Kernighan and Plauger's _T_h_e _E_l_e_m_e_n_t_s _o_f _P_r_o_g_r_a_m_m_i_n_g
_S_t_y_l_e was an important and rightly influential book. But
sometimes I feel its concise rules were taken as a cookbook
approach to good style instead of the succinct expression of
a philosophy they were meant to be. If the book claims that
variable names should be chosen meaningfully, doesn't it
then follow that variables whose names are small essays on
their use are even better? Isn't MaximumValueUntilOverflow
a better name than maxval? I don't think so.
What follows is a set of short essays that collectively
encourage a philosophy of clarity in programming rather than
giving hard rules. I don't expect you to agree with all of
them, because they are opinion and opinions change with the
times. But they've been accumulating in my head, if not on
paper until now, for a long time, and are based on a lot of
experience, so I hope they help you understand how to plan
the details of a program. (I've yet to see a good essay on
how to plan the whole thing, but then that's partly what
this course is about.) If you find them idiosyncratic,
fine; if you disagree with them, fine; but if they make you
think about why you disagree, that's better. Under no cir-
cumstances should you program the way I say to because I say
to; program the way you think expresses best what you're
trying to accomplish in the program. And do so consistently
and ruthlessly.
Your comments are welcome.
_I_s_s_u_e_s _o_f _t_y_p_o_g_r_a_p_h_y
A program is a sort of publication. It's meant to be
read by the programmer, another programmer (perhaps yourself
a few days, weeks or years later), and lastly a machine.
The machine doesn't care how pretty the program is - if the
program compiles, the machine's happy - but people do, and
they should. Sometimes they care too much: pretty printers
mechanically produce pretty output that accentuates
irrelevant detail in the program, which is _a_s sensible _a_s
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putting all the prepositions _i_n English text _i_n bold font.
Although many people think programs should look like the
Algol-68 report (and some systems even require you to edit
programs in that style), a clear program is not made any
clearer by such presentation, and a bad program is only made
laughable.
Typographic conventions consistently held are important
to clear presentation, of course - indentation is probably
the best known and most useful example - but when the ink
obscures the intent, typography has taken over. So even if
you stick with plain old typewriter-like output, be cons-
cious of typographic silliness. Avoid decoration; for
instance, keep comments brief and banner-free. Say what you
want to say in the program, neatly and consistently. Then
move on.
_V_a_r_i_a_b_l_e _n_a_m_e_s
Ah, variable names. Length is not a virtue in a name;
clarity of expression _i_s. A global variable rarely used may
deserve a long name, maxphysaddr say. An array index used
on every line of a loop needn't be named any more ela-
borately than i. Saying index or elementnumber is more to
type (or calls upon your text editor) and obscures the
details of the computation. When the variable names are
huge, it's harder to see what's going on. This is partly a
typographic issue; consider
for(i=0 to 100)
array[i]=0
_v_s.
for(elementnumber=0 to 100)
array[elementnumber]=0;
The problem gets worse fast with real examples. Indices are
just notation, so treat them as such.
Pointers also require sensible notation. np is just as
mnemonic as nodepointer _i_f you consistently use a naming
convention from which np means ``node pointer'' is easily
derived. More on this in the next essay.
As in all other aspects of readable programming, con-
sistency is important in naming. If you call one variable
maxphysaddr, don't call its cousin lowestaddress.
Finally, I prefer minimum-length but maximum-
information names, and then let the context fill in the
rest. Globals, for instance, typically have little context
when they are used, so their names need to be relatively
evocative. Thus I say maxphysaddr (not
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MaximumPhysicalAddress) for a global variable, but np not
NodePointer for a pointer locally defined and used. This is
largely a matter of taste, but taste is relevant to clarity.
I eschew embedded capital letters in names; to my
prose-oriented eyes, they are too awkward to read comfort-
ably. They jangle like bad typography.
_T_h_e _u_s_e _o_f _p_o_i_n_t_e_r_s.
C is unusual in that it allows pointers to point to
anything. Pointers are sharp tools, and like any such tool,
used well they can be delightfully productive, but used
badly they can do great damage (I sunk a wood chisel into my
thumb a few days before writing this). Pointers have a bad
reputation in academia, because they are considered too
dangerous, dirty somehow. But I think they are powerful
_n_o_t_a_t_i_o_n, which means they can help us express ourselves
clearly.
Consider: When you have a pointer to an object, it is a
name for exactly that object and no other. That sounds
trivial, but look at the following two expressions:
np
node[i]
The first points to a node, the second evaluates to (say)
the same node. But the second form is an expression; it is
not so simple. To interpret it, we must know what node is,
what i is, and that i and node are related by the (probably
unspecified) rules of the surrounding program. Nothing
about the expression in isolation can show that i is a valid
index of node, let alone the index of the element we want.
If i and j and k are all indices into the node array, it's
very easy to slip up, and the compiler cannot help. It's
particularly easy to make mistakes when passing things to
subroutines: a pointer is a single thing; an array and an
index must be believed to belong together in the receiving
subroutine.
An expression that evaluates to an object is inherently
more subtle and error-prone than the address of that object.
Correct use of pointers can simplify code:
parent->link[i].type
_v_s.
lp->type.
If we want the next element's type, it's
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parent->link[++i].type
or
(++lp)->type.
i advances but the rest of the expression must stay con-
stant; with pointers, there's only one thing to advance.
Typographic considerations enter here, too. Stepping
through structures using pointers can be much easier to read
than with expressions: less ink is needed and less effort is
expended by the compiler and computer. A related issue is
that the type of the pointer affects how it can be used
correctly, which allows some helpful compile-time error
checking that array indices cannot share. Also, if the
objects are structures, their tag fields are reminders of
their type, so
np->left
is sufficiently evocative; if an array is being indexed the
array will have some well-chosen name and the expression
will end up longer:
node[i].left.
Again, the extra characters become more irritating as the
examples become larger.
As a rule, if you find code containing many similar,
complex expressions that evaluate to elements of a data
structure, judicious use of pointers can clear things up.
Consider what
would look like using a compound expression for p. Some-
times it's worth a temporary variable (here p) or a macro to
distill the calculation.
_P_r_o_c_e_d_u_r_e _n_a_m_e_s
Procedure names should reflect what they do; function
names should reflect what they _r_e_t_u_r_n. Functions are used
in expressions, often in things like if's, so they need to
read appropriately.
if(checksize(x))
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is unhelpful because we can't deduce whether checksize
returns true on error or non-error; instead
if(validsize(x))
makes the point clear and makes a future mistake in using
the routine less likely.
_C_o_m_m_e_n_t_s
A delicate matter, requiring taste and judgement. I
tend to err on the side of eliminating comments, for several
reasons. First, if the code is clear, and uses good type
names and variable names, it should explain itself. Second,
comments aren't checked by the compiler, so there is no
guarantee they're right, especially after the code is modi-
fied. A misleading comment can be very confusing. Third,
the issue of typography: comments clutter code.
But I do comment sometimes. Almost exclusively, I use
them as an introduction to what follows. Examples: explain-
ing the use of global variables and types (the one thing I
always comment in large programs); as an introduction to an
unusual or critical procedure; or to mark off sections of a
large computation.
There is a famously bad comment style:
i=i+1; /* Add one to i */
and there are worse ways to do it:
/**********************************
* *
* Add one to i *
* *
**********************************/
i=i+1;
Don't laugh now, wait until you see it in real life.
Avoid cute typography in comments, avoid big blocks of
comments except perhaps before vital sections like the
declaration of the central data structure (comments on data
are usually much more helpful than on algorithms); basi-
cally, avoid comments. If your code needs a comment to be
understood, it would be better to rewrite it so it's easier
to understand. Which brings us to
_C_o_m_p_l_e_x_i_t_y
Most programs are too complicated - that is, more com-
plex than they need to be to solve their problems
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efficiently. Why? Mostly it's because of bad design, but I
will skip that issue here because it's a big one. But pro-
grams are often complicated at the microscopic level, and
that is something I can address here.
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
_o_v_e_r_w_h_e_l_m_s 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.) For
example, binary trees are always faster than splay trees for
workaday problems.
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.
The following data structures are a complete list for
almost all practical programs:
array
linked list
hash table
binary tree
Of course, you must also be prepared to collect these into
compound data structures. For instance, a symbol table
might be implemented as a hash table containing linked lists
of arrays of characters.
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. (See Brooks p.
102.)
Rule 6. There is no Rule 6.
_P_r_o_g_r_a_m_m_i_n_g _w_i_t_h _d_a_t_a.
Algorithms, or details of algorithms, can often be
encoded compactly, efficiently and expressively as data
rather than, say, as lots of if statements. The reason is
that the _c_o_m_p_l_e_x_i_t_y of the job at hand, if it is due to a
combination of independent details, _c_a_n _b_e _e_n_c_o_d_e_d. A clas-
sic example of this is parsing tables, which encode the
February 21, 1989
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grammar of a programming language in a form interpretable by
a fixed, fairly simple piece of code. Finite state machines
are particularly amenable to this form of attack, but almost
any program that involves the `parsing' of some abstract
sort of input into a sequence of some independent `actions'
can be constructed profitably as a data-driven algorithm.
Perhaps the most intriguing aspect of this kind of
design is that the tables can sometimes be generated by
another program - a parser generator, in the classical case.
As a more earthy example, if an operating system is driven
by a set of tables that connect I/O requests to the
appropriate device drivers, the system may be `configured'
by a program that reads a description of the particular dev-
ices connected to the machine in question and prints the
corresponding tables.
One of the reasons data-driven programs are not common,
at least among beginners, is the tyranny of Pascal. Pascal,
like its creator, believes firmly in the separation of code
and data. It therefore (at least in its original form) has
no ability to create initialized data. This flies in the
face of the theories of Turing and von Neumann, which define
the basic principles of the stored-program computer. Code
and data _a_r_e the same, or at least they can be. How else
can you explain how a compiler works? (Functional languages
have a similar problem with I/O.)
_F_u_n_c_t_i_o_n _p_o_i_n_t_e_r_s
Another result of the tyranny of Pascal is that
beginners don't use function pointers. (You can't have
function-valued variables in Pascal.) Using function
pointers to encode complexity has some interesting proper-
ties.
Some of the complexity is passed to the routine pointed
to. The routine must obey some standard protocol - it's one
of a set of routines invoked identically - but beyond that,
what it does is its business alone. The complexity is _d_i_s_-
_t_r_i_b_u_t_e_d.
There is this idea of a protocol, in that all functions
used similarly must behave similarly. This makes for easy
documentation, testing, growth and even making the program
run distributed over a network - the protocol can be encoded
as remote procedure calls.
I argue that clear use of function pointers is the
heart of object-oriented programming. Given a set of opera-
tions you want to perform on data, and a set of data types
you want to respond to those operations, the easiest way to
put the program together is with a group of function
pointers for each type. This, in a nutshell, defines class
February 21, 1989
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and method. The O-O languages give you more of course -
prettier syntax, derived types and so on - but conceptually
they provide little extra.
Combining data-driven programs with function pointers
leads to an astonishingly expressive way of working, a way
that, in my experience, has often led to pleasant surprises.
Even without a special O-O language, you can get 90% of the
benefit for no extra work and be more in control of the
result. I cannot recommend an implementation style more
highly. All the programs I have organized this way have
survived comfortably after much development - far better
than with less disciplined approaches. Maybe that's it: the
discipline it forces pays off handsomely in the long run.
_I_n_c_l_u_d_e _f_i_l_e_s
Simple rule: include files should never include include
files. If instead they state (in comments or implicitly)
what files they need to have included first, the problem of
deciding which files to include is pushed to the user (pro-
grammer) but in a way that's easy to handle and that, by
construction, avoids multiple inclusions. Multiple inclu-
sions are a bane of systems programming. It's not rare to
have files included five or more times to compile a single C
source file. The Unix /usr/include/sys stuff is terrible
this way.
There's a little dance involving #ifdef's that can
prevent a file being read twice, but it's usually done wrong
in practice - the #ifdef's are in the file itself, not the
file that includes it. The result is often thousands of
needless lines of code passing through the lexical analyzer,
which is (in good compilers) the most expensive phase.
