Unix Philosophy

12 Apr 2015. comments

I believe the Unix Philosophy is one of the most overused yet least understood set of concepts in software development. But its also just interesting to think about and revisit it periodically.

1. Rule of Modularity: Write simple parts connected by clean interfaces.

This is really all about abstraction and separation of concerns. A part of a system is easier to understand on its own more-so than the entire system. And those parts are easiest to understand and maintain if they have tight cohesion around a single concept. It’s also natural and beneficial for a system appropriately broken down into small parts to have small interfaces. The abstraction should expose as few details as possible so that the consumer can focus instead on the broader system instead of the details for one of its parts.

2. Rule of Clarity: Clarity is better than cleverness.

I would argue this is the most important yet least practiced of all the rules on this page. Too often developers write code that is fancy rather than communicative. This is insidious as well because the pain of writing fancy code is not immediately felt since maintenance comes later. When the system needs to be extended, repaired, or otherwise modified it needs to be completely clear what it does otherwise it becomes a time/money sink. Your most important job as a software developer is to write code that other developers can maintain with ease. Write code for humans, not compilers.

3. Rule of Composition: Design programs to be connected to other programs.

The general idea is that if software can be re-used then it can be re-connected to other software and therefor provide long term dividends beyond the original project. We have to be careful with this one though because it can quickly lead to premature optimization or gold plating.

4. Rule of Separation: Separate policy from mechanism; separate interfaces from engines.

How a thing is accomplished is something that should be interchangeable. A basic example of this is the strategy pattern where logic can be pluggable. Another example is that the same system might be interactable via a web application, web API, command line interface, etc. This again touches on separation of concerns since you must have modularity before being able to vary a systems parts.

5. Rule of Simplicity: Design for simplicity; add complexity only where you must.

Get it working. Don’t gold plate. Don’t prematurely optimize. Only make performance optimizations when you have proven that a performance problem exists and system needs to be more performant. Don’t generalize until your specific problem has been solved and a more general approach would be useful for multiple parts of the system or other systems. Prove that complexity would be advantageous before sacrificing simplicity. Remember Rule #2 and write code for humans first, compilers second.

6. Rule of Parsimony: Write a big program only when it is clear by demonstration that nothing else will do.

Really this is just Rule #5 (and #2) restated. Do the simplest thing that could possibly work. Have measurements that indicate adding code would be beneficial. Remember that every line of code added is a line that must be maintained and calculate that negative against the theoretical positives of adding more code.

7. Rule of Transparency: Design for visibility to make inspection and debugging easier.

This is Rule #2. Make it so that when things go wrong it requires very little inspection to know what happened. Keep inheritance heirarchies shallow so that behaviors can be tracked down easily. Break up large things into smaller things.

8. Rule of Robustness: Robustness is the child of transparency and simplicity.

When things can be easily understood and composed into larger things the result is a system that can do more things without sacrificing those things that made it composable in the first place. Legos can be made into greater things in part because each piece can be easily composed into large pieces.

9. Rule of Representation: Fold knowledge into data so program logic can be stupid and robust.

Let’s face it, programming is hard. When given a choice of making data complex vs logic complex we should always choose the data because code must be maintained and understood by future developers.

10. Rule of Least Surprise: In interface design, always do the least surprising thing.

This is sort of like defensive driving for computer programming. Make it obvious what you code does by thinking carefully about your APIs. Ideally consumers of your code should be utterly bored with how expected everything is. Your code should fade into the background and allow consumers to instead focus on their own problems they are trying to solve.

11. Rule of Silence: When a program has nothing surprising to say, it should say nothing.

Are status messages or other outputs necessary for a user? Is the information you are giving to a user useful or actionable? If it isn’t then it’s just noise to them and you shouldn’t concern them with it.

12. Rule of Repair: When you must fail, fail noisily and as soon as possible.

Nothing is worse than a system that goes wrong but brushes the problem under the rug for a while. Doing this makes it very difficult to know where the problem is since the root cause may be several levels removed from where the problem happened. Failing noisily makes us aware of the problem. Failing as soon as possibly makes localizing the failure easy.

13. Rule of Economy: Programmer time is expensive; conserve it in preference to machine time.

This is rule #2 and #5 again. Your fancy code might make a system slightly more performant or flexible but at what cost? If it costs future developers too much time to understand it then you have a net negative. Developers always tend to underestimate the maintenance costs of the software they write, or how many future developers will run into their code.

14. Rule of Generation: Avoid hand-hacking; write programs to write programs when you can.

Be lazy. The first time you have to do something by hand might not be too bad but if you have to do it again you should automate it. Twice is evidence that the likelihood of you or someone else having to perform this manual work again is high.

15. Rule of Optimization: Prototype before polishing. Get it working before you optimize it.

If you spend time making your software whiz-bang awesome, performant, or generalized before you understand a problem and get it working at a basic level then you’re really just wasting time. Doing these things early is dangerous because the shape of the problem or your understanding may change greatly as you explore the problem space and therefor all that extra code you’ve written just adds time and complexity as you evolve the system.

16. Rule of Diversity: Distrust all claims for “one true way”.

In software change is inevitable and nothing is one-size-fits-all. What solves your problem might not solve mine, and even if it does it may only be appropriate right now. In an industry as young as software we are still trying to figure things out (languages, patterns, practices). Saying you know the best way or tool is shutting off your search for even better ways/tools. This isn’t even really software specific and has wider applicability to life or science of any kind.

17. Rule of Extensibility: Design for the future, because it will be here sooner than you think.

Don’t misunderstand this one; it isn’t about premature optimization or overgeneralizing. It’s about leaving doors open and not painting yourself into a corner. You don’t need to go all the way towards making something generalized or reusable; you just need to make it easy to do that down the road.


Tagged: unix software engineering software craftsmanship patterns

2017 Ben Lakey

The words here do not reflect those of my employer.