IEEE Software, Vol. 15, No. 4, July/August 1998
Why You Should Use Routines, Routinely
As an undergraduate computer science student, I thought
that the main reason to create new routines instead of leaving all the code in one big
routine was to avoid duplicate code. That is one good reason to create a routine, but
hardly makes a complete list. The following sections describe many additional reasons to
The single most important reason to create a routine is
to reduce a program's complexity. Create a routine to hide information so that you won't
need to think about it. Sure, you need to think about it when you write the routine. But
after it's written, you should be able to forget the details and use the routine without
any knowledge of its internal workings. Other reasons to create routinesminimizing
code size, improving maintainability, and improving correctnessare good reasons, but
without the abstractive power of routines, complex programs would be intellectually
impossible to manage.
Avoiding duplicate code
Undoubtedly the most popular reason for creating a routine is to avoid
duplicate code. Similar code in two routines is a warning sign. David Parnas says that if
you use copy and paste while youre coding, youre probably committing a design
error. Instead of copying code, move it into its own routine. Future modifications will be
easier because you will need to modify the code in only one location. The code will be
more reliable because you will have only one place in which to be sure that the code is
Limiting effects of changes
Isolate areas that are likely to change so that effects
of changes are limited to a single routine or, at most, a few routines. Create your
designs so that the areas that are most likely to change are the easiest to change. Areas
likely to change include hardware dependencies, input/output formats, complex data
structures, and business rules.
Hide the order in which events happen to be processed.
If the program typically gets data from the user then gets auxiliary data from a file,
neither the routine that gets the user data nor the routine that gets the file data should
depend on the other routines being performed first. Design the system so that either
could be performed first, then create a routine to hide the information about which
happens to be performed first.
Having code in one place, inside a single routine, means
that a single optimization benefits all the code that calls that routine. It makes it
practical to recode the routine with a more efficient algorithm or a faster, more
difficult language, like assembler.
Hiding data structures
Hide data-structure implementation details so that most
of the program doesn't need to worry about the messy details of manipulating
computer-science data structures, but can deal with the data in terms of how it's used in
the problem domain. Routines that hide implementation details provide a valuable level of
abstraction that reduce a program's complexity. They centralize data structure operations
in one place and reduce the chance of errors in working with that data structure. They
make it possible to change the data structure without changing most of the program.
When hiding a data structure, refer to it independently of the media
its stored on. If you have an insurance rates table that's so big that it's always stored
on disk, you might be tempted to refer to it as a "rate file." When you
refer to it as a file, however, you're exposing more information about the data than you
need to. If you ever change the program so that the table is in memory instead of on disk,
the code that refers to it as a file will be incorrect, misleading, and confusing. Try,
instead, to make names of access routines independent of how the data is stored, and refer
to the abstract data type, insurance rates table, instead.
Hiding global data
If you need to use global data, at least hide its
implementation details. Working with global data through access routines provides several
benefits. You can change the structure of the data without changing your program, and you
can monitor accesses to the data. The discipline of using access routines also encourages
you to think clearly about whether the data is really global; it might be more accurate to
treat it as local to a class, module, or routine.
Promoting code reuse
Code put into modular routines can be reused in other
programs more easily than the same code spread across a large routine.
Planning for a family of programs
If you expect a program to be modified, isolate the
parts you expect to change within their own routines. You can then modify the routines
without affecting the rest of the program, or you can put the changes into completely new
routines instead. For example, several years ago I managed a team that created a family of
programs used by our clients to sell insurance. We had to tailor each program to each
specific client's insurance rates, report format, underwriting rules, and so on. But many
parts of the programs were similar: data-input routines that took in information about our
clients customers, routines that stored and retrieved information in a customer
database, routines that computed total rates for a group, and so on. The team modularized
the program so that each part that varied from client to client was put into its own
module. The initial programming for the whole system took several months, but, after that
was done, whenever we got a new client we merely wrote a handful of new modules and
dropped them into the rest of the code. A few days work, and voila! Custom software!
Putting a section of code into a well-named routine is
one of the best ways to document its function. Instead of reading a series of statements
if ( Node <> NULL ) then
while ( Node.Next <> NULL ) do
Node = Node.Next
LeafName = Node.Name
LeafName = ''
You can read a statement like
LeafName = GetLeafName( Node )
The new routine is so short that all it needs for
documentation is a good name. Using a function call instead of eight lines of code makes
the routine that originally contained the code less complex and automatically documents
You can use the same technique to document complicated boolean tests.
Move the code that performs the test into its own function, out of the main flow of the
code; choose an understandable function name; and the result will be that both the main
flow of the code and the boolean test will be clearer than when the test is in the main
flow of the code.
Isolate use of nonportable operations to explicitly
identify and isolate future portability work. Nonportable operations include use
nonstandard language features, hardware dependencies, operating system dependencies, and
Isolating use of nonstandard language functions
Most languages contain handy, nonstandard extensions.
Using them is a double-edged sword: theyre useful, but they might not be available
when you move to different hardware, a new vendor's implementation of the same language,
or even a new version of the language from your current vendor. If you use nonstandard
extensions, build routines of your own that act as gateways to those extensions. Then, you
can replace the vendor's nonstandard routines with custom written routines of your own if
Isolating complex operations
Complex operations include complicated algorithms,
communications protocols, tricky boolean tests, and operations on complex dataall of
which are prone to errors. When an error is detected, having the code to which it applies
contained within a single routine makes the error easier to diagnose and fix than if parts
of the complex operation were spread throughout the program.
The Greatest Invention in Computer Science
Aside from the invention of the computer, the routine is arguably the single greatest
invention in computer science. It makes programs easier to read and understand. It makes
them smaller (imagine how much larger your code would be if you had to repeat the code for
every call to a routine instead of invoking the routine). And it makes them faster
(imagine how hard it would be to make performance improvements in similar code used in a
dozen places rather than making all the performance improvements in one routine). In large
part, routines are what make modern programming possible.
Editor: Steve McConnell, Construx Software, 11820 Northup
#E200, Bellevue, WA 98005.
E-mail: firstname.lastname@example.org - WWW: http://www.construx.com/stevemcc/