Rendy's Blog » Introduction

Abstraction

Rendy — Sat, 05 Dec 2009 15:27:27 +0000

The concept of abstraction so permeates the study of computer science and the design of computer systems that it behoves me to address it in this introduction. The term abstraction, as we are using it here, refers to the distinction between the external properties of an entity and detail of the entity and the details of the entity’s internal composition. It is abstraction that allows us to ignore the internal details of complex device such as a computer, automobile, or microwave oven and use it as a single, comprehensible unit. Moreover, it is by means of abstraction that such complex systems are designed and manufactured in the first place. Computers, automobiles, and microwave ovens are constructed from components, each of which is constructed from smaller components. Each components represents a level of abstraction at which the use of component is isolated the details of the component’s internal composition.

It is by applying abstraction, then, that we are able to construct, analyze, and manage large, complex computer systems, which would be overwhelming of viewed in their entirely at a detailed level. At each level of abstraction, we view the systems in terms of components, called abstract tools, whose internal components we ignore. This allows us to concentrate on how each component interacts with other components at same level and how the collection as a whole forms a higher-level component. Thus we are able to comprehend the part of the system that is relevant to the task at hand rather than being lost in a sea of details.

Abstraction is not limited to science and technology. It is an important simplification technique with which our society has created a lifestyle that would otherwise be impossible. Few of us understand how the various convenience of daily life are actually implemented. We eat food and wear clothes that we cannot produce by ourselves. We use electrical devices without understanding the underlying technology. We use the services of others without knowing the details of their professions. With each new advancement, a small part of society choose to specialize in its implementation while the rest of us learn to use the result as abstract tools. In this manner, society’s warehouse of abstract tools expands, and society’s ability to progress increases.

Abstraction is everywhere, have you ever wonder how your iPod works?

Abstraction is a recurring theme in our study. We will learn that computing equipment is constructed in levels of abstract tools. We will also see that the development of large software systems is accomplished in a modular fashion in which each module is used as an abstract tool in larger modules. Moreover, abstraction plays an important role in the task of advancing computer science, itself, allowing researchers to focus attention on particular ares within a complex field. In fact, the organization of this text reflects this characteristic of the science. Each subject in computer science, focuses on particular area within the science, is often surprisingly independent of the others, yet together the chapters form a comprehensive overview of a vast field of study.

The Science of Algorithms

Rendy — Fri, 04 Dec 2009 16:28:07 +0000

Conditions such as limited data storage capabilities and intricate, time consuming programming procedures restricted the complexity of the algorithms utilized in early computing machines. However, as these limitations began to disappear, machine were applied to increasingly larger and more complex tasks. As attempts to express the composition of these tasks in algorithmic form began to tax the abilities of the human mind, more and more research effort were directed toward the study of algorithms and the programming process.

It was in this context that the theoretical work of mathematician began to pay dividends. As a consequence of Gödel’s incompleteness theorem, mathematician had already been investigating those questions regarding algorithmic process that advancing technology was now raising. With that, the stage was set for the emergence of a new discipline known as computer science.

Today, computer science has established itself as the science of algorithms. The scope of this science is broad, drawing from such diverse subjects as mathematics, engineering, psychology. biology, business administration, and linguistics. Indeed, researchers in different branches of computer science may have very distinct definitions of the science. For example, a researcher in the field of computer science as the advancement and application of technology. But, a researcher in the field of database systems may see computer science as seeking ways to make information systems more useful. And, a researcher in the field of artificial intelligence may regard computer science as the study if intelligence and intelligent behaviour.

Thus, an introduction to computer science must include a variety of topics. Which in each case there’s introduction to the central ideas in the subject, the current topics od research, and some of the technique being applied to advance knowledge in the area.

The origins of Computing Machines

Rendy — Fri, 04 Dec 2009 01:18:54 +0000

Today’s computers have an huge family tree. One of the earliest computing devices was Abacus also called counting frame. The use of Abacus dates back 2700-2300 BC, the ancient Mesopotamian was the first civilization to be found using this device. Then it was spread to other civilization from Ancient Egypt, Iranian Persian, Greek, Roman, Chinese, Indian, Japanese, Korean, Native American and finally Russian. The machine is quite simple, constructed from frame that usually made from Bamboo, and beads sliding on rods. As the beads moved back and forth on the rods, their positions represent stored values. For the processing system, the machine depend on human operator. Thus Abacus is not really computational device, unless it is combined with a human operator, otherwise it is only merely data storage system.

The development of Computing Machines in more recent year was based on technology of gears. Blaise Pascal (1632 – 1662) of France, Gottfried Wilhelm Leibniz (1646 – 1716) of Germany, and Charles Babbage (1792 – 1871) of England were among the inventors. These Machine represented data through gear positioning, with data being input mechanically by establishing initial gear positions. Output from Pascal’s and Leibniz’s machines was achieved by observing the final gear positions. Babbage, on the other hand, envisioned machines that would print results of computation on paper so that the possibility of transcription errors would be eliminated.

As for the ability to follow an algorithm, we can see a progression of flexibility in these machines. Pascal’s machine was built to perform only addition. Consequently, the appropriate sequence of steps was embedded into the structure of the machine itself. In a similar manner, Leibniz.s machine had its algorithms firmly embedded in its architecture, although it offered a variety of arithmetic operations from which the operator could select. Babbage’s difference Engine (Demonstration Model) could be modified to perform a variety of calculations, but his Analytical Engine was designed to read instructions in the form of holes in paper cards. Thus Babbage’s Analytical Engine could was programmable. In fact, Augusta Ada Byron who published a paper in which she demonstrated how Babbage’s Analytical Engine could be programmed to perform various computations, is often identified today as the world’s first programmer.

Babbage Analytical Engine

The idea of communicating an algorithm via holes in paper was not originated by Babbage. He got the idea from Joseph Jacquard (1752 – 1834), who, in 1801, had developed a weaving loom in which the steps to be performed during the weaving process were determined by patterns of holes in paper cards. In this manner, the algorithm followed by the loom could be changed easily to produce a different woven designs. Another beneficiary of Jacquard’s idea was Herman Hollerith (1860 – 1929), who applied the concept of representing information as holes in paper cards to speed up the tabulation process in the 1890 U.S census. (It was this work by Hollerith that led to the creation of IBM). Such cards ultimately came to be known as punched cards and survived as popular means of communicating with computers well into the 1970s. Indeed, the technique lives on today, as witnessed by the voting issues raised in the 2000 in the U.S presidential election.

The technique of the time was unable to produce the complex gear-driven machines of Pascal, Leibniz, and Babbage in a financially feasible manner. But with the advances in electronic in the early 1900s, this barrier was overcome. Examples of this progress include the electromechanical machine of George Stibitz, completed in 1940 at Bell Laboratories, and the Mark 1, completed in 1944 at Harvard University by Howard Eiken and a group of IBM engineers. These machines made heavy use of electronically controlled mechanical relays. In this sense they were obsolete almost as soon as they were built, because other researchers were applying the technology of vacuum tubes to construct totally electronic computers. The first of these machines was apparently the Atanasoff-Berry machine, constructed during the period from 1937 to 1941 at Iowa State Collage (now Iowa State University) by John Atanasoff and his assistant, Clifford Berry.Another was a machine called Colossus, built under the direction of Tommy Flowers in England to decode German messages during the latter part of World War II (Many of these machine were built, but Military secrecy and issues of national security kept their existence from becoming part of “computer family tree”). Other, more flexible machine such as the ENIAC (Electronic Numerical Integrator and Calculator) developed by John Mauchly and J. Presper Eckert at the Moore School of Electrical Engineering University of Pennsylvania, soon followed.

ENIAC : One of the very first electronic computer, It was very huge that occupied a big room

From that point on, the history of Computing machines has been closely linked to advancing technology, including the invention of transistors and the subsequent development of Integrated Circuits, the establishment of communication satellites and advances in optic technology. Today, small handheld computers have more computing power than the room-size machines of the 1940s and can exchange information quickly via global communication systems.

A major step forward popularizing computing was the development of desktop computers. The origins of these machine can be traced to the computer hobbyist who began to experiment with homemade computers shortly after the development of the large research machines of the 1940s. It was this within this “underground” of hobbyist activity that Steve Jobs and Stephen Wozniak built a commercially viable home computers and in 1976, established Apple Computer, Inc (now Apple Inc.) to manufacture and market their products. Other companies that marketed similar products were Commodore, Heathkit, and Radio Shack. Although these product were popular among computer hobbyist, they were not widely accepted by the business community, which continued to look to well-established IBM for the majority of its computing needs.

In 1981, IBM introduced its first desktop computer, called the personal computer, or PC, whose underlying software was developed by newly formed company known as Microsoft. The PC was an instant success and legitimized the desktop computer as an established commodity in the minds of the business community. Today, the term PC is widely used to refer all those machines (from various manufacturers) whose design has evolved from IBM’s initial desktop computer, most of which continue to be marketed with software from Microsoft. At times, however, the term PC is used interchangeably with the generic terms desktop or laptop.

IBM Personal Computer

The miniaturization of computers and their expanding capabilities have brought computer technology to the forefront of today’s society. Computer technology is so prevalent now that familiarity with it is fundamental to being a member of modern society. Home computers have become integrated with entertainment and communication systems. Cellular telephones, digital cameras, and audio/video players are now combined with computer technology in single hand-held devices called personal digital assistant (PDAs) that communicate via radio broadcast technology. Computing technology has altered the ability of government to exert control; had enormous impact on global economics; led to starling advances in scientific research; revolutionized the role of data collection, storage, and applications; and has repeatedly challenged society’s status quo. The result is a proliferation of subjects surrounding computer science, each of which is now significant field of study in its own right. Moreover, as with mechanical engineering and physics, it is often difficult to draw a line between these fields and computer science itself.

Today’s computer is very small and lightweight, thanks to miniaturization. This 2009 Macbook Air has much more computing power than room-size computers in the 1940s.

The Role of Algorithms

Rendy — Mon, 30 Nov 2009 11:49:19 +0000

Now let’s begin with the most fundamental concept on Computer Science, which is Algorithm. Algorithm is a set of steps that defines how a task is completed or performed. For example recipes are algorithm for cooking, directions are algorithm for finding your way around strange place, there is also a step by step guide to perform a machinery that is called algorithm, and for example you learn a magic trick you need an algorithm to perform that.

Before a machine such as a computer can perform a task, an algorithm for performing that task must be discovered and represented in a form that is compatible with the machine. A representation of an algorithm is called a program. A program usually displayed on computer screens. What you see on the screen does not necessarily what happened on the background, programs are encoded in a manner compatible with the technology of the machine. The process of developing program, encoding it in machine-compatible form, and inserting it into a machine is called programming. Programs, and the algorithms they represent, are collectively referred to as software, the machinery itself called hardware.

An algorithm to cook rice

Final result : Easy, Quick, Healthy, Inexpensive Tasty Rice

Steps:

Step 1. Rinse the rice. Rinse until the water is clear and not cloudy.

Step 2. Combine long grain rice and water. For every cup of long grain rice, add 1 1/2 cups water.

Step 3. Boil the Rice. Bring the rice to a boil, uncovered, at medium heat.

Step 4. When the rice is boiling, turn the heat down to medium low. Place the lid on the pot, tilting it to allow steam to escape.

Step 5. After the rice has been cooking for a few minutes, check for holes or “craters”.

Step 6. When you can see the holes or crater, put the lid on tight. Turn the heat down to low.

Step 7. Simmer the covered rice for another 15 minutes. Fluff it up with a fork and serve hot.

Now, the rice ready to serve. Final result achieved.

The study of algorithm began as a subject in mathematics’. Indeed, the search for algorithm was a significant activity if mathematician long before the development of today’s computers. The goal was to find a single set of directions that described how all problems of a particular type could be solved. One of the best known examples of this early research is the long division algorithm for finding the quotient of two multiple-digit numbers. Another example is the Euclidian algorithm, discovered by the ancient Greek mathematician Euclid, for finding the greatest common divisor of two positive integers.

The Euclidian Algorithm for Finding the Greatest Common Divisor of two positive integers

Description : This algorithm, assumes that its input consists of two positive integers and proceeds to compute the greatest common divisor of these two values.

Procedure:

Step 1. Assign X and Y the value of the larger and smaller of the two input values, respectively.

Step 2. Divide X and Y, and call the remainder N.

Step 3. If N is not 0, then assign X the return value of Y, assign Y the value of N, and return to step 2; otherwise, the greatest common divisor is the value currently assigned to Y.

Once an algorithm for performing a task has been found, the performance of that task no longer requires an understanding of the principles on which the algorithm is based. Instead, the performance of the task is reduced to the process merely following directions. It is through this ability to capture and convey intelligence by means of algorithms that we are able to build machines that perform useful tasks. Consequently, the level of intelligence displayed by machines is limited by the intelligence that can be conveyed through algorithms. We can construct a machine to perform a task only if an algorithm exists for performing that task.In turn, if no algorithm exists for solving a problem, then the solution of that problem lies beyond the capability of machines.

Indentifying the limitation of algorithmic capabilities solidified as a subject in mathematics in the 1930s with the publication of Kurt Gödel’s incompleteness Theorem. This Theorem essentially states that in any mathematical theory encompassing our traditional arithmetic systems, there are statements whose truth or falseness cannot be established by algorithmic means. In short, any complete study of our arithmetic systems lies beyond the capabilities of algorithm activities.

This realization shook the foundation of mathematics, and the study of algorithmic capabilities that ensued was the beginning of the field known today as Computer Science. Indeed, it is the study of algorithms that forms the core of Computer Science.

Computer Science Course

Rendy — Sat, 28 Nov 2009 14:37:28 +0000

Before we study even deeper it’s always good idea to know what we’re going to study and what we can expect to get by studying it. In this article we’re going to explore all Computer Science Course that you can learn from this website.

Data Storage
In this subject, we consider topics associated with data representation and the storage of data within a computer. The types of data we will consider including text, numeric values, images, audio, and video.
Data Manipulation
In this subject we will learn how a computers manipulates data and communicates with peripheral devices such as printers and keyboards. By learning this subject you can learn the basics of computer architecture and learn how computers are programmed by means of encoded instructions, called machine language instructions.
Operating Systems
In this subject we study operating systems, which are software packages that coordinate a computer’s internal activities as well as oversee its communication with the outside world. It is a computer’s operating system that transforms the computer hardware into a useful tool. The goal learning this subject is to understand what operating systems do and how they do it. Such a background is central to being an enlightened computer user.
Networking and the Internet
In this subject we fill find out the area of computer science known as networking, which encompasses the study of how computers can be linked together to share information and resources. We also going to study construction and operation of networks, applications of networks, and security issues. As a study case we going to use worldwide network knows as the internet.
Algorithms
As we study Computer Science we will learned that the central theme of Computer Science is the study of algorithms. When we reach this subjects it’s time for us to focus on this core topic. Our goal is to explore enough of this foundational material so that we can truly understand and appreciate the science of computing.
Programming Languages
In this subjects we study programming languages. We’re not going to learn all programming languages, that exist in universe. Rather than we going to learn about programming languages. Although I’ll put some programming languages example later on, our goal is to appreciate the commonality as well as the diversity among programming languages and their associated methodologies.
Software Engineering
In this subjects we explore the problems that are encountered during the development of large, complex software systems. The subjects is called Software Engineering because software development is an engineering process. The goal of researchers in software engineering is to find principles that guide the software development process and lead to efficient, reliable software products.
Data Abstractions
This subject will investigate how data arrangements other than the cell-by-cell organization provided by a computer’s main memory can be simulated – a subject known as data structures. The goal is to allow the data’s user to access collections of data as abstract tools rather than force the user to think in terms of the computer’s main memory organization. We will study how to construct such abstract tools to the concept of objects and object-oriented programming.
Database Systems
A database is a systems that converts a large collection of data into an abstract tool, allowing users to search for and extract pertinent items of information in a manner that is convenient to the user. In this chapter we explore this subject as well as take side excursions into the related fields of data mining, which seeks techniques for uncovering hidden patterns in large data collections, and traditional file structures, which provide many of the underlying today’s database and data mining systems.
Computer Graphics
Computer Graphics is the branch of computer science that applies computer technology to produce and manipulate visual representations. We going to explore a filed that is having major impact in the production of motion picture and interactive video games.
Artificial Intelligence
In this subject we explore the branch of computer science known as artificial intelligence. Although this field is relatively young, it has produced some astonishing breakthrough such as expert chess players, computer that appear to learn and reason, and machines that coordinate their activities a common goal. In Artificial Intelligence, everything that seems Science Fiction today’s may be reality for tomorrow’s.
Theory of Computation
This subject we will consider the theoretical foundations of computer science. In a sense, it is the material in this subject that gives computer science the status of a true science. Although somewhat abstract in nature, this body of knowledge has many very practical application. In particular, we will explore its implications regarding the power of programming languages and see how it leads to a public key encryption system that is widely used in communication over the internet.

Introduction to Computer Science and this website

Rendy — Fri, 27 Nov 2009 06:37:50 +0000

Computer Science (CS) is the discipline that seeks to build a scientific foundation for such topics as computer design, computer programming, information processing, algorithmic solutions of problems, and the algorithmic process itself. It provides the underpinnings for today’s computer application as well as the foundation for tomorrow’s applications.

CS is frequently described as the systematic study of algorithmic processes that create, describe, and transform information. Computer science has many sub-fields. For example: Computer Graphics (graphics that are created using computers and more generally, the representation and manipulation of pictorial data by computer), Artificial Intelligence (another branch of Computer Science that develops programs to allow machines to perform functions normally requiring human intelligence), and so on.

This website provides a comprehensive introduction to this science. We will learn all the subjects that introduced in Computer Science Curriculum. In addition to the Computer Science Topics itself, this website offers Computer Tips and Tricks that will help you during study and give books recommendation to support the Subjects being explained.

My goal is to establish a functional understanding of computer science for those who already interested in this field, and make this field more attractive for those occasional Internet users.

I’ll post everything categorised by their subjects for clean structure and easy finding. I’ll also post tags that may be related to the articles. So, for example I give a source code example of how login form made in PHP, so that means I’ll post that article in ‘Programming’ Categories and tag it with: PHP, Login Form, MySQL, Source Code.

I think that’s all for first Introduction. Stay tuned for more articles in Computer Science.