Basics of the Unix Philosophy
The ‘Unix philosophy’ originated with Ken
Thompson's
early meditations on how to design a small but capable operating
system with a clean service interface. It grew as the Unix culture
learned things about how to get maximum leverage out of Thompson's
design. It absorbed lessons from many sources along the way.
The Unix philosophy is not a formal design method. It wasn't
handed down from the high fastnesses of theoretical computer
science as a way to produce theoretically perfect software. Nor is
it that perennial executive's mirage, some way to magically extract
innovative but reliable software on too short a deadline from
unmotivated, badly managed, and underpaid programmers.
The Unix philosophy (like successful folk traditions in other
engineering disciplines) is bottom-up, not top-down. It is pragmatic
and grounded in experience. It is not to be found in official methods
and standards, but rather in the implicit half-reflexive knowledge, the
expertise
that the Unix culture transmits. It
encourages a sense of proportion and skepticism — and shows both
by having a sense of (often subversive) humor.
Doug McIlroy, the inventor of
Unix pipes and one of the
founders of the Unix tradition, had this to say at the time [McIlroy78]:
(i) Make each program do one thing well. To do a new job, build
afresh rather than complicate old programs by adding new
features.
(ii) Expect the output of every program to become the input to
another, as yet unknown, program. Don't clutter output with
extraneous information. Avoid stringently columnar or binary input
formats. Don't insist on interactive input.
(iii) Design and build software, even operating systems, to be
tried early, ideally within weeks. Don't hesitate to throw away the
clumsy parts and rebuild them.
(iv) Use tools in preference to unskilled help to lighten a
programming task, even if you have to detour to build the tools and
expect to throw some of them out after you've finished using
them.
He later summarized it this way (quoted in A Quarter
Century of Unix [Salus]):
This is the Unix philosophy: Write programs that do one
thing and do it well. Write programs to work together. Write
programs to handle text streams, because that is a universal
interface.
Rob Pike, who
became one of the great masters of C, offers a slightly different angle
in Notes on C Programming [Pike]:
Rule 1. You can't tell where a program is going to spend its
time. Bottlenecks occur in surprising places, so don't try to second
guess and put in a speed hack until you've proven that's where the
bottleneck
is.
Rule 2. Measure. Don't tune for speed until you've measured, and
even then don't unless one part of the code overwhelms the
rest.
Rule 3. Fancy algorithms are slow when n is small, and n is usually small. Fancy algorithms have big
constants. Until you know that n is
frequently going to be big, don't get fancy. (Even if n does get big, use Rule 2 first.)
Rule 4. Fancy algorithms are buggier than simple ones, and
they're much harder to implement. Use simple algorithms as well as
simple data structures.
Rule 5. Data dominates. If you've chosen the right data
structures and organized things well, the algorithms will almost
always be self-evident. Data structures, not algorithms, are central
to programming.[9]
Rule 6. There is no Rule 6.
Ken Thompson, the man who designed and implemented the
first Unix, reinforced Pike's rule 4 with a gnomic maxim worthy of a
Zen patriarch:
When in doubt, use brute force.
More of the Unix philosophy was implied not by what these elders
said but by what they did and the example Unix itself set. Looking
at the whole, we can abstract the following ideas:
-
Rule of Modularity: Write simple parts connected by clean interfaces.
-
Rule of Clarity: Clarity is better than cleverness.
-
Rule of Composition: Design programs to be connected to other programs.
-
Rule of Separation: Separate policy from mechanism;
separate interfaces from engines.
-
Rule of Simplicity: Design for simplicity; add
complexity only where you must.
-
Rule of Parsimony: Write a big program only when it is
clear by demonstration that nothing else will do.
-
Rule of Transparency: Design for visibility to make
inspection and debuggingeasier.
-
Rule of Robustness: Robustness is the child of transparency and simplicity.
-
Rule of Representation: Fold knowledge into data so program
logic can be stupid and robust.
-
Rule of Least Surprise: In interface design, always do
the least surprising thing.
-
Rule of Silence: When a program has nothing surprising
to say, it should say nothing.
-
Rule of Repair: When you must fail, fail noisily and
as soon as possible.
-
Rule of Economy: Programmer time is expensive; conserve it in
preference to machine time.
-
Rule of Generation: Avoid hand-hacking; write programs
to write programs when you can.
-
Rule of Optimization: Prototype before polishing. Get it
working before you optimize it.
-
Rule of Diversity: Distrust all claims for
“one true way”.
-
Rule of Extensibility: Design for the future, because
it will be here sooner than you think.
If you're new to Unix, these principles are worth some
meditation. Software-engineering texts recommend most of them; but
most other operating systems lack the right tools and traditions to
turn them into practice, so most programmers can't apply them with
any consistency. They come to accept blunt tools, bad designs,
overwork, and bloated code as normal — and then wonder what Unix
fans are so annoyed about.
Rule of Modularity: Write simple parts connected by clean interfaces.
As Brian Kernighan once observed, “Controlling complexity
is the essence of computer programming” [Kernighan-Plauger]. Debugging dominates
development time, and getting a working system out the door is
usually less a result of brilliant design than it is of managing not
to trip over your own feet too many times.
Assemblers, compilers, flowcharting, procedural programming,
structured programming, “artificial intelligence”,
fourth-generation languages, object
orientation, and software-development
methodologies without number have been touted and sold as a cure for
this problem. All have failed as cures, if only because they
‘succeeded’ by escalating the normal level of program
complexity to the point where (once again) human brains could barely
cope. As Fred Brooks famously observed [Brooks], there is no silver bullet.
The only way to write complex software that won't fall on its
face is to hold its global complexity down — to build it out of
simple parts connected by well-defined interfaces, so that most
problems are local and you can have some hope of upgrading
a part without breaking the whole.
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