First we must define what
really is a computer game.
Is it a computer game? Is it solely a computer game? Is it also both a computer and console game? Is Football Manager a computer game? If so, is MS Excel a computer game? Games are solely for entertainment, therefore if one's computer is solely an entertainment, is a computer a computer game?
Conventionally, a computer consists of at least one processing element, typically a central processing unit (CPU) and some form of memory. The processing element carries out arithmetic and logic operations, and a sequencing and control unit that can change the order of operations based on stored information. Peripheral devices allow information to be retrieved from an external source, and the result of operations saved and retrieved.
Modern computers based on integrated circuits are millions to billions of times more capable than the early machines, and occupy a fraction of the space. Simple computers are small enough to fit into mobile devices, and mobile computers can be powered by small batteries. Personal computers in their various forms are icons of the Information Age and are what most people think of as “computers.” However, the embedded computers found in many devices from MP3 players to fighter aircraft and from toys to industrial robots are the most numerous.
The first use of the word “computer” was recorded in 1613 in a book called “The yong mans gleanings” by English writer Richard Braithwait I haue read the truest computer of Times, and the best Arithmetician that euer breathed, and he reduceth thy dayes into a short number. It referred to a person who carried out calculations, or computations, and the word continued with the same meaning until the middle of the 20th century. From the end of the 19th century the word began to take on its more familiar meaning, a machine that carries out computations.
The history of the modern computer begins with two separate technologies, automated calculation and programmability. However no single device can be identified as the earliest computer, partly because of the inconsistent application of that term. A few devices are worth mentioning though, like some mechanical aids to computing, which were very successful and survived for centuries until the advent of the electronic calculator, like the Sumerian abacus, designed around 2500 BC of which a descendant won a speed competition against a modern desk calculating machine in Japan in 1946, the slide rules, invented in the 1620s, which were carried on five Apollo space missions, including to the moon and arguably the astrolabe and the Antikythera mechanism, an ancient astronomical analog computer built by the Greeks around 80 BC. The Greek mathematician Hero of Alexandria (c. 10–70 AD) built a mechanical theater which performed a play lasting 10 minutes and was operated by a complex system of ropes and drums that might be considered to be a means of deciding which parts of the mechanism performed which actions and when. This is the essence of programmability.
Blaise Pascal invented the mechanical calculator in 1642, known as Pascal's calculator, it was the first machine to better human performance of arithmetical computations and would turn out to be the only functional mechanical calculator in the 17th century. Two hundred years later, in 1851, Thomas de Colmar released, after thirty years of development, his simplified arithmometer; it became the first machine to be commercialized because it was strong enough and reliable enough to be used daily in an office environment. The mechanical calculator was at the root of the development of computers in two separate ways. Initially, it was in trying to develop more powerful and more flexible calculators that the computer was first theorized by Charles Babbage and then developed. Secondly, development of a low-cost electronic calculator, successor to the mechanical calculator, resulted in the development by Intel of the first commercially available microprocessor integrated circuit.
In 1801, Joseph Marie Jacquard made an improvement to the textile loom by introducing a series of punched paper cards as a template which allowed his loom to weave intricate patterns automatically. The resulting Jacquard loom was an important step in the development of computers because the use of punched cards to define woven patterns can be viewed as an early, albeit limited, form of programmability.
It was the fusion of automatic calculation with programmability that produced the first recognizable computers. In 1837, Charles Babbage was the first to conceptualize and design a fully programmable mechanical computer, his analytical engine. Limited finances and Babbage's inability to resist tinkering with the design meant that the device was never completed—nevertheless his son, Henry Babbage, completed a simplified version of the analytical engine's computing unit (the mill) in 1888. He gave a successful demonstration of its use in computing tables in 1906. This machine was given to the Science museum in South Kensington in 1910.
Between 1842 and 1843, Ada Lovelace, an analyst of Charles Babbage's analytical engine, translated an article by Italian military engineer Luigi Menabrea on the engine, which she supplemented with an elaborate set of notes of her own, simply called Notes. These notes contain what is considered the first computer program – that is, an algorithm encoded for processing by a machine. Lovelace's notes are important in the early history of computers. She also developed a vision on the capability of computers to go beyond mere calculating or number-crunching while others, including Babbage himself, focused only on those capabilities.
During the first half of the 20th century, many scientific computing needs were met by increasingly sophisticated analog computers, which used a direct mechanical or electrical model of the problem as a basis for computation. However, these were not programmable and generally lacked the versatility and accuracy of modern digital computers.
Alan Turing is widely regarded as the father of modern computer science. In 1936, Turing provided an influential formalization of the concept of the algorithm and computation with the Turing machine, providing a blueprint for the electronic digital computer. Of his role in the creation of the modern computer, Time magazine in naming Turing one of the 100 most influential people of the 20th century, states: “The fact remains that everyone who taps at a keyboard, opening a spreadsheet or a word-processing program, is working on an incarnation of a Turing machine.”.
The Atanasoff–Berry Computer (ABC) was the world's first electronic digital computer, albeit not programmable. Atanasoff is considered to be one of the fathers of the computer. Conceived in 1937 by Iowa State College physics professor John Atanasoff, and built with the assistance of graduate student Clifford Berry, the machine was not programmable, being designed only to solve systems of linear equations. The computer did employ parallel computation. A 1973 court ruling in a patent dispute found that the patent for the 1946 ENIAC computer derived from the Atanasoff–Berry Computer.
The first program-controlled computer was invented by Konrad Zuse, who built the Z3, an electromechanical computing machine, in 1941. The first programmable electronic computer was the Colossus, built in 1943 by Tommy Flowers.
George Stibitz is internationally recognized as a father of the modern digital computer. While working at Bell Labs in November 1937, Stibitz invented and built a relay-based calculator he dubbed the “Model K” (for “kitchen table,” on which he had assembled it), which was the first to use binary circuits to perform an arithmetic operation. Later models added greater sophistication including complex arithmetic and programmability.
A succession of steadily more powerful and flexible computing devices were constructed in the 1930s and 1940s, gradually adding the key features that are seen in modern computers. The use of digital electronics (largely invented by Claude Shannon in 1937) and more flexible programmability were vitally important steps, but defining one point along this road as “the first digital electronic computer” is difficult.Shannon 1940 Notable achievements include:.
Nearly all modern computers implement some form of the stored-program architecture, making it the single trait by which the word “computer” is now defined. While the technologies used in computers have changed dramatically since the first electronic, general-purpose computers of the 1940s, most still use the von Neumann architecture.
Beginning in the 1950s, Soviet scientists Sergei Sobolev and Nikolay Brusentsov conducted research on ternary computers, devices that operated on a base three numbering system of -1, 0, and 1 rather than the conventional binary numbering system upon which most computers are based. They designed the Setun, a functional ternary computer, at Moscow State University. The device was put into limited production in the Soviet Union, but supplanted by the more common binary architecture.
Computers using vacuum tubes as their electronic elements were in use throughout the 1950s, but by the 1960s they had been largely replaced by transistor-based machines, which were smaller, faster, cheaper to produce, required less power, and were more reliable. The first transistorized computer was demonstrated at the University of Manchester in 1953. In the 1970s, integrated circuit technology and the subsequent creation of microprocessors, such as the Intel 4004, further decreased size and cost and further increased speed and reliability of computers. By the late 1970s, many products such as video recorders contained dedicated computers called microcontrollers, and they started to appear as a replacement to mechanical controls in domestic appliances such as washing machines. The 1980s witnessed home computers and the now ubiquitous personal computer. With the evolution of the Internet, personal computers are becoming as common as the television and the telephone in the household.
In practical terms, a computer program may be just a few instructions or extend to many millions of instructions, as do the programs for word processors and web browsers for example. A typical modern computer can execute billions of instructions per second (gigaflops) and rarely makes a mistake over many years of operation. Large computer programs consisting of several million instructions may take teams of programmers years to write, and due to the complexity of the task almost certainly contain errors.
In most cases, computer instructions are simple: add one number to another, move some data from one location to another, send a message to some external device, etc. These instructions are read from the computer's memory and are generally carried out (executed) in the order they were given. However, there are usually specialized instructions to tell the computer to jump ahead or backwards to some other place in the program and to carry on executing from there. These are called “jump” instructions (or branches). Furthermore, jump instructions may be made to happen conditionally so that different sequences of instructions may be used depending on the result of some previous calculation or some external event. Many computers directly support subroutines by providing a type of jump that “remembers” the location it jumped from and another instruction to return to the instruction following that jump instruction.
Program execution might be likened to reading a book. While a person will normally read each word and line in sequence, they may at times jump back to an earlier place in the text or skip sections that are not of interest. Similarly, a computer may sometimes go back and repeat the instructions in some section of the program over and over again until some internal condition is met. This is called the flow of control within the program and it is what allows the computer to perform tasks repeatedly without human intervention.
Comparatively, a person using a pocket calculator can perform a basic arithmetic operation such as adding two numbers with just a few button presses. But to add together all of the numbers from 1 to 1,000 would take thousands of button presses and a lot of time, with a near certainty of making a mistake. On the other hand, a computer may be programmed to do this with just a few simple instructions.
Errors in computer programs are called “bugs.” They may be benign and not affect the usefulness of the program, or have only subtle effects. But in some cases, they may cause the program or the entire system to “hang,” becoming unresponsive to input such as mouse clicks or keystrokes, to completely fail, or to crash. Otherwise benign bugs may sometimes be harnessed for malicious intent by an unscrupulous user writing an exploit, code designed to take advantage of a bug and disrupt a computer's proper execution. Bugs are usually not the fault of the computer. Since computers merely execute the instructions they are given, bugs are nearly always the result of programmer error or an oversight made in the program's design.
In most computers, individual instructions are stored as machine code with each instruction being given a unique number (its operation code or opcode for short). The command to add two numbers together would have one opcode, the command to multiply them would have a different opcode and so on. The simplest computers are able to perform any of a handful of different instructions; the more complex computers have several hundred to choose from, each with a unique numerical code. Since the computer's memory is able to store numbers, it can also store the instruction codes. This leads to the important fact that entire programs (which are just lists of these instructions) can be represented as lists of numbers and can themselves be manipulated inside the computer in the same way as numeric data. The fundamental concept of storing programs in the computer's memory alongside the data they operate on is the crux of the von Neumann, or stored program, architecture. In some cases, a computer might store some or all of its program in memory that is kept separate from the data it operates on. This is called the Harvard architecture after the Harvard Mark I computer. Modern von Neumann computers display some traits of the Harvard architecture in their designs, such as in CPU caches.
While it is possible to write computer programs as long lists of numbers (machine language) and while this technique was used with many early computers, it is extremely tedious and potentially error-prone to do so in practice, especially for complicated programs. Instead, each basic instruction can be given a short name that is indicative of its function and easy to remember – a mnemonic such as ADD, SUB, MULT or JUMP. These mnemonics are collectively known as a computer's assembly language. Converting programs written in assembly language into something the computer can actually understand (machine language) is usually done by a computer program called an assembler.
Programming languages provide various ways of specifying programs for computers to run. Unlike natural languages, programming languages are designed to permit no ambiguity and to be concise. They are purely written languages and are often difficult to read aloud. They are generally either translated into machine code by a compiler or an assembler before being run, or translated directly at run time by an interpreter. Sometimes programs are executed by a hybrid method of the two techniques.
Though considerably easier than in machine language, writing long programs in assembly language is often difficult and is also error prone. Therefore, most practical programs are written in more abstract high-level programming languages that are able to express the needs of the programmer more conveniently (and thereby help reduce programmer error). High level languages are usually “compiled” into machine language (or sometimes into assembly language and then into machine language) using another computer program called a compiler. High level languages are less related to the workings of the target computer than assembly language, and more related to the language and structure of the problem(s) to be solved by the final program. It is therefore often possible to use different compilers to translate the same high level language program into the machine language of many different types of computer. This is part of the means by which software like video games may be made available for different computer architectures such as personal computers and various video game consoles.
Program design of small programs is relatively simple and involves the analysis of the problem, collection of inputs, using the programming constructs within languages, devising or using established procedures and algorithms, providing data for output devices and solutions to the problem as applicable. As problems become larger and more complex, features such as subprograms, modules, formal documentation, and new paradigms such as object-oriented programming are encountered. Large programs involving thousands of line of code and more require formal software methodologies. The task of developing large software systems presents a significant intellectual challenge. Producing software with an acceptably high reliability within a predictable schedule and budget has historically been difficult; the academic and professional discipline of software engineering concentrates specifically on this challenge.
A general purpose computer has four main components: the arithmetic logic unit (ALU), the control unit, the memory, and the input and output devices (collectively termed I/O). These parts are interconnected by buses, often made of groups of wires.
The control unit, ALU, registers, and basic I/O (and often other hardware closely linked with these) are collectively known as a central processing unit (CPU). Early CPUs were composed of many separate components but since the mid-1970s CPUs have typically been constructed on a single integrated circuit called a microprocessor.
The set of arithmetic operations that a particular ALU supports may be limited to addition and subtraction, or might include multiplication, division, trigonometry functions such as sine, cosine, etc., and square roots. Some can only operate on whole numbers (integers) whilst others use floating point to represent real numbers, albeit with limited precision. However, any computer that is capable of performing just the simplest operations can be programmed to break down the more complex operations into simple steps that it can perform. Therefore, any computer can be programmed to perform any arithmetic operation—although it will take more time to do so if its ALU does not directly support the operation. An ALU may also compare numbers and return boolean truth values (true or false) depending on whether one is equal to, greater than or less than the other (“is 64 greater than 65?”).
A computer's memory can be viewed as a list of cells into which numbers can be placed or read. Each cell has a numbered “address” and can store a single number. The computer can be instructed to “put the number 123 into the cell numbered 1357” or to “add the number that is in cell 1357 to the number that is in cell 2468 and put the answer into cell 1595.” The information stored in memory may represent practically anything. Letters, numbers, even computer instructions can be placed into memory with equal ease. Since the CPU does not differentiate between different types of information, it is the software's responsibility to give significance to what the memory sees as nothing but a series of numbers.
Computer main memory comes in two principal varieties: random-access memory or RAM and read-only memory or ROM. RAM can be read and written to anytime the CPU commands it, but ROM is preloaded with data and software that never changes, therefore the CPU can only read from it. ROM is typically used to store the computer's initial start-up instructions. In general, the contents of RAM are erased when the power to the computer is turned off, but ROM retains its data indefinitely. In a PC, the ROM contains a specialized program called the BIOS that orchestrates loading the computer's operating system from the hard disk drive into RAM whenever the computer is turned on or reset. In embedded computers, which frequently do not have disk drives, all of the required software may be stored in ROM. Software stored in ROM is often called firmware, because it is notionally more like hardware than software. Flash memory blurs the distinction between ROM and RAM, as it retains its data when turned off but is also rewritable. It is typically much slower than conventional ROM and RAM however, so its use is restricted to applications where high speed is unnecessary.
In more sophisticated computers there may be one or more RAM cache memories, which are slower than registers but faster than main memory. Generally computers with this sort of cache are designed to move frequently needed data into the cache automatically, often without the need for any intervention on the programmer's part.
I/O is the means by which a computer exchanges information with the outside world. Devices that provide input or output to the computer are called peripherals. On a typical personal computer, peripherals include input devices like the keyboard and mouse, and output devices such as the display and printer. Hard disk drives, floppy disk drives and optical disc drives serve as both input and output devices. Computer networking is another form of I/O.
One means by which this is done is with a special signal called an interrupt, which can periodically cause the computer to stop executing instructions where it was and do something else instead. By remembering where it was executing prior to the interrupt, the computer can return to that task later. If several programs are running “at the same time,” then the interrupt generator might be causing several hundred interrupts per second, causing a program switch each time. Since modern computers typically execute instructions several orders of magnitude faster than human perception, it may appear that many programs are running at the same time even though only one is ever executing in any given instant. This method of multitasking is sometimes termed “time-sharing” since each program is allocated a “slice” of time in turn.
Seemingly, multitasking would cause a computer that is switching between several programs to run more slowly, in direct proportion to the number of programs it is running, but most programs spend much of their time waiting for slow input/output devices to complete their tasks. If a program is waiting for the user to click on the mouse or press a key on the keyboard, then it will not take a “time slice” until the event it is waiting for has occurred. This frees up time for other programs to execute so that many programs may be run simultaneously without unacceptable speed loss.
Some computers are designed to distribute their work across several CPUs in a multiprocessing configuration, a technique once employed only in large and powerful machines such as supercomputers, mainframe computers and servers. Multiprocessor and multi-core (multiple CPUs on a single integrated circuit) personal and laptop computers are now widely available, and are being increasingly used in lower-end markets as a result.
Supercomputers in particular often have highly unique architectures that differ significantly from the basic stored-program architecture and from general purpose computers. They often feature thousands of CPUs, customized high-speed interconnects, and specialized computing hardware. Such designs tend to be useful only for specialized tasks due to the large scale of program organization required to successfully utilize most of the available resources at once. Supercomputers usually see usage in large-scale simulation, graphics rendering, and cryptography applications, as well as with other so-called “embarrassingly parallel” tasks.
In time, the network spread beyond academic and military institutions and became known as the Internet. The emergence of networking involved a redefinition of the nature and boundaries of the computer. Computer operating systems and applications were modified to include the ability to define and access the resources of other computers on the network, such as peripheral devices, stored information, and the like, as extensions of the resources of an individual computer. Initially these facilities were available primarily to people working in high-tech environments, but in the 1990s the spread of applications like e-mail and the World Wide Web, combined with the development of cheap, fast networking technologies like Ethernet and ADSL saw computer networking become almost ubiquitous. In fact, the number of computers that are networked is growing phenomenally. A very large proportion of personal computers regularly connect to the Internet to communicate and receive information. “Wireless” networking, often utilizing mobile phone networks, has meant networking is becoming increasingly ubiquitous even in mobile computing environments.
The ability to store and execute lists of instructions called programs makes computers extremely versatile, distinguishing them from calculators. The Church–Turing thesis is a mathematical statement of this versatility: any computer with a minimum capability (being Turing-complete) is, in principle, capable of performing the same tasks that any other computer can perform. Therefore any type of computer (netbook, supercomputer, cellular automaton, etc.) is able to perform the same computational tasks, given enough time and storage capacity.
A computer does not need to be electronic, nor even have a processor, nor RAM, nor even a hard disk. While popular usage of the word “computer” is synonymous with a personal electronic computer, the modern definition of a computer is literally “A device that computes, especially a programmable electronic machine that performs high-speed mathematical or logical operations or that assembles, stores, correlates, or otherwise processes information.” Any device which processes information qualifies as a computer, especially if the processing is purposeful.
There is active research to make computers out of many promising new types of technology, such as optical computers, DNA computers, neural computers, and quantum computers. Most computers are universal, and are able to calculate any computable function, and are limited only by their memory capacity and operating speed. However different designs of computers can give very different performance for particular problems; for example quantum computers can potentially break some modern encryption algorithms (by quantum factoring) very quickly.
A computer will solve problems in exactly the way it is programmed to, without regard to efficiency, alternative solutions, possible shortcuts, or possible errors in the code. Computer programs that learn and adapt are part of the emerging field of artificial intelligence and machine learning.
The term hardware covers all of those parts of a computer that are tangible objects. Circuits, displays, power supplies, cables, keyboards, printers and mice are all hardware.
Software refers to parts of the computer which do not have a material form, such as programs, data, protocols, etc. When software is stored in hardware that cannot easily be modified (such as BIOS ROM in an IBM PC compatible), it is sometimes called “firmware.”.
The field covers all the processes and mechanisms by which computer-based equipment, information and services are protected from unintended or unauthorized access, change or destruction. Computer security also includes protection from unplanned events and natural disasters.
Security Architecture can be defined as the design artifacts that describe how the security controls (security countermeasures) are positioned, and how they relate to the overall information technology architecture. These controls serve to maintain the system's quality attributes: confidentiality, integrity, availability, accountability and assurance services.
While hardware may be a source of insecurity, hardware based or assisted computer security offers an alternative to software-only computer security. Devices such as dongles, case intrusion detection, drive locks, or disabling USB ports, or CD ROM Drives may be considered more secure due to the physical access required in order to be compromised. This is important to know for data conservation.
One use of the term computer security refers to technology to implement a secure operating system. Much of this technology is based on science developed in the 1980s and used to produce what may be some of the most impenetrable operating systems ever. Though still valid, the technology is in limited use today, primarily because it imposes some changes to system management and also because it is not widely understood. Such ultra-strong secure operating systems are based on operating system kernel technology that can guarantee that certain security policies are absolutely enforced in an operating environment. An example of such a Computer security policy is the Bell-LaPadula model. The strategy is based on a coupling of special microprocessor hardware features, often involving the memory management unit, to a special correctly implemented operating system kernel. This forms the foundation for a secure operating system which, if certain critical parts are designed and implemented correctly, can ensure the absolute impossibility of penetration by hostile elements. This capability is enabled because the configuration not only imposes a security policy, but in theory completely protects itself from corruption. Ordinary operating systems, on the other hand, lack the features that assure this maximal level of security. The design methodology to produce such secure systems is precise, deterministic and logical.
After the
Netscape announcement broke in January I did a lot of thinking about the next phase -- the serious push to get "free software" accepted in the mainstream corporate world. And I realized we have a serious problem with "free software" itself.
Specifically, we have a problem with the
term "free software", itself, not the concept. I've become convinced that the term has to go.
The problem with it is twofold. First, it's confusing; the term "free" is very ambiguous (something the
Free Software Foundation's propaganda has to wrestle with constantly). Does "free" mean "no money charged?" or does it mean "free to be modified by anyone", or something else?
Second, the term makes a lot of corporate types nervous. While this does not intrinsically bother me in the least, we now have a pragmatic interest in converting these people rather than thumbing our noses at them. There's now a chance we can make serious gains in the mainstream business world without compromising our ideals and commitment to technical excellence -- so it's time to reposition. We need a new and better label.
I brainstormed this with some Silicon Valley fans of Linux (including Larry Augustin of the
Linux International board of directors) the day after my meeting with Netscape (Feb 5th). We kicked around and discarded several alternatives, and we came up with a replacement label we all liked: "open source".
We suggest that everywhere we as a culture have previously talked about "free software", the label should be changed to "open source". Open-source software. The open-source model. The open source culture. The Debian Open Source Guidelines. (In pitching this to the corporate world I'm also going to be invoking the idea of "peer review" a lot.)
And, we should explain publicly the reason for the change. Linus Torvalds has been saying in "World Domination 101" that the open-source culture needs to make a serious effort to take the desktop and engage the corporate mainstream. Of course he's right -- and this re-labeling, as Linus agrees, is part of the process. It says we're willing to work with and co-opt the market for our own purposes, rather than remaining stuck in a marginal, adversarial position.
This re-labeling has since attracted a lot of support (and some opposition) in the hacker culture. Supporters include Linus himself, John "maddog" Hall, Larry Augustin, Bruce Perens of
Debian, Phil Hughes of
Linux Journal. Opposers include Richard Stallman, who initially flirted with the idea but now thinks the term "open source" isn't pure enough.
Bruce Perens has applied to register "open source" as a trademark and hold it through Software in the Public Interest. The trademark conditions will be known as the ``Open Source Definition'', essentially the same as the
Debian Free Software Guidelines.
It's crunch time, people. The Netscape announcement changes everything. We've broken out of the little corner we've been in for twenty years. We're in a whole new game now, a bigger and more exciting one -- and one I think we can win.
Her grades fell. She was always tired. She never seemed to be able to focus at school. Classes she used to be interested in became utterly mundane. Friends she used to care about became replaceable. She stopped spending time with her family. She sat on the bench at every soccer game instead of becoming the star player her coaches thought she could. This is what addiction to drugs can do to a young person’s life. Addiction can take away everything that once made that young person happy. The only thing that matters anymore is the drug, getting high, and getting higher. It is a horrible and tragic thing that destroys so many young lives. Some people think that in order to prevent these situations, the best solution is random drug testing. But this is not a reasonable solution whatsoever. Many more students are using and selling drugs as they roam around the campus, but will never be “caught” with such a fickle and illusive process. Random student drug testing is not a plausible solution for the drug problem in public schools; it is unreliable and it infringes on the lives of those students involved.
There is a sense of complexity today that has led many to believe the individual investor has little chance of competing with professional brokers and investment firms. However, Malkiel states this is a major misconception as he explains in his book “A Random Walk Down Wall Street”. What does a random walk mean? The random walk means in terms of the stock market that, “short term changes in stock prices cannot be predicted”. So how does a rational investor determine which stocks to purchase to maximize returns? Chapter 1 begins by defining and determining the difference in investing and speculating. Investing defined by Malkiel is the method of “purchasing assets to gain profit in the form of reasonably predictable income or appreciation over the long term”. Speculating in a sense is predicting, but without sufficient data to support any kind of conclusion. What is investing? Investing in its simplest form is the expectation to receive greater value in the future than you have today by saving income rather than spending. For example a savings account will earn a particular interest rate as will a corporate bond. Investment returns therefore depend on the allocation of funds and future events. Traditionally there have been two approaches used by the investment community to determine asset valuation: “the firm-foundation theory” and the “castle in the air theory”.
Recent empirical studies imply that most appraisal error is nonrandom, which suggests that strategies that advocate portfolio assembly over individual property selection may be defective.
Each step of the appraisal process involves an unknown amount of estimation error. The combination of these errors is unlikely to produce a perfect, error-free estimate of value. Thus, appraisal error is virtually unavoidable. Investors need reasonable estimates of value when buying, selling, or retaining commercial property, so an unknown amount of appraisal error adds uncertainty to the decision-making process. Despite the uncertainty, investors have learned to make allowances for appraisal error in their decision-making processes. The way in which real estate investors interpret appraisal errors has a material effect upon the decisions that they make. In particular, the predominant belief among real estate professionals is that appraisal error is random. This belief materially influences investor attitudes toward portfolio management and the valuation process itself. Lack of understanding of the relative magnitudes of random and nonrandom components of total appraisal error has consequences for optimal portfolio strategies. For example, investors who deem the bulk of total appraisal error to be random may reasonably conclude that error in estimates is beyond their control or influence.
