Computer programming (often shortened to
programming,
scripting, or
coding) is the process of
designing,
writing,
testing,
debugging,
and maintaining the
source code of
computer
programs. This source code is written in one or more
programming languages (such as
C++,
C#,
Java,
Python,
Smalltalk,
etc.). The purpose of programming is to create a set of instructions that
computers use to perform specific operations or to exhibit desired behaviors.
The process of writing source code often requires expertise in many different
subjects, including knowledge of the application domain, specialized
algorithms
and
formal logic.
There is an ongoing debate on the extent to which
the writing of programs is an
art form, a
craft, or an
engineering discipline.
[1]
In general, good programming is considered to be the measured application of
all three, with the goal of producing an efficient and evolvable software
solution (the criteria for "efficient" and "evolvable" vary
considerably). The discipline differs from many other technical professions in
that
programmers,
in general, do not need to be licensed or pass any standardized (or
governmentally regulated) certification tests in order to call themselves
"programmers" or even "software engineers." Because the
discipline covers many areas, which may or may not include critical
applications, it is debatable whether licensing is required for the profession
as a whole. In most cases, the discipline is self-governed by the entities
which require the programming, and sometimes very strict environments are
defined (e.g.
United States Air Force use of
AdaCore and
security clearance). However, representing oneself as a "Professional
Software Engineer" without a license from an accredited institution is
illegal in many parts of the world.
Another ongoing debate is the extent to which the
programming language used in writing
computer
programs affects the form that the final program takes. This debate is
analogous to that surrounding the
Sapir–Whorf hypothesis[2]
in
linguistics
and
cognitive science, which postulates that a
particular spoken language's nature influences the habitual thought of its
speakers. Different language patterns yield different patterns of
thought. This
idea challenges the possibility of representing the world perfectly with
language, because it acknowledges that the mechanisms of any language condition
the thoughts of its speaker community.
History
Ada
Lovelace created the first
algorithm designed for processing by a computer and is
usually recognized as history's first computer programmer.
Ancient cultures had no conception of computing
beyond simple
arithmetic. The only mechanical device that existed for
numerical computation at the beginning of human history was the
abacus, invented in
Sumeria circa 2500
BC. Later, the
Antikythera mechanism, invented some time
around 100 BC in
ancient Greece, was the first mechanical calculator
utilizing gears of various sizes and configuration to perform calculations,
[3]
which tracked the
metonic cycle still used in lunar-to-solar calendars,
and which is consistent for calculating the dates of the
Olympiads.
[4]
The
Kurdish
medieval scientist
Al-Jazari built programmable
Automata
in 1206 AD. One system employed in these devices was the use of pegs and
cams placed into a wooden
drum at specific locations, which would sequentially trigger
levers that in turn
operated
percussion instruments. The output of this
device was a small drummer playing various rhythms and drum patterns.
[5][6]
The
Jacquard
Loom, which Joseph Marie Jacquard developed in 1801, uses a series of
pasteboard
cards with holes punched in them. The hole pattern represented the pattern that
the loom had to follow in weaving cloth. The loom could produce entirely
different weaves using different sets of cards.
Charles
Babbage adopted the use of
punched
cards around 1830 to control his
Analytical
Engine. The first computer program was written for the Analytical Engine by
mathematician
Ada Lovelace to calculate a sequence of
Bernoulli
numbers.
[7]
The synthesis of numerical calculation, predetermined operation and output,
along with a way to organize and input instructions in a manner relatively easy
for humans to conceive and produce, led to the modern development of computer
programming. Development of computer programming accelerated through the
Industrial Revolution.
Data and instructions were once
stored on external
punched cards, which were kept in order and arranged
in program decks.
In the 1880s,
Herman
Hollerith invented the recording of data on a medium that could then be
read by a machine. Prior uses of machine readable media, above, had been for
lists of instructions (not data) to drive
programmed machines such as
Jacquard
looms and
mechanized musical instruments. "After some initial
trials with paper tape, he settled on
punched
cards..."
[8]
To process these punched cards, first known as "Hollerith cards" he
invented the
keypunch,
sorter, and
tabulator unit record machines.
[9]
These inventions were the foundation of the data processing industry. In 1896
he founded the
Tabulating Machine Company (which
later became the core of
IBM).
The addition of a
control panel (plugboard) to his 1906 Type I Tabulator
allowed it to do different jobs without having to be physically rebuilt. By the
late 1940s, there were several unit record calculators, such as the
IBM 602 and
IBM 604, whose
control panels specified a sequence (list) of operations and thus were
programmable machines.
The invention of the
von Neumann architecture allowed computer programs
to be stored in
computer memory. Early programs had to be
painstakingly crafted using the instructions (elementary operations) of the
particular machine, often in
binary notation. Every model of computer
would likely use different instructions (
machine
language) to do the same task. Later,
assembly
languages were developed that let the programmer specify each instruction
in a text format, entering abbreviations for each operation code instead of a
number and specifying addresses in symbolic form (e.g., ADD X, TOTAL). Entering
a program in assembly language is usually more convenient, faster, and less
prone to human error than using machine language, but because an assembly
language is little more than a different notation for a machine language, any
two machines with different instruction sets also have different assembly
languages.
Some of the earliest computer programmers were
women during World War II. According to Dr.
Sadie Plant,
programming is essentially feminine-not simply because women, from
Ada
Lovelace to
Grace Hopper, were the first programmers, but because
of the historical and theoretical ties between programming and what Freud
called the quintessentially feminine invention of weaving, between female
sexuality as mimicry and the mimicry grounding Turing's vision of computers as
universal machines. Women, Plant argues, have not merely had a minor part to
play in the emergence of digital machines...Theirs is not a subsidiary role which
needs to be rescued for posterity, a small supplement whose inclusion would set
the existing records straight...Hardware, software, wetware-before their
beginnings and beyond their ends, women have been the simulators, assemblers,
and programmers of the digital machines.
[10]
In 1954,
FORTRAN was
invented; it was the first
high level programming language to have a
functional implementation, as opposed to just a design on paper.
[11][12]
(A high-level language is, in very general terms, any programming language that
allows the programmer to write programs in terms that are more
abstract than assembly language
instructions, i.e. at a level of abstraction "higher" than that of an
assembly language.) It allowed programmers to specify calculations by entering
a formula directly (e.g.
Y = X*2 + 5*X + 9). The
program text, or
source, is converted into machine instructions using a
special program called a
compiler, which translates the FORTRAN program into machine
language. In fact, the name FORTRAN stands for "Formula Translation".
Many other languages were developed, including some for commercial programming,
such as
COBOL.
Programs were mostly still entered using punched cards or
paper tape.
(See
computer programming in the
punch card era). By the late 1960s,
data storage devices and
computer
terminals became inexpensive enough that programs could be created by
typing directly into the computers.
Text
editors were developed that allowed changes and corrections to be made much
more easily than with punched cards. (Usually, an error in punching a card
meant that the card had to be discarded and a new one punched to replace it.)
Modern programming languages like
C++ are
exponentially more powerful than their predecessors.
As time has progressed, computers have made giant
leaps in the area of processing power. This has brought about newer programming
languages that are more abstracted from the underlying hardware. Popular
programming languages of the modern era include
ActionScript,
C++,
C#,
Haskell,
HTML with
PHP,
Java,
JavaScript,
Objective-C,
Perl,
Python,
Ruby,
Smalltalk,
SQL,
Visual
Basic, and dozens more.
[13]
Although these high-level languages usually incur greater
overhead, the increase in speed of modern
computers has made the use of these languages much more practical than in the
past. These increasingly abstracted languages typically are easier to learn and
allow the programmer to develop applications much more efficiently and with
less source code. However, high-level languages are still impractical for a few
programs, such as those where low-level hardware control is necessary or where
maximum processing speed is vital. Computer programming has become a popular
career in the
developed world, particularly in the
United
States,
Europe,
and
Japan. Due to
the high labor cost of programmers in these countries, some forms of
programming have been increasingly subject to
offshore outsourcing (importing software and
services from other countries, usually at a lower wage), making programming
career decisions in developed countries more complicated, while increasing
economic opportunities for programmers in less developed areas, particularly
China and
India.
Modern programming
Quality requirements
Whatever the approach to software development may
be, the final program must satisfy some fundamental properties. The following
properties are among the most relevant:
- Reliability: how often the results
of a program are correct. This depends on conceptual correctness of
algorithms, and minimization of programming mistakes, such as mistakes in
resource management (e.g., buffer
overflows and race conditions) and logic errors (such as
division by zero or off-by-one errors).
- Robustness: how well a
program anticipates problems not due to programmer error. This includes
situations such as incorrect, inappropriate or corrupt data,
unavailability of needed resources such as memory, operating system
services and network connections, and user error.
- Usability:
the ergonomics
of a program: the ease with which a person can use the program for its
intended purpose, or in some cases even unanticipated purposes. Such
issues can make or break its success even regardless of other issues. This
involves a wide range of textual, graphical and sometimes hardware
elements that improve the clarity, intuitiveness, cohesiveness and
completeness of a program's user interface.
- Portability: the range of computer hardware and operating system platforms on which the source
code of a program can be compiled/interpreted and run. This depends on
differences in the programming facilities provided by the different
platforms, including hardware and operating system resources, expected
behaviour of the hardware and operating system, and availability of
platform specific compilers (and sometimes libraries) for the language of
the source code.
- Maintainability:
the ease with which a program can be modified by its present or future
developers in order to make improvements or customizations, fix bugs
and security holes, or adapt it to new
environments. Good practices during initial development make the
difference in this regard. This quality may not be directly apparent to
the end user but it can significantly affect the fate of a program over
the long term.
- Efficiency/performance: the amount of system
resources a program consumes (processor time, memory space, slow devices
such as disks, network bandwidth and to some extent even user
interaction): the less, the better. This also includes correct disposal of
some resources, such as cleaning up temporary
files and lack of memory leaks.
Readability of source code
In computer programming,
readability
refers to the ease with which a human reader can comprehend the purpose,
control flow, and operation of
source code.
It affects the aspects of quality above, including portability, usability and
most importantly maintainability.
Readability is important because programmers
spend the majority of their time reading, trying to understand and modifying
existing source code, rather than writing new source code. Unreadable code
often leads to
bugs, inefficiencies, and
duplicated
code. A study
[14]
found that a few simple readability transformations made code shorter and
drastically reduced the time to understand it.
Following a consistent
programming
style often helps readability. However, readability is more than just
programming style. Many factors, having little or nothing to do with the
ability of the computer to efficiently compile and execute the code, contribute
to readability.
[15]
Some of these factors include:
Various
visual programming languages have also
been developed with the intent to resolve readability concerns by adopting
non-traditional approaches to code structure and display.
Algorithmic complexity
The academic field and the engineering practice
of computer programming are both largely concerned with discovering and
implementing the most efficient
algorithms for a given class of problem. For this purpose,
algorithms are classified into
orders using so-called
Big O
notation, which expresses resource use, such as execution time or memory
consumption, in terms of the size of an input. Expert programmers are familiar
with a variety of well-established algorithms and their respective complexities
and use this knowledge to choose algorithms that are best suited to the
circumstances.
Methodologies
The first step in most formal software
development processes is requirements analysis, followed by testing to
determine value modeling, implementation, and failure elimination (
debugging).
There exist a lot of differing approaches for each of those tasks. One approach
popular for
requirements analysis is
Use Case
analysis. Nowadays many programmers use forms of
Agile software development where the
various stages of formal software development are more integrated together into
short cycles that take a few weeks rather than years. There are many approaches
to the
Software development process.
Popular modeling techniques include
Object-Oriented Analysis and Design (
OOAD) and Model-Driven Architecture (
MDA). The Unified Modeling Language (
UML) is a notation used for both the OOAD
and MDA.
A similar technique used for database design is
Entity-Relationship Modeling (
ER Modeling).
Measuring language usage
It is very difficult to determine what are the
most popular of modern programming languages. Some languages are very popular
for particular kinds of applications (e.g.,
COBOL is still strong
in the corporate data center
[citation needed], often on
large
mainframes,
FORTRAN in engineering applications,
scripting languages in
Web
development, and
C in
embedded
applications), while some languages are regularly used to write many
different kinds of applications. Also many applications use a mix of several
languages in their construction and use. New languages are generally designed
around the syntax of a previous language with new functionality added (for
example
C++ adds
object-orientedness to C, and
Java adds memory management and
bytecode to
C++).
Methods of
measuring programming
language popularity include: counting the number of job advertisements that
mention the language,
[16]
the number of books sold and courses teaching the language (this overestimates
the importance of newer languages), and estimates of the number of existing
lines of code written in the language (this underestimates the number of users
of business languages such as COBOL).
Debugging
The
bug
from 1947 which is at the origin of a popular (but incorrect) etymology for the
common term for a software defect.
Debugging, is a very important task in the software
development process since having defects in a program can have significant
consequences for its users. Some languages are more prone to some kinds of
faults because their specification does not require
compilers to
perform as much checking as other languages. Use of a
static code analysis tool can help detect some
possible problems.
Programming languages
Different programming languages support different
styles of programming (called
programming paradigms). The choice of
language used is subject to many considerations, such as company policy,
suitability to task, availability of third-party packages, or individual
preference. Ideally, the programming language best suited for the task at hand
will be selected. Trade-offs from this ideal involve finding enough programmers
who know the language to build a team, the availability of
compilers for
that language, and the efficiency with which programs written in a given
language execute. Languages form an approximate spectrum from
"low-level" to "high-level"; "low-level"
languages are typically more machine-oriented and faster to execute, whereas
"high-level" languages are more abstract and easier to use but
execute less quickly. It is usually easier to code in "high-level" languages
than in "low-level" ones.
Source: Wikipedia
