Ajit K

Recently I have started reading the book: “The Art of Unix Programming” by Eric Raymod. This is a great reading and I like it a lot! It is enlightening! Here is an excerpt from the Philosophy of Unix:

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.

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:

1. Rule of Modularity: Write simple parts connected by clean interfaces.
2. Rule of Clarity: Clarity is better than cleverness.
3. Rule of Composition: Design programs to be connected to other programs.
4. Rule of Separation: Separate policy from mechanism; separate interfaces from engines.
5. Rule of Simplicity: Design for simplicity; add complexity only where you must.
6. Rule of Parsimony: Write a big program only when it is clear by demonstration that nothing else will do.
7. Rule of Transparency: Design for visibility to make inspection and debugging easier.
8. Rule of Robustness: Robustness is the child of transparency and simplicity.
9. Rule of Representation: Fold knowledge into data so program logic can be stupid and robust.
10. Rule of Least Surprise: In interface design, always do the least surprising thing.
11. Rule of Silence: When a program has nothing surprising to say, it should say nothing.
12. Rule of Repair: When you must fail, fail noisily and as soon as possible.
13. Rule of Economy: Programmer time is expensive; conserve it in preference to machine time.
14. Rule of Generation: Avoid hand-hacking; write programs to write programs when you can.
15. Rule of Optimization: Prototype before polishing. Get it working before you optimize it.
16. Rule of Diversity: Distrust all claims for “one true way”.
17. Rule of Extensibility: Design for the future, because it will be here sooner than you think.

Reading down the line, these had me on a roll . It is so true! I am sure most of the people involved in programming have experienced this. Note the comment about marketing fad ;):

Many pressures tend to make programs more complicated (and therefore more expensive and buggy). One such pressure is technical machismo. Programmers are bright people who are (often justly) proud of their ability to handle complexity and juggle abstractions. Often they compete with their peers to see who can build the most intricate and beautiful complexities. Just as often, their ability to design outstrips their ability to implement and debug, and the result is expensive failure.

Even more often (at least in the commercial software world) excessive complexity comes from project requirements that are based on the marketing fad of the month rather than the reality of what customers want or software can actually deliver. Many a good design has been smothered under marketing’s pile of “checklist features” — features that, often, no customer will ever use. And a vicious circle operates; the competition thinks it has to compete with chrome by adding more chrome. Pretty soon, massive bloat is the industry standard and everyone is using huge, buggy programs not even their developers can love.

This page is a real treasure-trove. Whenever you need a relook at your programming approach, do read this chapter about Philosophy of Unix. These principles can be applied to general software development as well (there’s nothing that says its unix only!). And it can be summarized by the “Kiss principle”:

I have become a fan of ESR.