Software engineering is the application of a systematic, disciplined, quantifiable approach to the development, operation, and maintenance of software, and the study of these approaches; that is, the application of engineering to software.The term software engineering first appeared in the 1968 NATO Software Engineering Conference and was meant to provoke thought regarding the current "software crisis" at the time.  Since then, it has continued as a profession and field of study dedicated to creating software that is of higher quality, more affordable, maintainable, and quicker to build. Since the field is still relatively young compared to its sister fields of engineering, there is still much debate around what software engineering actually is, and if it conforms to the classical definition of engineering. It has grown organically out of the limitations of viewing software as just programming. Software development is a term sometimes preferred by practitioners[who?] in the industry who view software engineering as too heavy-handed and constrictive to the malleable process of creating software. Although software engineering is a young profession, the field's future looks bright as Money Magazine and Salary.com rated software engineering as the best job in America in 2006.
Thursday, July 16, 2009
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Monday, July 13, 2009
The broader field of theoretical computer science encompasses both the classical theory of computation and a wide range of other topics that focus on the more abstract, logical, and mathematical aspects of computing.
Mathematical logic Automata theory Number theory Graph theory Type theory Category theory Computational geometry Quantum computing theory
Friday, July 10, 2009
Thursday, July 9, 2009
Monday, July 6, 2009
Approximately around the year 825, Persian mathematician Al-Khwarizmi wrote a book, On the Calculation with Hindu Numerals, that was principally responsible for the diffusion of the Indian system of numeration in the Middle East and then Europe. Around the 12th century, there was translation of this book written into Latin: Algoritmi de numero Indorum. These books presented newer concepts to perform a series of steps in order to accomplish a task such as the systematic application of arithmetic to algebra. By derivation from his name, we have the term algorithm.
Around the 3rd century BC, Indian mathematician Pingala discovered the binary numeral system. In this system, still used today to process all modern computers, a sequence of ones and zeros can represent any number.
In 1703, Gottfried Leibniz developed logic in a formal, mathematical sense with his writings on the binary numeral system. In his system, the ones and zeros also represent true and false values or on and off states. But it took more than a century before George Boole published his Boolean algebra in 1854 with a complete system that allowed computational processes to be mathematically modeled.
Birth of computer science
Before the 1920s, computers (sometimes computors) were human clerks that performed computations. They were usually under the lead of a physicist. Many thousands of computers were employed in commerce, government, and research establishments. Most of these computers were women, and they were known to have a degree in calculus. Some performed astronomical calculations for calendars.
After the 1920s, the expression computing machine referred to any machine that performed the work of a human computer, especially those in accordance with effective methods of the Church-Turing thesis. The thesis states that a mathematical method is effective if it could be set out as a list of instructions able to be followed by a human clerk with paper and pencil, for as long as necessary, and without ingenuity or insight.
Machines that computed with continuous values became known as the analog kind. They used machinery that represented continuous numeric quantities, like the angle of a shaft rotation or difference in electrical potential.
Digital machinery, in contrast to analog, were able to render a state of a numeric value and store each individual digit. Digital machinery used difference engines or relays before the invention of faster memory devices.
The phrase computing machine gradually gave away, after the late 1940s, to just computer as the onset of electronic digital machinery became common. These computers were able to perform the calculations that were performed by the previous human clerks.
Since the values stored by digital machines were not bound to physical properties like analog devices, a logical computer, based on digital equipment, was able to do anything that could be described "purely mechanical." Alan Turing, known as the Father of Computer Science, invented such a logical computer known as the Turing Machine, which later evolved into the modern computer. These new computers were also able to perform non-numeric computations, like music.
Emergence of a discipline
The theoretical groundwork
The mathematical foundations of modern computer science began to be laid by Kurt Gödel with his incompleteness theorem (1931). In this theorem, he showed that there were limits to what could be proved and disproved within a formal system. This led to work by Gödel and others to define and describe these formal systems, including concepts such as mu-recursive functions and lambda-definable functions.
1936 was a key year for computer science. Alan Turing and Alonzo Church independently, and also together, introduced the formalization of an algorithm, with limits on what can be computed, and a "purely mechanical" model for computing.
These topics are covered by what is now called the Church–Turing thesis, a hypothesis about the nature of mechanical calculation devices, such as electronic computers. The thesis claims that any calculation that is possible can be performed by an algorithm running on a computer, provided that sufficient time and storage space are available.
Turing also included with the thesis a description of the Turing machine. A Turing machine has an infinitely long tape and a read/write head that can move along the tape, changing the values along the way. Clearly such a machine could never be built, but nonetheless, the model can simulate the computation of any algorithm which can be performed on a modern computer.
Turing is so important to computer science that his name is also featured on the Turing Award and the Turing test. He contributed greatly to British code-breaking successes in the Second World War, and continued to design computers and software through the 1940s, but committed suicide in 1954.
At a symposium on large-scale digital machinery in Cambridge, Turing said, "We are trying to build a machine to do all kinds of different things simply by programming rather than by the addition of extra apparatus".
In 1948, the first practical computer that could run stored programs, based on the Turing machine model, had been built - the Manchester Baby.
Shannon and information theory
Up to and during the 1930s, electrical engineers were able to build electronic circuits to solve mathematical and logic problems, but most did so in an ad hoc manner, lacking any theoretical rigor. This changed with Claude Elwood Shannon's publication of his 1937 master's thesis, A Symbolic Analysis of Relay and Switching Circuits. While taking an undergraduate philosophy class, Shannon had been exposed to Boole's work, and recognized that it could be used to arrange electromechanical relays (then used in telephone routing switches) to solve logic problems. This concept, of utilizing the properties of electrical switches to do logic, is the basic concept that underlies all electronic digital computers, and his thesis became the foundation of practical digital circuit design when it became widely known among the electrical engineering community during and after World War II.
Shannon went on to found the field of information theory with his 1948 paper titled A Mathematical Theory of Communication, which applied probability theory to the problem of how to best encode the information a sender wants to transmit. This work is one of the theoretical foundations for many areas of study, including data compression and cryptography.