Computer science an overview 13th edition pdf download

Computer science an overview 13th edition pdf download

Computer science an overview 13th edition pdf download,Computer Science : An Overview by J. Glenn Brookshear (2011, Paperback)

Computer Science: An Overview (13th Edition) (What's New in Computer Science) by Glenn Brookshear, Dennis Brylow [PDF EBOOK EPUB MOBI Kindle] Computer Science: An Unformatted text preview: [PDF] Download Computer Science: An Overview (12th Edition) Read Online Download Ebook computer science an overview 12th edition in PDF Format email me at to get the ebook pdf ISBN ISBN X. Writing, and Literature Religion and Spirituality Science Tabletop Games Technology Travel. [PDF] It gives students an overview of computer science—a foundation from which they can appreciate the rele-vance and interrelationships of future courses in the field. This survey Unlike static PDF Computer Science: An Overview solution manuals or printed answer keys, our experts show you how to solve each problem step-by-step. No need to wait for office hours ... read more

Indeed, the flip-flop is only one of many circuits that are basic tools in computer engineering. Second, the concept of a flip-flop provides an example of abstraction and the use of abstract tools. Actually, there are other ways to build a flip-flop. One alternative is shown in Figure 1. If you experiment with this circuit, you will find that, although it has a different internal structure, its external properties are the same as those of Figure 1. A computer engineer does not need to know which circuit is actually used within a flip-flop.

A flipflop, along with other well-defined circuits, forms a set of building blocks from which an engineer can construct more complex circuitry. In turn, the design of computer circuitry takes on a hierarchical structure, each level of which uses the lower level components as abstract tools. The third purpose for introducing the flip-flop is that it is one means of storing a bit within a modern computer. More precisely, a flip-flop can be set to have the output value of either 0 or 1. Thus, many flip-flops, constructed as very small electrical circuits, can be used inside a computer as a means of recording information that is encoded as patterns of 0s and 1s. Indeed, technology known as very large-scale integration VLSI , which allows millions of electrical components to be constructed on a wafer called a chip , is used to create miniature devices containing millions of flip-flops along with their controlling circuitry.

Consequently, these chips are used as abstract tools in the construction of computer systems. In fact, in some cases VLSI is used to create an entire computer system on a single chip. Hexadecimal Notation When considering the internal activities of a computer, we must deal with patterns of bits, which we will refer to as a string of bits, some of which can be quite long. A long string of bits is often called a stream. Unfortunately, streams are difficult for the human mind to comprehend. Merely transcribing the pattern is tedious and error prone. To simplify the representation of such bit patterns, therefore, we usually use a shorthand notation called hexadecimal notation, which takes advantage of the fact that bit patterns within a machine Figure 1.

In particular, hexadecimal notation uses a single symbol to represent a pattern of four bits. For example, a string of twelve bits can be represented by three hexadecimal symbols. Figure 1. The left column displays all possible bit patterns of length four; the right column shows the symbol used in hexadecimal notation to represent the bit pattern to its left. Using this system, the bit pattern is represented as B5. This is obtained by dividing the bit pattern into substrings of length four and then representing each substring by its hexadecimal equivalent— is represented by B, and is represented by 5. In this manner, the bit pattern can be reduced to the more palatable form A4C8. We will use hexadecimal notation extensively in the next chapter. There you will come to appreciate its efficiency. What input bit patterns will cause the following circuit to produce an ­output of 1?

Inputs Output 2. In the text, we claimed that placing a 1 on the lower input of the flip-flop in Figure 1. Describe the sequence of events that occurs within the ­flip-flop in this case. Assuming that both inputs to the flip-flop in Figure 1. The symbol for a NAND gate is the same as an AND gate except that it has a circle at its output. The following is a circuit containing a NAND gate. What Boolean operation does the circuit compute? Input Input b. If the output of an OR gate is passed through a NOT gate, the combina- tion computes the Boolean operation called NOR that has an output of 1 only when both its inputs are 0. The symbol for a NOR gate is the same as an OR gate except that it has a circle at its output. The following is a circuit containing an AND gate and two NOR gates.

Input Output Input 5. Use hexadecimal notation to represent the following bit patterns: a. What bit patterns are represented by the following hexadecimal patterns? A string of eight bits is called a byte. Thus, a typical memory cell has a capacity of one byte. Although there is no left or right within a computer, we normally envision the bits within a memory cell as being arranged in a row. The left end of this row is called the high-order end, and the right end is called the low-order end. The leftmost bit is called either the high-order bit or the most significant bit in reference to the fact that if the contents of the cell were interpreted as representing a numeric value, this bit would be the most significant digit in the number. Similarly, the rightmost bit is referred to as the low-order bit or the least significant bit.

Thus we may represent the contents of a byte-size memory cell as shown in Figure 1. The system is analogous to the technique of identifying houses in a city by addresses. In the case of memory cells, however, the addresses used are entirely numeric. To be more precise, we envision all the cells being placed in a single row and numbered in this order starting with the value zero. Such an addressing system not only gives us a way of uniquely identifying each cell but also associates an order to the cells Figure 1. Pieces of this long row can therefore be used to store bit patterns that may be longer than the Figure 1. In particular, we can still store a string of 16 bits merely by using two consecutive memory cells. To complete the main memory of a computer, the circuitry that actually holds the bits is combined with the circuitry required to allow other circuits to store and retrieve data from the memory cells. In this way, other circuits can get data from the memory by electronically asking for the contents of a certain address called a read operation , or they can record information in the memory by requesting that a certain bit pattern be placed in the cell at a particular address called a write operation.

This random access feature of main memory is in stark contrast to the mass storage systems that we will discuss in the next section, in which long strings of bits are manipulated as amalgamated blocks. Although we have introduced flip-flops as a means of storing bits, the RAM in most modern computers is constructed using analogous, but more complex technologies that provide greater miniaturization and faster response time. Many of these technologies store bits as tiny electric charges that dissipate quickly. Thus these devices require additional circuitry, known as a refresh circuit, that repeatedly replenishes the charges many times a second. Measuring Memory Capacity As we will learn in the next chapter, it is convenient to design main memory systems in which the total number of cells is a power of two.

In turn, the size of the memories in early computers were often measured in which is cell units. Since is close to the value , the computing community adopted the prefix kilo in reference to this unit. That is, the term kilobyte abbreviated KB was used to refer to bytes. As memories became larger, this terminology grew to include MB megabyte , GB gigabyte , and TB terabyte. Unfortunately, this application of prefixes kilo-, mega-, and so on, represents a misuse of terminology because these are already used in other fields in reference to units that are powers of a thousand. For example, when measuring distance, kilometer refers to meters, and when measuring radio frequencies, ­megahertz refers to 1,, hertz. In the late s, international standards organizations developed specialized terminology for powers of two: kibi-, mebi-, gibi-, and tebi-bytes denote powers of , rather than powers of a thousand.

As a general rule, terms such as kilo-, mega-, etc. refer to powers of two when used in the context of computer measurements, but they refer to powers of a thousand when used in other contexts. If the memory cell whose address is 5 contains the value 8, what is the difference between writing the value 5 into cell number 6 and moving the contents of cell number 5 into cell number 6? Suppose you want to interchange the values stored in memory cells 2 and 3. What is wrong with the following sequence of steps: Step 1. Move the contents of cell number 2 to cell number 3. Move the contents of cell number 3 to cell number 2. Design a sequence of steps that correctly interchanges the contents of these cells.

If needed, you may use additional cells. How many bits would be in the memory of a computer with 4KB memory? The advantages of mass storage systems over main memory include less volatility, large storage capacities, low cost, and in many cases, the ability to remove the storage medium from the machine for archival purposes. Moreover, storage systems with moving parts are more prone to mechanical failures than solid state systems. Magnetic Systems For years, magnetic technology has dominated the mass storage arena. The most common example in use today is the magnetic disk or hard disk drive HDD , in which a thin spinning disk with magnetic coating is used to hold data ­Figure 1. Since a track can contain more information than we would normally want to manipulate at any one time, each track is divided into small arcs called sectors on which information is recorded as a continuous string of bits.

Thus, the bits within a sector on a track near the outer edge of the disk are less compactly stored than those on the tracks near the center, since the outer tracks are longer than the inner ones. In contrast, in high-capacity disk storage systems, the tracks near the outer edge are capable of containing significantly more sectors than those near the center, and this capability is often used by applying a technique called zoned-bit recording. Using zoned-bit recording, several adjacent tracks are collectively known as zones, with a typical disk containing approximately 10 zones. All tracks within a zone have the same number of sectors, but each zone has more sectors per track than the zone inside of it. In this manner, efficient use of the entire disk surface is achieved. Regardless of the details, a disk storage system consists of many individual sectors, each of which can be accessed as an independent string of bits.

The capacity of a disk storage system depends on the number of platters used and the density in which the tracks and sectors are placed. Lower-capacity systems may consist of a single platter. High-capacity disk systems, capable of holding many gigabytes, or even terabytes, consist of perhaps three to six platters mounted on a common spindle. Furthermore, data may be stored on both the upper and lower surfaces of each platter. A factor limiting the access time and transfer rate is the speed at which a disk system rotates. Thus, disk systems are typically housed in cases that are sealed at the factory. With this construction, disk systems are able to rotate at speeds of several hundred times per second, achieving transfer rates that are measured in MB per second. Since disk systems require physical motion for their operation, these systems suffer when compared to speeds within electronic circuitry. Delay times within an electronic circuit are measured in units of nanoseconds billionths of a second or less, whereas seek times, latency times, and access times of disk systems are measured in milliseconds thousandths of a second.

Thus the time required to retrieve information from a disk system can seem like an eternity to an electronic circuit awaiting a result. Magnetic storage technologies that are now less widely used include m ­ agnetic tape, in which information is recorded on the magnetic coating of a thin plastic tape wound on reels, and floppy disk drives, in which single platters with a magnetic coating are encased in a portable cartridge designed to be readily removed from the drive. Magnetic tape drives have extremely long seek times, just as their cousins, audio cassettes, suffer from long rewind and fast-forward times.

Low cost and high data capacities still make magnetic tape suitable for applications where data is primarily read or written linearly, such as archival data backups. The removable nature of floppy disk platters came at the cost of much lower data densities and access speeds than hard disk platters, but their portability was extremely valuable in earlier decades, prior to the arrival of flash drives with larger capacity and higher durability. Optical Systems Another class of mass storage systems applies optical technology. An example is the compact disk CD. These disks are 12 centimeters approximately 5 inches in diameter and consist of reflective material covered with a clear protective coating. Information is recorded on them by creating variations in their reflective surfaces. This information can then be retrieved by means of a laser that detects irregularities on the reflective surface of the CD as it spins. CD technology was originally applied to audio recordings using a recording format known as CD-DA compact disk-digital audio , and the CDs used today for computer data storage use essentially the same format.

In particular, information on these CDs is stored on a single track that spirals around the CD like a groove in an old-fashioned phonograph record, however, unlike old-fashioned phonograph records, the track on a CD spirals from the inside out Figure 1. Note that the distance around the spiraled track is greater toward the outer edge of the disk than at the inner portion. To maximize the capacity of a CD, information is stored at a uniform linear density over the entire spiraled track, which means that more information is stored in a loop around the outer portion of the spiral than in a loop around the inner portion. In turn, more sectors will be read in a single revolution of the disk when the laser is scanning the outer portion of the spiraled track than when the laser is scanning the inner portion of the track.

However, most CD systems used for computer data storage spin at a faster, constant speed and thus must accommodate variations in data transfer rates. As a consequence of such design decisions, CD storage systems perform best when dealing with long, continuous strings of data, as when reproducing music. In contrast, when an application requires access to items of data in a random manner, the approach used in magnetic disk storage individual, concentric tracks divided into individually accessible sectors outperforms the spiral approach used in CDs. Traditional CDs have capacities in the range of to MB. However, DVDs Digital Versatile Disks , which are constructed from multiple, semitransparent layers that serve as distinct surfaces when viewed by a precisely focused laser, provide storage capacities of several GB. Such disks are capable of storing lengthy multimedia presentations, including entire motion pictures.

Finally, Blu-ray technology, which uses a laser in the blue-violet spectrum of light instead of red , is able to focus its laser beam with very fine precision. As a result, BDs Blu-ray Disks provides over five times the capacity of a DVD. This seemingly vast amount of storage is needed to meet the demands of high definition video. This means that data storage and retrieval is slow compared to the speed of electronic circuitry. Flash memory technology has the potential of alleviating this drawback. In a flash memory system, bits are stored by sending electronic signals directly to the storage medium where they cause electrons to be trapped in tiny chambers of silicon dioxide, thus altering the characteristics of small electronic circuits.

Since these chambers are able to hold their captive electrons for many years without external power, this technology is excellent for portable, nonvolatile data storage. Moreover, repeated erasing slowly damages the silicon dioxide chambers, meaning that current flash memory technology is not suitable for general main memory applications where its contents might be altered many times a second. However, in those applications in which alterations can be controlled to a reasonable level, such as in digital cameras and smartphones, flash memory has become the mass storage technology of choice. Indeed, since flash memory is not sensitive to physical shock in contrast to magnetic and optic systems , it is now replacing other mass storage technologies in portable applications such as laptop computers.

Flash memory devices called flash drives, with capacities of hundreds of GBs, are available for general mass storage applications. The high capacity of these portable units as well as the fact that they are easily connected to and disconnected from a computer make them ideal for portable data storage. However, the vulnerability of their tiny storage chambers dictates that they are not as reliable as optical disks for truly long-term applications. Larger flash memory devices called SSDs solid-state disks are explicitly designed to take the place of magnetic hard disks. SSDs compare favorably to hard disks in their resilience to vibrations and physical shock, their quiet operation due to no moving parts , and their lower access times. SSDs remain more expensive than hard disks of comparable size and thus are still considered a high-end option when buying a computer.

SSD sectors suffer from the more limited lifetime of all flash memory technologies, but the use of wear-leveling techniques can reduce the impact of this by relocating frequently altered data blocks to fresh locations on the drive. Another application of flash technology is found in SD Secure Digital memory cards or just SD Card. These provide up to two GBs of storage and are packaged in a plastic rigged wafer about the size a postage stamp SD cards are also available in smaller mini and micro sizes , SDHC High Capacity memory cards can provide up to 32 GBs and the next generation SDXC Extended Capacity memory cards may exceed a TB. Given their compact physical size, these cards conveniently slip into slots of small electronic devices. Thus, they are ideal for digital cameras, smartphones, music players, car navigation systems, and a host of other electronic appliances. What is gained by increasing the rotation speed of a disk or CD? When recording data on a multiple-disk storage system, should we fill a complete disk surface before starting on another surface, or should we first fill an entire cylinder before starting on another cylinder?

Why should the data in a reservation system that is constantly being updated be stored on a magnetic disk instead of a CD or DVD? What factors allow CD, DVD, and Blu-ray disks all to be read by the same drive? What advantage do flash drives have over the other mass storage systems introduced in this section? What advantages continue to make magnetic hard disk drives competitive? Our study focuses on popular methods for encoding text, numerical data, images, and sound. Each of these systems has repercussions that are often visible to a typical computer user. Our goal is to understand enough about these techniques so that we can recognize their consequences for what they are. Representing Text Information in the form of text is normally represented by means of a code in which each of the different symbols in the text such as the letters of the alphabet and punctuation marks is assigned a unique bit pattern.

The text is then represented as a long string of bits in which the successive patterns represent the successive symbols in the original text. In the s and s, many such codes were designed and used in connection with different pieces of equipment, producing a corresponding proliferation of communication problems. This code uses bit patterns of length seven to represent the upper- and lowercase letters of the English alphabet, punctuation symbols, the digits 0 through 9, and certain control information such as line feeds, carriage returns, and tabs. ASCII is extended to an eight-bit-per-symbol format by adding a 0 at the most significant end of each of the seven-bit patterns. This technique not only produces a code in which each pattern fits conveniently into a typical byte-size memory cell but also provides additional bit patterns those obtained by assigning the extra bit the value 1 that can be used to represent symbols beyond the English alphabet and associated punctuation.

A portion of ASCII in its eight-bit-per-symbol format is shown in Appendix A. The International Organization for Standardization also known as ISO, in reference to the Greek word isos, meaning equal has developed a number of extensions to ASCII, each of which was designed to accommodate a major language group. For example, one standard provides the symbols needed to express the text of most Western European languages. Included in its additional patterns are symbols for the British pound and the German vowels ä, ö, and ü. First, the number of extra bit patterns available in extended ASCII is simply insufficient to accommodate the alphabet of many Asian and some Eastern European languages. Second, because a given document was constrained to using symbols in just the one selected standard, documents containing text of languages from disparate language groups could not be supported.

Both proved to be a significant detriment to international use. To address this deficiency, Unicode was developed through the cooperation of several of the leading manufacturers of hardware and software and has rapidly gained the support of the computing community. This code uses a unique pattern of up to 21 bits to represent each symbol. When the Unicode character set is combined with the Unicode Transformation Format 8-bit UTF-8 encoding standard, the original ASCII characters can still be represented with 8 bits, while the thousands of additional characters from such languages as Chinese, Japanese, and Hebrew can be represented by 16 bits. A file consisting of a long sequence of symbols encoded using ASCII or Unicode is often called a text file.

Both consist of textual material. However, a text file contains only a character-by-character encoding of the text, whereas a file produced by a word processor contains numerous proprietary codes representing changes in fonts, alignment information, and other parameters. Representing Numeric Values Storing information in terms of encoded characters is inefficient when the information being recorded is purely numeric. To see why, consider the problem of storing the value If we insist on storing it as encoded symbols in ASCII using one byte per symbol, we need a total of 16 bits.

Moreover, the largest number we could store using 16 bits is However, as we will shortly see, by using binary notation we can store any integer in the range from 0 to in these 16 bits. Thus, binary notation or variations of it is used extensively for encoded numeric data for computer storage. Binary notation is a way of representing numeric values using only the digits 0 and 1 rather than the digits 0, 1, 2, 3, 4, 5, 6, 7, 8, and 9 as in the traditional decimal, or base 10, system. We will study the binary system more thoroughly in Section 1. For now, all we need is an elementary understanding of the system. Today, ANSI membership includes more than businesses, professional organizations, trade associations, and government agencies.

ANSI is headquartered in New York and represents the United States as a member body in the ISO. Similar organizations in other countries include Standards Australia Australia , Standards Council of Canada Canada , China State Bureau of Quality and Technical Supervision China , Deutsches Institut für Normung Germany , Japanese ­Industrial Standards Committee Japan , Dirección General de Normas Mexico , State C ­ ommittee of the Russian Federation for Standardization and Metrology Russia , Swiss Association for Standardization Switzerland , and British Standards Institution United Kingdom. contain only the digits 0 and 1 rather than the traditional digits 0 through 9. The odometer starts with a reading of all 0s, and as the car is driven for the first few miles, the rightmost wheel rotates from a 0 to a 1. Then, as that 1 rotates back to a 0, it causes a 1 to appear to its left, producing the pattern The 0 on the right then rotates to a 1, producing Now the rightmost wheel rotates from 1 back to 0, causing the 1 to its left to rotate to a 0 as well.

This in turn causes another 1 to appear in the third column, producing the pattern In short, as we drive the car we see the following sequence of odometer readings: This sequence consists of the binary representations of the integers zero through eight. Although tedious, we could extend this counting technique to discover that the bit pattern consisting of 16 1s represents the value , which confirms our claim that any integer in the range from 0 to can be encoded using 16 bits. Due to this efficiency, it is common to store numeric information in a form of binary notation rather than in encoded symbols. Some of these variations of the binary system are discussed later in this chapter. Such a collection is called a bit map.

This approach is popular because many display devices, such as printers and display screens, operate on the pixel concept. In turn, images in bit map form are easily formatted for display. The method of encoding the pixels in a bit map varies among applications. In the case of a simple black-and-white image, each pixel can be represented by a single bit whose value depends on whether the corresponding pixel is black or white. This is the approach used by most facsimile machines. For more elaborate black-and-white photographs, each pixel can be represented by a collection of bits usually eight , which allows a variety of shades of grayness to be represented. In the case of color images, each pixel is encoded by more complex system.

Two approaches are common. In one, which we will call RGB encoding, each pixel is represented as three color components—a red component, a green component, and a blue component—corresponding to the three primary colors of light. One byte is normally used to represent the intensity of each color component. In turn, three bytes of storage are required to represent a single pixel in the original image. Actually, it is considered to be the amount of white light in the pixel, but these details need not concern us here. Together these three components contain the information required to reproduce the pixel. The popularity of encoding images using luminance and chrominance components originated in the field of color television broadcast because this approach provided a means of encoding color images that was also compatible with older black-and-white television receivers.

Indeed, a gray-scale version of an image can be produced by using only the luminance components of the encoded color image. Today, it is headquartered in Geneva, Switzerland, and has more than member bodies as well as numerous correspondent members. A ­correspondent member is usually a standardization body from a country that does not have a ­nationally recognized standardization body. Such members cannot participate directly in the development of standards but are kept informed of ISO activities. Essentially, the only way to enlarge the image is to make the pixels bigger, which leads to a grainy appearance. An alternate way of representing images that avoids this scaling problem is to describe the image as a collection of geometric structures, such as lines and curves, that can be encoded using techniques of analytic geometry.

Such a description allows the device that ultimately displays the image to decide how the geometric structures should be displayed rather than insisting that the device reproduce a particular pixel pattern. For example, TrueType developed by Microsoft and Apple is a system for geometrically describing text symbols. Likewise, PostScript developed by Adobe Systems provides a means of describing characters as well as more general pictorial data. This geometric means of representing images is also popular in computer-aided design CAD systems in which drawings of three-dimensional objects are displayed and manipulated on computer display screens.

The user simply selects the desired geometric shape from a menu and then directs the drawing of that shape via a mouse. During the drawing process, the software maintains a geometric description of the shape being drawn. As directions are given by the mouse, the internal geometric representation is modified, reconverted to bit map form, and displayed. This allows for easy scaling and shaping of the image. Once the drawing process is complete, however, the underlying geometric description is discarded and only the bit map is preserved, meaning that additional alterations require a tedious pixel-by-pixel modification process. On the other hand, some drawing systems preserve the description as geometric shapes that can be modified later. With these systems, the shapes can be easily resized, maintaining a crisp display at any dimension.

Representing Sound The most generic method of encoding audio information for computer storage and manipulation is to sample the amplitude of the sound wave at regular intervals and record the series of values obtained. For instance, the series 0, 1. This technique, using a sample rate of samples per second, has been used for years in long-distance voice telephone communication. The voice at one end of the communication is encoded as numeric values representing the amplitude of the voice every eight-thousandth of a second. These numeric values are then transmitted over the communication line to the receiving end, where they are used to reproduce the sound of the voice. Although samples per second may seem to be a rapid rate, it is not sufficient for high-fidelity music recordings. The data obtained from each sample are represented in 16 bits 32 bits for stereo recordings.

Consequently, each second of music recorded in stereo requires more than a million bits. By encoding directions for producing music on a synthesizer rather than encoding the sound itself, MIDI avoids the large storage requirements of the sampling technique. More precisely, MIDI encodes what instrument is to play which note for what duration of time, which means that a clarinet playing the note D for two seconds can be encoding in three bytes rather than more than two million bits when sampled at a rate of 44, samples per second.

Here is a message encoded in ASCII using 8 bits per symbol. What does it say? See Appendix A 2. In the ASCII code, what is the relationship between the codes for an uppercase letter and the same letter in lowercase? See Appendix A. Encode these sentences in ASCII: a. Describe a device from everyday life that can be in either of two states, such as a flag on a flagpole that is either up or down. Assign the symbol 1 to one of the states and 0 to the other, and show how the ASCII representation for the letter b would appear when stored with such bits. Convert each of the following binary representations to its equivalent base 10 form: a.

Convert each of the following base 10 representations to its equivalent binary form: a. What is the largest numeric value that could be represented with three bytes if each digit were encoded using one ASCII pattern per byte? What if binary notation were used? An alternative to hexadecimal notation for representing bit patterns is ­dotted decimal notation in which each byte in the pattern is represented by its base 10 equivalent. In turn, these byte representations are separated by periods. For example, Represent each of the following bit patterns in dotted decimal notation. What is an advantage of representing images via geometric structures as opposed to bit maps? What about bit map techniques as opposed to geometric structures? Suppose a stereo recording of one hour of music is encoded using a sam- ple rate of 44, samples per second as discussed in the text. How does the size of the encoded version compare to the storage capacity of a CD?

It is time now to look at binary notation more thoroughly. In the representation , the 5 is in the position associated with the quantity one, the 7 is in the position associated with ten, and the 3 is in the position associated with the quantity one hundred Figure 1. Each quantity is 10 times that of the quantity to its right. The position of each digit in binary notation is also associated with a quantity, except that the quantity associated with each position is twice the quantity associated with the position to its right. More precisely, the rightmost digit in a binary representation is associated with the quantity one 20 , the next position to the left is associated with two 21 , the next is associated with four 22 , the next with eight 23 , and so on. For example, in the binary representation , the rightmost 1 is in the position associated with the quantity one, the 1 next to it is in the position associated with two, the 0 is in the position associated with four, and the leftmost 1 is in the position associated with eight Figure 1.

To extract the value represented by a binary representation, we follow the same procedure as in base 10—we multiply the value of each digit by the quantity associated with its position and add the results. For example, the value represented by is 37, as shown in Figure 1. Note that since binary notation uses only the digits 0 and 1, this multiply-and-add process reduces merely to adding the quantities associated with the positions occupied by 1s. Thus the binary pattern represents the value eleven, because the 1s are found in the positions associated with the quantities one, two, and eight. In Section 1. For finding binary representations of large values, you may prefer the approach described by the algorithm in Figure 1. Let us apply this algorithm to the value thirteen Figure 1. We first divide thirteen by two, obtaining a quotient of six and a remainder of one.

Since the quotient was not zero, Step 2 tells us to divide the quotient six by two, obtaining a new quotient of three and a remainder of zero. The newest quotient is still not zero, so we divide it by two, obtaining a quotient of one and a remainder of one. Once again, we divide the newest quotient one by two, this time obtaining a quotient of zero and a remainder of one. Since we have now acquired a quotient of zero, we move on to Step 3, where we learn that the binary representation of the original value thirteen is , obtained from the list of remainders. Base two system Eig a. Divide the value by two and record the remainder. As long as the quotient obtained is not zero, continue to divide the newest quotient by two and record the remainder. Now that a quotient of zero has been obtained, the binary representation of the original value consists of the remainders listed from right to left in the order they were recorded.

To add two integers represented in binary notation, we follow the same procedure except that all sums are computed using the addition facts shown in ­Figure 1. Now we add the 1 and 1 from the next column, obtaining We write the 0 from this 10 under the column and carry the 1 to the top of the next column. The 1 and 1 from the next column total 10; we write the 0 under the column and carry the 1 to the next column. We add that 1 to the 1 already in that column to obtain Again, we record the low-order 0 and carry the 1 to the next column. That is, the digits to the left of the point represent the integer part whole part of the value and are interpreted as in the binary system discussed previously. The digits to its right represent the fractional part of the value and are interpreted in a manner similar to the other bits, except their positions are assigned fractional quantities. Note that this is merely a continuation of the rule stated previously: Each position is assigned a quantity twice the size of the one to its right.

With these quantities assigned to the bit positions, decoding a binary representation containing a radix point requires the same procedure as used without a radix point. To illustrate, the binary representation For addition, the techniques applied in the base 10 system are also applicable in binary. That is, to add two binary representations having radix points, we Figure 1. In a digital system, a value is encoded as a series of digits and then stored using several devices, each representing one of the digits. In an analog system, each value is stored in a single device that can represent any value within a continuous range. Let us compare the two approaches using buckets of water as the storage devices. To simulate a digital system, we could agree to let an empty bucket represent the digit 0 and a full bucket represent the digit 1.

Then we could store a numeric value in a row of buckets using floating-point notation see Section 1. In contrast, we could simulate an analog system by partially filling a single bucket to the point at which the water level represented the numeric value being represented. At first glance, the analog system may appear to be more accurate since it would not suffer from the truncation errors inherent in the digital system again see Section 1. However, any movement of the bucket in the analog system could cause errors in detecting the water level, whereas a significant amount of sloshing would have to occur in the digital system before the distinction between a full bucket and an empty bucket would be blurred.

Thus the digital system would be less sensitive to error than the analog system. This robustness is a major reason why many applications that were originally based on analog technology such as telephone communication, audio recordings, and television are shifting to digital technology. merely align the radix points and apply the same addition process as before. Express the following values in binary notation: a. Perform the following additions in binary notation: a. These systems are based on the binary system but have additional properties that make them more compatible with computer design.

With these advantages, however, come disadvantages as well. Our goal is to understand these properties and how they affect computer usage. This system uses a fixed number of bits to represent each of the values in the system. Such a large system allows a wide range of numbers to be represented but is awkward for demonstration purposes. Such a system is constructed by starting with a string of 0s of the appropriate length and then counting in binary until the pattern consisting of a single 0 followed by 1s is reached. These patterns represent the values 0, 1, 2, 3,. The patterns representing negative values are obtained by starting with a string of 1s of the appropriate length and then counting backward in binary until the pattern consisting of a single 1 followed by 0s is reached. These patterns represent the values -1, -2, -3,. If counting backward in binary is difficult for you, merely start at the very bottom of the table with the pattern consisting of a single 1 followed by 0s, and count up to the pattern consisting of all 1s.

Thus, the leftmost bit is often called the sign bit. They are identical when read from right to left, up to and including the first 1. From there on, the patterns are complements of one another. The complement of a pattern is the pattern obtained by changing all the 0s to 1s and all the 1s to 0s; and are complements. For example, in the 4-bit system in Figure 1. Using patterns of length three Bit pattern b. Using patterns of length four Value represented Bit pattern 3 2 1 0 -1 -2 -3 -4 Value represented 7 6 5 4 3 2 1 0 -1 -2 -3 -4 -5 -6 -7 -8 the patterns representing 2 and -2 both end with 10, but the pattern representing 2 begins with 00, whereas the pattern representing -2 begins with This observation leads to an algorithm for converting back and forth between bit patterns representing positive and negative values of the same magnitude.

We merely copy the original pattern from right to left until a 1 has been copied, then we complement the remaining bits as they are transferred to the final bit pattern Figure 1. If the pattern Figure 1. For example, represents the value 6, because is binary for 6. If the pattern to be decoded has a sign bit of 1, we know the value represented is negative, and all that remains is to find the magnitude of the value. For example, to decode the pattern , we first recognize that since the sign bit is 1, the value represented is negative. With this understanding, consider the three addition problems in Figure 1. Observe that the third problem in Figure 1. This is in stark contrast to how humans traditionally perform arithmetic computations. Such circuits are shown and explained in Appendix B.

In fact, the result would appear as This phenomenon is called overflow. That is, overflow is the problem that occurs when a computation produces a value that falls outside the range of values that can be represented. In either case, the condition can be detected by checking the sign bit of the answer. Melanie Curtis's Ownd. Computer science an overview 13th edition pdf download. R The Game of Life. The 13th Edition continues its focus on Python to provide programming tools for exploration and experimentation. A new full-color design reflects the use of color in most modern programming interfaces to aid the programmer's download pdf computer science an overview 11th edition solutions.

co 1 File Size: KB. Software ownership and liability: You have successfully signed out and will be required to sign back in should you need to download more resources. Best Selling in Textbooks, Education See all. Chapter 3 Operating Systems 3. Chapter 1 Data Storage 19 1. The lowest-priced item in unused and unworn condition with absolutely no signs of wear. Chapter-by-chapter activities that extend topics in the text and provide opportunities to explore related topics. Chapter 7 Software Engineering 7. An Overview uses broad coverage and clear exposition to present a complete picture of the dynamic computer science field. The material in Chapter 7 Software Engineering pertaining to this topic has been rewritten and updated. This website uses cookies to improve your experience while you navigate through the website. Out of these cookies, the cookies that are categorized as necessary are stored on your browser as they are as essential for the working of basic functionalities of the website.

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For the Introduction to Computer Science course. A broad exploration of computer science—with the depth needed to unde. English Pages [] Year DOWNLOAD FILE. In this language-independent book, J. Glenn Brookshear provides accurate and balanced coverage of a variety of topics, p. Named a Notable Book in the 21st Annual Best of Computing list by the ACM! Robert Sedgewick and Kevin Wayne'sCompu. For coursesin Business Data Communication and Networking. Anintroduction to computer networking grounded in real-worl. For courses in Business Data Communication and Networking.

An introduction to computer networking grounded in real-wo. This book provides a systematic and comprehensive overview of a subject that every thoughtful person wants to understand. Table of contents : Front Cover Title Page Copyright Page Dedication Page Contents Preface Page Acknowledgment Page Chapter 0 Introduction 0. This is a special edition of an established title widely used by colleges and universities throughout the world. Pearson published this exclusive edition for the benefit of students outside the United States and Canada. If you purchased this book within the United States or Canada, you should be aware that it has been imported without the approval of the Publisher or Author.

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Oh, the places you will go. It explores the breadth of the subject while including enough depth to convey an honest appreciation of the topics involved. Audience We wrote this text for students of computer science as well as students from other disciplines. As for computer science students, most begin their studies with the illusion that computer science is programming, web browsing, and Internet file sharing because that is essentially all they have seen. Yet computer science is much more than this. Beginning computer science students need exposure to the breadth of the subject in which they are planning to major. It gives students an overview of computer science—a foundation from which they can appreciate the relevance and ­interrelationships of future courses in the field.

This survey approach is, in fact, the model used for introductory courses in the natural sciences. This broad background is also what students from other disciplines need if they are to relate to the technical society in which they live. A ­computer science course for this audience should provide a practical, realistic ­understanding of the entire field rather than merely an introduction to using the Internet or training in the use of some popular software packages. There is, of course, a proper place for that training, but this text is about educating. While writing previous editions of this text, maintaining accessibility for nontechnical students was a major goal. The result was that the book has been used successfully in courses for students over a wide range of disciplines and educational levels, ranging from high school to graduate courses.

This 13th edition is designed to continue that tradition. New in the 13th Edition Now in color! The move to a full color printing process in the 13th edition has allowed us to make many figures and diagrams more descriptive, and to use syntax coloring to better effect for clarifying code and pseudocode segments in the text. While the primary audience for this book remains college-level introductory courses, this edition explicitly calls out many points of intersection with CSP content to better assist students and instructors either preparing for the AP® CSP exam, or taking a college-level course that is intended to correspond with the credit from that exam.

The 13th edition continues the use of Python code examples and Pythonlike pseudocode adopted in the 12th edition. We made this change for several reasons. First, the text already contains quite a bit of code in various languages, including detailed pseudocode in several chapters. To the extent that readers are already absorbing a fair amount of syntax, it is appropriate to target that syntax toward a language they may actually see in a subsequent course. More importantly, a growing number of instructors who use this text have made the determination that even in a breadth-first introduction to computing, it is difficult for students to master many of the topics in the absence of programming tools for exploration and experimentation.

But why Python? Choosing a language is always a contentious matter, with any choice bound to upset at least as many as it pleases. It is a mature language with a vibrant development community and copious online resources for further study. Python remains one of the top five most commonly used languages in the industry by some measures, and has seen a sharp increase in its usage for introductory computer science courses. It is particularly popular for introductory courses for non-majors, and has wide acceptance in other STEM fields, such as physics and biology, and as the language of choice for computational science applications.

Nevertheless, the focus of the text remains on broad computer science ­concepts; the Python supplements are intended to give readers a deeper taste of programming than previous editions, but not to serve as a full-fledged introduction to programming. The Python topics covered are driven by the existing structure of the text. Thus, Chapter 1 touches on Python syntax for representing data—integers, floats, ASCII, and Unicode strings. Chapter 2 touches on Python operations that closely mirror the machine primitives discussed throughout the rest of the chapter.

Conditionals, loops, and functions are introduced in Chapter 5, at the time that those constructs are needed to devise a sufficiently complete pseudocode for describing algorithms. In short, Python constructs are used to reinforce computer science concepts rather than to hijack the conversation. Every chapter has seen revisions, updates, and corrections from the previous editions. Organization Organization This text follows a bottom-up arrangement of subjects that progresses from the concrete to the abstract—an order that results in a sound pedagogical presentation in which each topic leads to the next.

It begins with the fundamentals of information encoding, data storage, and computer architecture Chapters 1 and 2 ; progresses to the study of operating systems Chapter 3 and computer networks Chapter 4 ; investigates the topics of algorithms, programming languages, and software development Chapters 5 through 7 ; explores techniques for enhancing the accessibility of information Chapters 8 and 9 ; considers some major applications of computer technology via graphics Chapter 10 and artificial intelligence Chapter 11 ; and closes with an ­introduction to the abstract theory of computation Chapter Although the text follows this natural progression, the individual chapters and sections are surprisingly independent and can usually be read as isolated units or rearranged to form alternative sequences of study.

Indeed, the book is often used as a text for courses that cover the material in a variety of orders. One of these alternatives begins with material from Chapters 5 and 6 Algorithms and Programming Languages and returns to the earlier chapters as desired. I also know of one course that starts with the material on computability from Chapter Courses for less technically oriented audiences may want to concentrate on Chapters 4 Networking and the Internet , 9 Database Systems , 10 Computer Graphics , and 11 Artificial Intelligence. On the opening page of each chapter, we have used asterisks to mark some sections as optional. These are sections that cover topics of more specific interest, or perhaps explore traditional topics in more depth. Our intention is merely to provide suggestions for alternative paths through the text. There are, of course, other shortcuts.

In particular, if you are looking for a quick read, we suggest the following sequence: Section 1. One is that com­ puter science is dynamic. The text repeatedly presents topics in a historical 9 10 Preface perspective, discusses the current state of affairs, and indicates directions of research. Another theme is the role of abstraction and the way in which abstract tools are used to control complexity. This theme is introduced in Chapter 0 and then echoed in the context of operating system architecture, networking, algorithm development, programming language design, software engineering, data organization, and computer graphics.

To Instructors There is more material in this text than students can normally cover in a single semester, so do not hesitate to skip topics that do not fit your course ­objectives or to rearrange the order as you see fit. You will find that, although the text follows a plot, the topics are covered in a largely independent manner that allows you to pick and choose as you desire. The book is designed to be used as a course resource—not as a course definition. We suggest encouraging ­students to read the material not explicitly included in your course. We ­underrate students if we assume that we have to explain everything in class. We should be helping them learn to learn on their own. We feel obliged to say a few words about the bottom-up, concreteto-abstract organization of the text.

As academics, we too often assume that students will appreciate our perspective of a subject—often one that we have developed over many years of working in a field. These are topics to which students readily relate—they have most likely heard terms such as JPEG and MP3; they have probably recorded data on DVDs and flash drives; they have interacted with an operating system; and they use the Internet and smartphones daily. From this beginning, it is natural to move on to the more abstract issues of algorithms, algorithmic structures, programming languages, software development methodologies, computability, and complexity, that those of us in the field view as the main topics in the science.

As already stated, the topics are presented in a manner that does not force you to follow this bottom-up sequence, but we encourage you to give it a try. We are all aware that students learn a lot more than we teach them directly, and the lessons they learn implicitly are often better absorbed than those that are studied explicitly. Students do not become problem solvers by studying problem-solving methodologies. We encourage you to use these and to expand on them. We do not believe that this material should be presented as an isolated subject that is merely tacked on to the course. Instead, it should be an integral part of the coverage that surfaces when it is relevant.

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Computer science an overview 13th edition download * Asterisks indicate suggestions for optional sections Introduction The Role of Algorithms The History of Computing An It gives students an overview of computer science—a foundation from which they can appreciate the rele-vance and interrelationships of future courses in the field. This survey Unformatted text preview: [PDF] Download Computer Science: An Overview (12th Edition) Read Online Download Ebook computer science an overview 12th edition in PDF Format Unformatted text preview: [PDF] Download Computer Science: An Overview (12th Edition) Read Online Download Ebook computer science an overview 12th edition in PDF Format Computer science an overview 13th edition download * Asterisks indicate suggestions for optional sections Introduction The Role of Algorithms The History of Computing An Networking, OS, Computer Architecture, Algorithms provides students with a general level of proficiency for future courses. An Overview uses broad coverage and clear exposition to ... read more

Optical Systems Another class of mass storage systems applies optical technology. You should also consider why you answered as you did and whether your justifications are consistent from one question to the next. Cambridge, MA: The MIT Press, Announce that you have selected some red cards and some black cards. Although machines normally use much longer patterns, this 8-bit format is representative of actual systems and serves to demonstrate the important concepts without the clutter of long bit patterns.

Finally, the 1 from the AND gate keeps the OR gate from changing after the upper input returns to 0. Next, computer science an overview 13th edition pdf download, we observe that the first pattern with a 1 as its most significant bit appears approximately halfway through the list. Would the employees be unfairly treated? We feel obliged to say a few words about the bottom-up, concreteto-abstract organization of the text. In each chapter, our goal is to explore the subject deeply enough to enable true understanding. More precisely, MIDI encodes what instrument is to play which note for what duration of time, which means that a clarinet playing the note D for two seconds can be encoded in three bytes rather than the over two million bits when sampled at a rate of 44, samples per second.