A Catalog of Principles

21 Aug 2021 | Three-minute read

I often find myself referring to these but sometimes forget the name. Now if I could only remember I have a list…

Ockham’s razor or Principle of Parsimony

Entities should not be multiplied beyond necessity

— William of Ockham

Often interpreted to mean “the simplest explanation is likely the right one”.

Conway’s Law

Any organization that designs a system (defined broadly) will produce a design whose structure is a copy of the organization’s communication structure.

— Melvin E. Conway

The Rumpelstiltskin Principle

As the 4,000 year old tale tells, once you have a name for something, you have power over it.

This feel highly related to the fundamental problems of computer science:

There are only two hard things in Computer Science: cache invalidation and naming things.

— Phil Karlton

The vocabulary we use can restrict our ideas when we have the wrong words and liberate them when we have the right words.

Dead Horse Theory

When you discover that you are riding a dead horse, the best strategy is to dismount

— Tribal Wisdom

Hyrum’s Law

With a sufficient number of users of an API, it does not matter what you promise in the contract: all observable behaviors of your system will be depended on by somebody.

Hyrum Wright

Principle of Least Surprise (Astonishment)

It proposes that a component of a system should behave in a way that most users will expect it to behave.

This is usually a good way to vet whether the model you have matches the model of the user or the model of the world - surprises are often indicative of a mismatch between these.

Murphy’s Law

If anything can go wrong, it will.

— Edward Murphy

I interpret this as planning for failure, even if you think it will never happen.

Law of Large Numbers

The average of the results obtained from a large number of trials should be close to the expected value and will tend to become closer to the expected value as more trials are performed.

One way to think of this is that if you only have a few samples, you should have no expectation of the samples being close to the expected value. With many, it is a good bet that they trend to the expected value.

Law of Medium Numbers

For medium number systems, we can expect that large fluctuations, irregularities, and discrepancy with any theory will occur more or less regularly.

— Gerald Weinberg in “An Introduction to General Systems Thinking”

In simple terms, small system are those that you can model analytically Large systems are those that you can model statistically. Medium systems neither lend themselves to “small analysis” nor “large analysis”. They are pervasive.

Single Responsibility Principle

A class should have only one reason to change

— Robert C. Martin

Often interpreted to mean that any entity (module, class, function) should have responsibility over exactly one idea.

Don’t Repeat Yourself Principle

Every piece of knowledge must have a single, unambiguous, authoritative representation within a system.

— Andy Hunt and Dave Thomas

Never, ever, copy, code.