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Striving for Simplicity, Arriving at Complexity

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Striving for Simplicity, Arriving at Complexity

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This post is a riff on a line from Mathematics without Apologies, the book I quoted yesterday.

In an all too familiar trade-off, the result of striving for ultimate simplicity is intolerable complexity; to eliminate too-long proofs we find ourselves “hopelessly lost” among the too-long definitions. [emphasis added]

It’s as if there’s some sort of conservation of complexity, but not quite in the sense of a physical conservation law. Conservation of momentum, for example, means that if one part of a system loses 5 units of momentum, other parts of the system have to absorb exactly 5 units of momentum. But perceived complexity is psychological, not physical, and the accounting is not the same. By moving complexity around we might increase or decrease the overall complexity.

The opening quote suggests that complexity is an optimization problem, not an accounting problem. It also suggests that driving the complexity of one part of a system to its minimum may disproportionately increase the complexity of another part. Striving for the simplest possible proofs, for example, could make the definitions much harder to digest. There’s a similar dynamic in programming languages and programs.

Larry Wall said that Scheme is a beautiful programming language, but every Scheme program is ugly. Perl, on the other hand, is ugly, but it lets you write beautiful programs. Scheme can be simple because it requires libraries and applications to implement functionality that is part of more complex languages. I had similar thoughts about COM. It was an elegant object system that lead to hideous programs.

Scheme is a minimalist programming language, and COM is a minimalist object framework. By and large the software development community prefers complex languages and frameworks in hopes of writing smaller programs. Additional complexity in languages and frameworks isn’t felt as strongly as additional complexity in application code. (Until something breaks. Then you might have to explore parts of the language or framework that you had blissfully ignored before.)

The opening quote deals specifically with the complexity of theorems and proofs. In context, the author was saying that the price of Grothendieck’s elegant proofs was a daunting edifice of definitions. (More on that here.) Grothendieck may have taken this to extremes, but many mathematicians agree with the general approach of pushing complexity out of theorems and into definitions. Michael Spivak defends this approach in the preface to his book Calculus on Manifolds.

… the proof of [Stokes’] theorem is, in the mathematician’s sense, an utter triviality — a straight-forward calculation. On the other hand, even the statement of this triviality cannot be understood without a horde of definitions … There are good reasons why the theorems should all be easy and the definitions hard. As the evolution of Stokes’ theorem revealed, a single simple principle can masquerade as several difficult results; the proofs of many theorems involve merely stripping away the disguise. The definitions, on the other hand, serve a twofold purpose: they are rigorous replacements for vague notions, and machinery for elegant proofs. [emphasis added]

Mathematicians like to push complexity into definitions like software developers like to push complexity into languages and frameworks. Both strategies can make life easier on professionals while making it harder on beginners.

Related post: A little simplicity goes a long way

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Published at DZone with permission of John Cook, DZone MVB. See the original article here.

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