draft under submission; copyright reserved by author

In Praise of Scripting:  Real Programming Pragmatism

Ronald P. Loui
Associate Professor of CSE
Washington University in St. Louis

ABSTRACT:  This article's main purpose is to review the changes in
	programming practices known collectively as the "rise of
	scripting," as predicted in 1998 IEEE COMPUTER by Ousterhout.
	This attempts to be both brief and definitive, drawing on many of
	the essays that have appeared in online forums.  The main new idea
	is that programming language theory needs to move beyond semantics
	and take language pragmatics more seriously.

KEYWORDS: scripting, programming languages, programming practices,
	computing curricula

TO THE EDITORS:  Please read at least the first four lines to see
	why this article belongs in IEEE COMPUTER.  See the Business Week
	article linked at the end for additional motivation on the topic
	and its timing (we've actually been thinking about this article
	for over a year -- this is draft #7).

To the credit of this journal, it had the courage to publish the signal
paper on scripting, John Ousterhout's "Scripting: Higher Level Programming
for the 21st Century" in 1998.  Today, that document rolls forward with an
ever-growing list of positive citations.  More importantly, every major
observation in that paper seems now to be entrenched in software practice
today; every benefit claimed for scripting appears to be genuine
(flexibility of typelessness, rapid turnaround of interpretation, higher
level semantics, development speed, appropriateness for gluing components
and internet programming, ease of learning and increase in amount of
casual programming).

Interestingly, IEEE COMPUTER also just printed one of the most canonical
attacks on scripting, by one Diomidis
Spinellis, 2005, "Java Makes Scripting Languages Irrelevant?"  Part of
what makes this attack interesting is that the author seems unconvinced of
his own title; the paper concludes with more text devoted to praising
scripting languages than it expends in its declaration of Java's progress
toward improved usability.  It is unclear what is a better recommendation
for scripting:  the durability of Ousterhout's text or the indecisiveness
of this recent critic's.

The real shock is that the academic programming language community
continues to reject the sea change in programming practices brought
about by scripting.  Enamored of the object-oriented paradigm,
especially in the undergraduate curriculum, unwilling to accept the
LAMP (Linux-Apache-MySQL-Perl/Python/Php) tool set, and firmly believing
that more programming theory leads to better programming practice, the
academics seem blind to the facts on the ground.  The ACM flagship,
COMMUNICATIONS OF THE ACM for example, has never published a paper
recognizing the scripting philosophy, and the references throughout the
ACM Digital Library to scripting are not encouraging.

Part of the problem is that scripting has risen in the shadow of
object-oriented programming and highly publicized corporate battles
between Sun, Netscape, and Microsoft with their competing software
practices.  Scripting has been appearing language by language,
including object-oriented scripting languages now.  Another part of the
problem is that scripting is only now mature enough to stand up against
its legitimate detractors.  Today, there are answers to many of the
persistent questions about scripting:  is there a scripting language
appropriate for the teaching of CS1 (the first programming course for
majors in the undergraduate computing curriculum)?  Is there a scripting
language for enterprise or real-time applications?  Is there a way for
scripting practices to scale to larger software engineering projects?

I intend to review the recent history briefly for those who have not yet
joined the debate, then present some of the answers that scripting
advocates now give to those nagging questions.  Finally, I will describe
how a real pragmatism of academic interest in programming languages would
have better prepared the academic computing community to see the changes
that have been afoot.

1996-1998 are perhaps the most interesting years in the phylogeny of
scripting.  In those years, perl "held the web together", and together
with a new POSIX awk and GNU gawk, was shipping with every new Linux.
Meanwhile javascript was being deployed furiously (javascript bearing no
important relation to java, having been renamed from "livescript" for
purely corporate purposes, apparently a sign of Netscape's solidarity with
Sun, and even renamed "jscript" under Microsoft).  Also, a handoff from
tcl/tk to python was taking place as the language of choice for GUI
developers who would not yield to Microsoft's VisualBasic.  Php appeared
in those years, though it would take another round of development before
it would start displacing server-side perl, cold fusion, and asp.  Every
one of these languages is now considered a classic, even prototypical,
scripting language.

Already by mid-decade, the shift from scheme to java as the dominant CS1
language was complete, and the superiority of c++ over c was unquestioned
in industry.  But java applets were not well supported in browsers, so the
appeal of "write once, run everywhere" quickly became derided as "write
once, debug everywhere."  Web page forms, which used the common gateway
interface (cgi) were proliferating, and systems programming languages like
c became recognized as overkill for server-side programming.  Developers
quickly discovered the main advantage of perl for cgi forms processing,
especially in the dot-com setting:  it minimized the programmer's
write-time.  What about performance?  The algorithms were simple, network
latency masked small delays, and database performance was built into the
database software.  It turned out that the bottleneck was the
programming.  Even at run-time, the network and disk properties were the
problems, not the cpu processing.  What about maintenance?  The developers
and management were both happy to rewrite code for redesigned services
rather than deal with legacy code.  Scripting, it turns out, was so
powerful and programmer-friendly that it was easier to create new scripts
from scratch than to modify old programs.  What about user interface?
After all, by 1990, most of the programming effort had become the writing
of the GUI, and the object-oriented paradigm had much of its momentum in
the inheritance of interface widget behaviors.  Surprisingly, the
interface that most programmers needed could be had in a browser.  The
html/javascript/cgi trio became the GUI, and if more was needed, then
ambitious client-side javascript was more reliable than the browser's java
virtual machine.  Moreover, the server-side program was simply a better
way to distribute automation in a heterogeneous internet than the
downloadable client-side program, regardless of whether the download was
in binary or bytecode.

Although there was not agreement on what exact necessary and sufficient
properties characterized scripting and distinguished it from "more
serious" programming, several things were clear:

	scripting permitted rapid development, often regarded as merely
	"rapid prototyping," but subsequently recognized as a kind of agile

	scripting was the kind of high-level programming that had always
	been envisioned, in the ascent from low-level assembly language
	programming to higher levels of abstraction:  it was concise,
	and it removed programmers from concerning themselves with
	many performance and memory management details; 

	scripting was well suited to the majority of a programming task,
	usually the accumulation, extraction, and transformation of data,
	followed eventually by its presentation, so that only the
	performance-critical portion of a project had to be written in a
	more cumbersome, high-performance language;

	it was easier to get things right when source code was short, when
	behavior was determined by code that fit on a page, all types were
	easily coerced into strings for trace-printing, code fragments
	could be interpreted, identifiers were short, and when the
	programmer could turn ideas into code quickly without losing

This last point was extremely counterintuitive.  Strong typing, naming
regimen, and verbosity were motivated mainly by a desire to help the
programmer avoid errors.  But the programmer who had to generate too many
keystrokes and consult too many pages, who had to search through many
different files to discover semantics, and who had to follow too many
rules, who had to sustain motivation and concentration over a long period
of time, was a distracted and consequently inefficient programmer.  Just
as vast libraries did not deliver the promise of greater reusability, and
virtual machines did not deliver the promise of platform-independence, the
language's promise to discipline the programmer quite simply did not
reduce the tendency of humans to err.  It exchanged one kind of frequent
error for another.

Scripting languages became the favorite tools of the independent-minded
programmers:  the "hackers" yes, but also the gifted and genius
programmers who tended to drive a project's design and development.  As
Paul Graham noted (in a column reprinted in "Hackers and Painters" or this), one
of the lasting and legitimate benefits of java is that it permits managers
to level the playing field and extract considerable productivity from the
less talented and less motivated programmers (hence, more disposable).
There was a corollary to this difference between the mundane and the

	scripting was not enervating but was actually renewing:
	programmers who viewed code generation as tedious and tiresome in
	contrast viewed scripting as rewarding self-expression or

The distinct features of scripting languages that produce these effects
are usually enumerated as semantic features, starting with low I/O
specification costs, the use of implicit coercion and weak typing,
automatic variable initialization with optional declaration, predominant
use of associative arrays for storage and regular expressions for pattern
matching, reduced syntax, and powerful control structures.  But the main
reason for the productivity gains may be found in the name "scripting"
itself.  To script an environment is to be powerfully embedded in that
environment.  In the same way that the dolphin reigns over the open ocean,
lisp is a powerful language for those who would customize their emacs,
javascript is feral among browsers, and gawk and perl rule the linux

There is even a hint of AI in the idea of scripting:  the scripting
language is the way to get high level control, to automate by capturing
the intentions and routines normally provided by the human.  If recording
and replaying macros is a kind of autopilot, then scripting is a kind of
proxy for human decisionmaking.  Nowhere is this clearer than in simple
server-side php, or in sysadmin shell scripting.

So where do we stand now?  While it may have been risky for Ousterhout to
proclaim scripting on the rise in 1998, it would be folly to dismiss the
success of scripting today.  It is even possible that java will yield its
position of dominance in the near future.  (By the time this essay is
printed, LAMP and AJAX might be the new darlings of the tech press;
see recent articles in Business Week, this IEEE COMPUTER, and even James
Gosling's blog where he concedes he was wanting to write a scripting
language when he was handed the java project.  Java is very much in full
retreat.)  Is scripting ready to fill the huge vacuum that would be

I personally believe that CS1 java is the greatest single mistake in the
history of computing curricula.  I believe this because of the empirical
evidence, not because I have an a priori preference (I too voted to shift
from scheme to java in our CS1, over a decade ago, so I am complicit in
the java debacle).  I reported in SIGPLAN 1996 ("Why gawk for AI?") that
only the scripting programmers could generate code fast enough to keep up
with the demands of the artificial intelligence laboratory class.  Even
though students were allowed to choose any language they wanted, and many
had to unlearn the java ways of doing things in order to benefit from
scripting, there were few who could develop ideas into code effectively
and rapidly without scripting.  In the intervening decade, little has
changed.  We actually see more scripting, as students are happy to
compress images so that they can script their computer vision projects
rather than stumble around in c and c++.  In fact, students who learn to
script early are empowered throughout their college years, especially in
the crucial UNIX and web environments.  Those who learn only java are
stifled by enterprise-sized correctness and the chimerae of just-in-time
compilation, swing, JRE, JINI, etc.  Young programmers need to practice
and produce, and to learn through mistakes why discipline is needed.  They
need to learn design patterns by solving problems, not by reading
interfaces to someone else's black box code.  It is imperative that
programmers learn to be creative and inventive, and they need programming
tools that support code exploration rather than code production.

What scripting language could be used for CS1?  My personal preferences
are gawk, javascript, php, and asp, mainly because of their very gentle
learning curves.  I don't think perl would be a disaster; its imperfection
would create many teaching moments.  But there is emerging consensus in
the scripting community that python is the right choice for freshman
programming.  Ruby would also be a defensible choice.  Python and ruby
have the enviable properties that almost no one dislikes them, and almost
everyone respects them.  Both languages support a wide variety of
programming styles and paradigms and satisfy practitioners and
theoreticians equally.  Both languages are carefully enough designed that
"correct" programming practices can be demonstrated and high standards of
code quality can be enforced.  The fact that Google stands by python is an
added motivation for undergraduate majors.

But do scripting solutions scale?  What about the performance gap when the
polynomial, or worse the exponential, algorithm faces large n, and the
algorithm is written in an interpreted or weakly compiled language?  What
about software engineering in the large, on big projects?  There has been
a lot of discussion about scalability of scripts recently.  In the past,
debates have simply ended with the concession that large systems would
have to be rewritten in c++, or a similar language, once the scripting had
served its prototyping duty.

The enterprise question is the easier of the two.  Just as the individual
programmer reaps benefits from a division of labor among tools, writing
most of the code in scripts, and writing all bottleneck code in a highly
optimizable language, the group of programmers benefits from the use of
multiple paradigms and multiple languages.  In a recent large project, we
used vhdl for fpga's with a lot of gawk to configure the vhdl.  We
used python and php to generate dynamic html with svg and javascript for
the interfaces.  We used c and c++ for high performance communications
wrappers, which communicated xml to higher level scripts that managed
databases and processes.  We saw sysadmin and report-generation in perl,
ruby, and gawk, data scrubbing in perl and gawk, user scripting in bash,
tcl, and gawk, and prototyping in perl and gawk.  Only one module was
written in java (because that programmer loved java):  it was late, it was
slow, it failed, and it was eventually rewritten in c++.  In retrospect,
neither the high performance components nor the lightweight code
components were appropriate for the java language.  Does scripting scale
to enterprise software?  I would not manage a project that did not include
a lot of scripting, to minimize the amount of "hard" programming, to
increase flexibility and reduce delivery time at all stages, to take
testing to a higher level, and to free development resources for
components where performance is actually critical.  I nearly weep when I
think about the text processing that was written in c under my managerial
watch, because the programmer did not know perl.  We write five hundred
line scripts in gawk that would be ten thousand line modules in java or
c++.  In view of the fact that there are much better scripting tools for
most of what gets programmed in java and c++, perhaps the question is
whether java and c++ scale.

How about algorithmic complexity?  Don't scripting languages take too long
to perform nested loops?  The answer here is that a cpu-bound tight loop
such as a matrix multiplication is indeed faster in a language like c.
But such bottlenecks are easy to identify and indeed easy to rewrite in
c.  True system bottlenecks are things like paging, chasing pointers on
disk, process initialization, garbage collection, fragmentation, cache
mismanagement, and poor data organization.  Often, we see that better data
organization was unimplemented because it would have required more code,
code that would have been attempted in an "easier" programming language
like a scripting language, but which was too difficult to attempt in a
"harder" programming language.  We saw this in the AI class with heuristic
search and computer vision, where brute force is better in c, but complex
heuristics are better than brute force, and scripting is better for
complex heuristics.  When algorithms are exponential, it usually doesn't
matter what language you use because most practical n will incur too great
a cost.  Again, the solution is to write heuristics, and scripting is the
top dog in that house.  Cpu's are so much faster than disks these days
that a single extra disk read can erase the CPU advantage of using
compiled c instead of interpreted gawk.  In any case, java is hardly the
first choice for those who have algorithmic bottlenecks.

The real reason why academics were blindsided by scripting is their lack
of practicality.  Academic computing was generally late to adopt Wintel
architectures, late to embrace cgi programming, and late to accept Linux
in the same decade that brought scripting's rise.  Academia understandably
holds industry at a distance.  Still, there is a purely intellectual
reason why programming language courses are only now warming to
scripting.  The historical concerns of programming language theory have
been syntax and semantics.  Java's amazing contribution to computer
science is that it raised so many old-fashioned questions that tickled the
talents of existing programming language experts:  e.g., how can it be
compiled?  But there are new questions that can be asked, too, such as
what a particular language is well-suited to achieve inexpensively,
quickly, or elegantly, especially with the new mix of platforms.  The
proliferation of scripting languages represents a new age of innovation in
programming practice.  

Linguists recognize something above syntax and semantics, and they call it
"pragmatics".  Pragmatics has to do with more abstract social and
cognitive functions of language:  situations, speakers and hearers,
discourse, plans and actions, and performance.  We are entering an era of
comparative programming language study when the issues are higher-level,
social, and cognitive too.

My old friend, Michael Scott, has a popular textbook called PROGRAMMING
LANGUAGE PRAGMATICS.  But it is a fairly traditional tome concerned with
parameter passing, types, and bindings (it's hard to see why it merits
"pragmatics" in its title, even as it goes to second edition with a
chapter on scripting added!).  A real programming pragmatics would ask
questions like:

	how well does each language mate to the other UNIX tools?

	what is the propensity in each language for programmers
	at various expertise levels to produce a memory leak?

	what is the likelihood in each language that unmodified
	code will still function in five years?

	what is the demand of a programmer's concentration, what is the
	load on her short-term memory of ontology, and what is the support
	for visual metaphor in each language?

There have been programming language "shootouts" and "scriptometers" on
the internet that have sought to address some of the questions that are
relevant to the choice of scripting language, but they have been just
first steps.  For example, one site reports on the shortest script in each
scripting language that can perform a simple task.  But absolute brevity
for trivial tasks, such as "print hello world" is not as illuminating as
typical brevity for real tasks, such as xml parsing.

Pragmatic questions are not the easiest questions for
mathematically-inclined computer scientists to address.  They refer by
their nature to people, their habits, their sociology, and the
technological demands of the day.  But it is the importance of such
questions that makes programmers choose scripting languages.  Ousterhout
declared scripting on the rise, but perhaps so too are programming
language pragmatics.


I have to thank Charlie Comstock for contributing many ideas and
references over the past two years that have shaped my views,
especially the commitment to the idea of pragmatics.

Prof. Dr. Loui and his students are the usual winners of the department
programming contest and have contributed to current gnu releases of gawk
and malloc.  He has lectured on AI for two decades on five continents,
taught AI programming for two decades, and is currently funded on a
project delivering hardware and software on U.S. government contracts.


Graham, P., Hackers and Painters, O'Reilly, 2004.
Levinson, S., Pragmatics, Cambridge University Press, 1983.
Loui, R.P., Why Gawk for AI? SIGPLAN Notices 31(8): 8-9, 1996.
Ousterhout, John K., Scripting: Higher Level Programming for the
	21st Century, IEEE Computer, March 1998.
Shannon, Christine, Another breadth-first approach to CS I using Python, 
	Proceedings of the 34th SIGCSE technical symposium on 
	Computer science education, Reno, 2003. 
Scott, Michael L., Programming Language Pragmatics, Morgan Kaufman 2000.
Spinellis, Diomidis.  Java makes scripting languages irrelevant? IEEE 
	Software, 22(3):70-71, May/June 2005.
Zelle, J.M., Python as a First Language, 13th Annual Midwest Computer 
	Conference, 1999.

The Great Win32 Computer Language Shootout
Scriptometer: measuring the ease of SOP (Script-Oriented Programming)
A Slightly Skeptical View on Scripting Languages, Dr. Nikolai Bezroukov
WIKIPEDIA:  Scripting Language
WIKIPEDIA:  Java Programming Language/Criticism
Java?  It's So Nineties
Quotes about Java - Smalltalk
The PHP Scalability Myth
Gosling:  RADlab, scripting and scale
More Gosling, Jan 9
"Java Is Dead, Long Live Java!"  The Future of Java By: Bryan W. Taylor
	(check out the very last line... hardly a defense of java!)
Open-source LAMP a beacon to developers
The Perils of JavaSchools
Java's Demise
Ruby on Rails
Beyond Java
Stevey on Python culture
Learn to talk awk (see end comment about 12,000 lines -- we've done 2k-5k a lot)
Not in the Script: News of Java's Demise Is Premature Greg Goth
Older prechelt ieee sofwtare study on seven languages
which reminded me of kernighan's '98 thing