delve into the problem, consider one insight: Brilliant tactics cannot save bad strategy.

The software industry has been searching for solutions to the code productivity problem for decades, as shown by attention to software engineering lore, code production process, coding tools, and coding languages. Just as Fred Brooks predicted in his 1986 essay "No Silver Bullet: Essence and Accident in Software Engineering" (see also the sidebar at the end of this article, "A Dissenting Opinion from Fred Brooks"), nothing has helped in the range of an order of magnitude:

But as we look to the horizon of a decade hence, we see no silver bullet. There is no single development, in either technology or management technique, which by itself promises even one order-of-magnitude improvement in productivity, in reliability, in simplicity.

Guess what? We're focusing on the wrong problem. The real problem is not productivity at the code/developer level, but at the system/user level.

Code-centricity is a dangerous myth because it stifles productivity and prevents fundamental progress in the science of computation. If we don't use drastically better alternatives, the software industry runs the risk of becoming a dinosaur relic, replaced by up-and-coming industries such as biotechnology and electromechanical nanotechnology, or by new ones not yet on anyone's radar. Congruence -- how closely two things match -- is at least one way out of the tar pit of code-centricity.

Another myth is that only radical innovation can achieve order-of-magnitude advances. Not so. Slow but steady improvement over a long period of time can have the same effect. In fact, most improvement is by evolution rather than revolution. This article presents nothing revolutionary or high risk. Instead, it proposes modest evolutionary progress by using bits and pieces of today's technology, focused tightly in the right direction.

Software generations

We'll explore the problem by learning from the past. Software development productivity trends are best understood if traced through successive generations, starting in the early 1950s. A new generation arose approximately once per decade. Table 1 classifies each generation by its proven productivity.

 

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