complexity as entropy • Buttondown

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In the previous post, I characterized Ron Jeffries' meandering approach to software design as "a shrug in the face of entropy." Some readers seem to have taken this as a strange, flowery metaphor. It wasn't. In this newsletter, our analytic framework is borrowed from information theory: simplicity is a fitness between content and expectation. When we say software is complex, we mean it's difficult to explain; we need to bridge the distance between our audience's expectations and the realities of our software. This distance — the subjective complexity of our software — can be measured in bits. In some literature, this metric is called surprisal. This is a good name; it reminds us that the complexity of our code varies with its audience. But there is a more common term for the number of bits in a message, borrowed from thermodynamics: entropy. To understand the relationship between information and disorder in a physical system, consider why a sequence of random numbers cannot be compress

March 12, 2025 complexity as entropy In a random dataset, there are no internal relationships; with each element, our explanation must begin anew. In the previous post , I characterized Ron Jeffries' meandering approach to software design as "a shrug in the face of entropy." Some readers seem to have taken this as a strange, flowery metaphor. It wasn't. In this newsletter, our analytic framework is borrowed from information theory: simplicity is a fitness between content and expectation. When we say software is complex, we mean it's difficult to explain; we need to bridge the distance between

complexity as entropy • Buttondown

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