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Chapter:
Abstraction
Efficiency
Like any natural language, computer languages are built around their
environments. Human cultures have developed languages as a means of
communicating their perceptions of internal, conceptual and external
environments. However what exists in one environment might not be a
part of another. Subsequently, a string of words might be used to
describe something that is uncommon to one environment, whereas in
another culture where that thing is common a single word might be used
to describe it.
For example a visitor traveling to Japan in the late 1800's might
describe a specific mode of transport as:
“A human-powered two wheeled cart, that seats one or two people
reserved for the social elite.”
However a person familiar with this mode of transport might have a
specific name for it, such as:
“Rickshaw”
Rickshaws are
not a common sight in modern times but where a regular mode of
transport in Japan, in the 1800's
Obviously if you are living in an environment where such things are
common using a single word that can effectively describe a whole
sentence can be a more efficient means of communication.
Computer languages are similar in this way, each language is developed
to run efficiently under certain conditions and circumstances yet the
same language may perform less efficiently under a different set of
circumstances.
What qualifies as an optimal environment for a computer's
programming language is something that the developer of that
language will have to define. An environment in this sense could be an
operating system, the world wide web, a network, or a combination of
these environments. This could also be a large contributing factor,
possibly explaining why there are so many different computer languages
currently in existence each with it's efficiency optimizations
for specific “environments”.
Currently Wikipedia lists approximately 661 popular computer languages
and this number is constantly growing compared to it's listing of 540
currently spoken languages (not including their derivatives). Of course
there have been many more spoken languages throughout human history,
The Cambridge Encyclopaedia of Language estimates this number to be
between 3000 to 10000, but then again what actually qualifies as a
language is a whole other topic for discussion in itself. Computer
languages share in this ambiguity. Throughout the comparatively short
history of computer languages, which can arguably be traced as far back
as the first programmable computer, the Z1 invented by Germany's Konrad
Zuse in 1938, programmers have seen languages raise to popularity and
become virtually obsolete, one such language is LISP. LISP was in many
ways synonymous with Artificial Intelligence (AI) from the mid 1950's
till the early 1970's but gradually gave way to a dwindling numbers of
devotees, who where lured by new programming paradigms such as object
oriented programming and other higher level programming language
concepts, which we will explore in greater detail later. Although this
language never really died, some would say it became somewhat
antiquated. Nonetheless, LISP started to regain popularity in the mid
1990's in a new implementation currently known as Common LISP.
Determining whether a programming language closely based on a previous
programming language should be considered a new language that is able
to stand on it's own, can be a difficult distinction to make and can
add considerably to the ambiguity around what defines and distinguishes
one computer language from another. Processing too, has been subject to
this topic of debate as it's roots in the programming language Java
have seen it referred to as a library for Java while others identify it
as stand-alone programming language.
Regardless of whether a programming language derived from another can
stand on it's own or not one of the key factors that determine it's
popularity, and ultimately contributes to a following of devotees that
develop and maintain the language, is the language's ability to achieve
a balance of being fast enough for a computer to process but easy
enough for a human to read. It is this balance that currently
determines the efficiency of a computer's programming language.
Disambiguation
Computers tend to be very literal. They accept specific instructions
more readily than vague descriptions of what you are hoping to achieve
with their help. Such that a statement like the above mentioned, and
repeated below:
“... draw a circle that has a diameter of 55 pixels and who's center is
somewhere close to the top left of my screen...”
would not be as effective as the statement:
ellipse(56, 46, 55, 55);
The first statement although a perfectly acceptable command issued in
English, would fail dismally when translated directly into
computer-speak for several reasons relating to the ambiguity associated
with it.
Firstly the longer a command tends to be the more prone it is to
incorporating an erroneous syntax. Computers are very specific about
the type of syntax you use to communicate with them. Syntax in terms of
the English definition is the particular arrangements of words making
up a sentence. In computer terms, syntax has a very similar meaning but
is even more relevant and specific in it's implementation. Words must
follow a particular sequence within the context of a command issued to
a computer determined by the language you are currently programming in,
and may not be rearranged into various discourses simply because you
find them to be more meaningful.
Computers have truly amazing mathematical capabilities and predictably
congruent mediocre social skills. Subsequently concepts such as circles
and squares which are simply mathematical concepts abstracted for human
convenience have little or no relevance to a computer. For example if
you were to consider that a circle, as per another description, could
be an ellipse with equidistant radii to each point encompassing it's
edge; or technically speaking a square is actually a rectangle with
it's height equal to it's width. Descriptive abstractions such as these
for human convenience are in fact very inconvenient for a computer, and
as a result in Processing we refer to a “circle” and an “ellipse” using
Processing specific syntax that removes the ambiguity and abstraction
for the convenience of a spoken language and groups them into the same
context. Subsequently if we want to describe a circle we refer to it as
an ellipse with equal dimensions in height and width or more
specifically:
ellipse(56,46,55,55);
Finally I'm sure that if computers had a sense of humour, they would
find our former description of the location of our circle “ somewhere
close to the top left of my screen” to be somewhat uninformed and
laughable, not to mention words such as “somewhere” and “my” which
might condition a response equivalent to that of an existential dilemma
for a computer. If you supply a computer program with specific screen
positions in terms of x, y and z and dimensions in terms of width,
height and depth either communicated explicitly or implicitly through
an expression (which is something we will discuss in more detail later)
you will find your programs to have more predictable and efficient
results and would help to remove ambiguities that could lead to errors.
Screen space and dimensions are concepts we will be dealing with in
more detail in later chapters. Of course there are times when
randomness and unpredictability are desirable qualities in a program,
in which case no other resources available to man can produce a series
of unpredictable results more efficiently than computers. This is a
testament to why people devotedly invest in computers to provide the
sequence of random digits that could potentially make casinos loose
millions upon millions to gambling patrons.
Computers, and
subsequently software are used in various fields of medical
technologies where predictability is of the utmost importance. Gambling
machines also use software but in contrast to medical software
predictability in the application of the software, is an undesirable
effect for the machine owners.
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