An algorithm, according to the Random House Unabridged Dictionary, is a set of rules for solving a problem in a finite number of steps.
One of the fundamental problems of computer science is sorting a set of items. The solutions to these problems are known as sorting algorithms and rather ironically, “the process of applying an algorithm to an input to obtain an output is called a computation” [http://mathworld.wolfram.com/Algorithm.html].
The quest to develop the most memory efficient and the fastest sorting algorithm has become one of the great mathematical challenges of the last half century, resulting in many tried and tested algorithms available to the individual who needs to sort a list of data. In fact new sorting algorithms are still being developed today, take for example the Library sort, which was published in 2004.
Of all the popular sorting algorithms, I have chosen to research and explain in detail an algorithm known as the ‘Quicksort’. Quicksort is a popular and speedy sorting algorithm that is the multi-purpose, sorting algorithm of choice for many mathematicians and computer scientists. Though of course the choosing of an algorithm comes down to which algorithm is best suited to the clients needs, and is dependent on the specific set of data to be sorted, Quicksort has proven to fulfill the required criteria on many occasions.
C.A.R. Hoare developed the Quicksort algorithm in the year 1960, while he was working for a small, English scientific computer manufacturer named Elliott Brothers (London) Ltd.
Sorting algorithms are designed to be fast, and efficient. To be able to sort a list of data as quickly as possible, using as little memory as possible. To measure or classify an algorithm according to these two criteria, we measure the algorithm’s computational complexity. The computational complexity of a sorting algorithm is it’s worst, average and best behavior. Sorting algorithms are generally classified by their computational complexity of element comparisons, against the size of the list.
This is represented with what is known as ‘Big O notation’, for example where the ideal behavior is O(n), most algorithm’s behavior is O(nlogn), and bad behavior is O(n²). O(n) behavior means that a sorting algorithm would take ten times longer to sort a list of one hundred elements, than it would to sort a list of one thousand elements. O(n²) behavior is quadratic behavior, and this would take one hundred times longer to sort a list of one hundred elements, than it would to sort a list of one thousand elements.
Proceedings of the 30th Annual ACM Symposium on Theory of Computing (STOC-98), pages 151--160, New York, May 23--26
Harrington, Tom. "Ranking and Number of Users." Gallaudet University Library. Gallaudet University, n.d. Web. 2 Dec 2013.
Lovelace and Hopper are by no means the only women who have made invaluable contributions to the field of computer science. Without Betty Holberton, who "devised the first sort-merge generator, for UNIVAC I" (AWC, "Frances..."), Grace Hopper would never have been able to design the first compiler. A more contemporary scientist, Dr. Anita Borg, has profoundly influenced the field by "designing and building a fault tolerant UNIX-based operating system" ("Short Biography of Anita Borg"), as well as developing a performance analysis method for high-speed memory systems. However, I've chosen to focus on Lovelace and Hopper because they are probably the most frequently mentioned women in computer science, and they represent two critical historical moments in the field: Lovelace helps to bring the first computer into being, while Hopper forges the start of the modern computer age.
Mark I. It was actually a electromechanical calculation. It is said that this was the first potentially computers. In 1951 Remington Rand’s came out with the UNIVAC it began
D. Cantone [2002] et.al have proposed a productive and reasonable algorithm for the internal sorting issue. It performs a running time of O(n lg n) in the size n of the input.
Computer engineering started about 5,000 years ago in China when they invented the abacus. The abacus is a manual calculator in which you move beads back and forth on rods to add or subtract. Other inventors of simple computers include Blaise Pascal who came up with the arithmetic machine for his father’s work. Also Charles Babbage produced the Analytical Engine, which combined math calculations from one problem and applied it to solve other complex problems. The Analytical Engine is similar to today’s computers.
Computer engineering, in short, is the study of the applications and advancement of computer systems. Research in this field includes but is not limited to: making technology more accessible, developing new systems that are faster and more efficient, programming software to work better with existing hardware, and using technology to improve the lives of its users.
Over the last so many years, a large amount of data has become available like a large amount of collections of photos, genetic information, and network traffic statistics, modern technologies and cheap storage facilities have made it possible to collect huge datasets. But can we effectively use all this data? The ever increasing sizes of the datasets make it imperative to design new algorithms capable of shifting through this data with extreme efficiency.
...ults are obtained by taking average of 5 experiments. The proposed method is performing 96 % efficiency than Bubble sort and some random data set equivalence with Quick sort. The proposed algorithm D-Shuffle sort compares with some standard survey papers based on Divide & Conquer sorting methodology and its execution time results based on the various data size are given in the table 1. Based on the results in the table 1, for some larger data sets, the proposed algorithm works much faster than the GCS method.
To better describe this concept, an article from Software Technology states, “This is like giving a student a set of problems and their solutions and telling that student to figure [it] out …” (2016, Panos Louridas and Christof Eber). The way the computer learns is by grouping data together. This type of method uses two different types of grouping methods to help identify possible outcomes: classification and regression algorithms.
Huss-Lederman, S., Jacobson, E. M., Johnson, J. R., Tsao, A., & Turnbull, T. (1996). Implementation of Strassen's algorithm for matrix multiplication. In Supercomputing, 1996. Proceedings of the 1996 ACM/IEEE Conference on (pp. 32-32). IEEE.
In this paper he described a new system for storing and working with large databases. Instead of records being stored in some sort of linked list of free-form records as in Codasyl, Codd's idea was to use a "table" of fixed-length records. A linked-list system would be very inefficient when storing "sparse" databases where some of the data for any one record could be left empty. The relational model solved this by splitting the data into a series of tables, with optional elements being moved out of the main table to where they would take up room only if needed.
Genetic algorithms are a randomized search method based on the biological model of evolution through mating and mutation. In the classic genetic algorithm, problem solutions are encoded into bit strings which are tested for fitness, then the best bit strings are combined to form new solutions using methods which mimic the Darwinian process of "survival of the fittest" and the exchange of DNA which occurs during mating in biological systems. The programming of genetic algorithms involves little more than bit manipulation and scoring the quality of solutions. Genetic algorithms have been applied to problems as diverse as graph partitioning and the automatic creation of programs to match mathematical functions.
The history of the computer dates back all the way to the prehistoric times. The first step towards the development of the computer, the abacus, was developed in Babylonia in 500 B.C. and functioned as a simple counting tool. It was not until thousands of years later that the first calculator was produced. In 1623, the first mechanical calculator was invented by Wilhelm Schikard, the “Calculating Clock,” as it was often referred to as, “performed it’s operations by wheels, which worked similar to a car’s odometer” (Evolution, 1). Still, there had not yet been anything invented that could even be characterized as a computer. Finally, in 1625 the slide rule was created becoming “the first analog computer of the modern ages” (Evolution, 1). One of the biggest breakthroughs came from by Blaise Pascal in 1642, who invented a mechanical calculator whose main function was adding and subtracting numbers. Years later, Gottfried Leibnez improved Pascal’s model by allowing it to also perform such operations as multiplying, dividing, taking the square root.
Algorithm is a part of discrete mathematics and very useful for the computer science. An algorithm is the ability to carry out the correct steps in the correct order and should always be considered in the context of the certain assumptions. Algorithms of arithmetic, operate with integers which they depend on a digit integer. That was the definition of an algorithm in numerical situation. The connection with the computing science is that in nowadays the algorithms are designed to be used by a machine. So algorithms can be expressed in more languages like natural language , Java, C++. The computer solves a problem by way of a computer program, which as it is mentioned above is a list of orders giving detailed instructions about the action of the computer. Algo...