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Chapter:
Abstraction
Abstraction
Representing the abstract concept of something like data in the form of
high and low voltages with a series of 1's and 0's can be quite useful,
but still very difficult to read and understand. Imagine having to
memorize all of those sequences in order to be an efficient programmer.
It would take exorbitant amounts of time to create the simplest of
software programs. Fortunately the process of representing
human-relevant concepts to a computer does not stop at binary code.
Since we know that a certain sequence of 1's and 0's on a certain type
of machine such as the sequence “00110101” can be used to represent the
number “53” why not make the sequence “01001000” and “01101001”
represent the characters “h” and “i” put together to make the word
“hi”. This is exactly what software developers do, the process of
taking a complex set of data and representing it in a more
human-readable format is known as abstraction. As you can imagine this
makes it a lot simpler to communicate with a computer, so instead of
typing “01001000 01101001” we can simply type “hi” and
thanks to the process of abstraction our computer knows what to display
even though it's reading a sequence of high and low voltages at the
simplest level.
Abstraction is great because it makes the process of communicating with
computers easier, so you might be thinking to yourself why then is
programming and source code so cryptic and far removed from a common
natural spoken human language such as English? Surely, if we can
abstract complex data why not keep on abstracting concepts to computers
until it can understand a human specific language like plain and simple
English?
For example if we wanted to draw a circle on a computer screen why
can't we just say to a computer:
“Computer, could you please draw a circle that has a diameter of 55
pixels and who's center is somewhere close to the top left of my
screen, thanks?”
Instead we communicate with our computers like this:
ellipse(56,
46, 55, 55);
There are three main issues to consider here speed, efficiency and
disambiguation.
Speed
One of the main reasons we cannot continue to abstract our
communications with computers to the point where everyday English is
used, is due to the speed at which data can be processed.
As we abstract data in order to make it more human-readable that same
data becomes less machine-readable, and in order for a machine to be
able to make anything useful out of that data it must first convert
that data into a machine-readable format.
All of this abstracting and un-abstracting requires valuable system
resources and energy, system resources and energy that could be used
more effectively elsewhere. Subsequently as we move further away from
machine code we require faster more powerful computers to process the
data we create.
It's estimated that under certain circumstances a consumer grade Intel
Core i7 3.3 GHz processor can preform 147,600 Million instructions per
second, and if you've ever used one of these processors you'll probably
also note that even with all of that processing power there are certain
situations where your computer can still lag!
This does not necessarily have anything to do with the processor
specifically but simply due to the massive amounts of data that an
average modern day computer is expected to cope with. To put this into
perspective consider that 40 years ago in order to send a man to the
moon computers with a clock speed of 0.043MHz and 64Kbyte of RAM were
required to run software ranging about 6MB in size, by today's
standards a single modern day home computer could be about 77 million
times more powerful than the computers used to launch a space shuttle,
navigate it to the moon and safely return it to earth such as the
Apollo Guidance Computer. In retrospect the modern day needs we place
on our computers can be somewhat demanding.
The Apollo
Guidance Computer used on Apollo 11 on the left and the NASA Manned
Spacecraft Center on the right. Technology from the 1960's.
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