-
41 autocomprobación
f.self-test, self-check.* * *SF self-test* * *= self-checking, self-test, self-testing.Ex. This paper discusses the features of the EDLIN program and its use for creating the computer's automatic self-checking sequence when the machine is started.Ex. The author offers a self-test to help users choose the model that best suits their needs.Ex. This system uses expert system architectural principles to generate an inexhaustible supply of accounting questions that can be used by students for self-study and self-testing.* * *= self-checking, self-test, self-testing.Ex: This paper discusses the features of the EDLIN program and its use for creating the computer's automatic self-checking sequence when the machine is started.
Ex: The author offers a self-test to help users choose the model that best suits their needs.Ex: This system uses expert system architectural principles to generate an inexhaustible supply of accounting questions that can be used by students for self-study and self-testing. -
42 контрольный прогон программы
1. execution testing2. exhaustive testingРусско-английский большой базовый словарь > контрольный прогон программы
-
43 программный
1. softпрограммный возврат; мягкий возврат — soft return
2. program3. programm4. programmeфайл программ; программный файл — program file
5. software" программная шина " — software bus
-
44 Artificial Intelligence
In my opinion, none of [these programs] does even remote justice to the complexity of human mental processes. Unlike men, "artificially intelligent" programs tend to be single minded, undistractable, and unemotional. (Neisser, 1967, p. 9)Future progress in [artificial intelligence] will depend on the development of both practical and theoretical knowledge.... As regards theoretical knowledge, some have sought a unified theory of artificial intelligence. My view is that artificial intelligence is (or soon will be) an engineering discipline since its primary goal is to build things. (Nilsson, 1971, pp. vii-viii)Most workers in AI [artificial intelligence] research and in related fields confess to a pronounced feeling of disappointment in what has been achieved in the last 25 years. Workers entered the field around 1950, and even around 1960, with high hopes that are very far from being realized in 1972. In no part of the field have the discoveries made so far produced the major impact that was then promised.... In the meantime, claims and predictions regarding the potential results of AI research had been publicized which went even farther than the expectations of the majority of workers in the field, whose embarrassments have been added to by the lamentable failure of such inflated predictions....When able and respected scientists write in letters to the present author that AI, the major goal of computing science, represents "another step in the general process of evolution"; that possibilities in the 1980s include an all-purpose intelligence on a human-scale knowledge base; that awe-inspiring possibilities suggest themselves based on machine intelligence exceeding human intelligence by the year 2000 [one has the right to be skeptical]. (Lighthill, 1972, p. 17)4) Just as Astronomy Succeeded Astrology, the Discovery of Intellectual Processes in Machines Should Lead to a Science, EventuallyJust as astronomy succeeded astrology, following Kepler's discovery of planetary regularities, the discoveries of these many principles in empirical explorations on intellectual processes in machines should lead to a science, eventually. (Minsky & Papert, 1973, p. 11)5) Problems in Machine Intelligence Arise Because Things Obvious to Any Person Are Not Represented in the ProgramMany problems arise in experiments on machine intelligence because things obvious to any person are not represented in any program. One can pull with a string, but one cannot push with one.... Simple facts like these caused serious problems when Charniak attempted to extend Bobrow's "Student" program to more realistic applications, and they have not been faced up to until now. (Minsky & Papert, 1973, p. 77)What do we mean by [a symbolic] "description"? We do not mean to suggest that our descriptions must be made of strings of ordinary language words (although they might be). The simplest kind of description is a structure in which some features of a situation are represented by single ("primitive") symbols, and relations between those features are represented by other symbols-or by other features of the way the description is put together. (Minsky & Papert, 1973, p. 11)[AI is] the use of computer programs and programming techniques to cast light on the principles of intelligence in general and human thought in particular. (Boden, 1977, p. 5)The word you look for and hardly ever see in the early AI literature is the word knowledge. They didn't believe you have to know anything, you could always rework it all.... In fact 1967 is the turning point in my mind when there was enough feeling that the old ideas of general principles had to go.... I came up with an argument for what I called the primacy of expertise, and at the time I called the other guys the generalists. (Moses, quoted in McCorduck, 1979, pp. 228-229)9) Artificial Intelligence Is Psychology in a Particularly Pure and Abstract FormThe basic idea of cognitive science is that intelligent beings are semantic engines-in other words, automatic formal systems with interpretations under which they consistently make sense. We can now see why this includes psychology and artificial intelligence on a more or less equal footing: people and intelligent computers (if and when there are any) turn out to be merely different manifestations of the same underlying phenomenon. Moreover, with universal hardware, any semantic engine can in principle be formally imitated by a computer if only the right program can be found. And that will guarantee semantic imitation as well, since (given the appropriate formal behavior) the semantics is "taking care of itself" anyway. Thus we also see why, from this perspective, artificial intelligence can be regarded as psychology in a particularly pure and abstract form. The same fundamental structures are under investigation, but in AI, all the relevant parameters are under direct experimental control (in the programming), without any messy physiology or ethics to get in the way. (Haugeland, 1981b, p. 31)There are many different kinds of reasoning one might imagine:Formal reasoning involves the syntactic manipulation of data structures to deduce new ones following prespecified rules of inference. Mathematical logic is the archetypical formal representation. Procedural reasoning uses simulation to answer questions and solve problems. When we use a program to answer What is the sum of 3 and 4? it uses, or "runs," a procedural model of arithmetic. Reasoning by analogy seems to be a very natural mode of thought for humans but, so far, difficult to accomplish in AI programs. The idea is that when you ask the question Can robins fly? the system might reason that "robins are like sparrows, and I know that sparrows can fly, so robins probably can fly."Generalization and abstraction are also natural reasoning process for humans that are difficult to pin down well enough to implement in a program. If one knows that Robins have wings, that Sparrows have wings, and that Blue jays have wings, eventually one will believe that All birds have wings. This capability may be at the core of most human learning, but it has not yet become a useful technique in AI.... Meta- level reasoning is demonstrated by the way one answers the question What is Paul Newman's telephone number? You might reason that "if I knew Paul Newman's number, I would know that I knew it, because it is a notable fact." This involves using "knowledge about what you know," in particular, about the extent of your knowledge and about the importance of certain facts. Recent research in psychology and AI indicates that meta-level reasoning may play a central role in human cognitive processing. (Barr & Feigenbaum, 1981, pp. 146-147)Suffice it to say that programs already exist that can do things-or, at the very least, appear to be beginning to do things-which ill-informed critics have asserted a priori to be impossible. Examples include: perceiving in a holistic as opposed to an atomistic way; using language creatively; translating sensibly from one language to another by way of a language-neutral semantic representation; planning acts in a broad and sketchy fashion, the details being decided only in execution; distinguishing between different species of emotional reaction according to the psychological context of the subject. (Boden, 1981, p. 33)Can the synthesis of Man and Machine ever be stable, or will the purely organic component become such a hindrance that it has to be discarded? If this eventually happens-and I have... good reasons for thinking that it must-we have nothing to regret and certainly nothing to fear. (Clarke, 1984, p. 243)The thesis of GOFAI... is not that the processes underlying intelligence can be described symbolically... but that they are symbolic. (Haugeland, 1985, p. 113)14) Artificial Intelligence Provides a Useful Approach to Psychological and Psychiatric Theory FormationIt is all very well formulating psychological and psychiatric theories verbally but, when using natural language (even technical jargon), it is difficult to recognise when a theory is complete; oversights are all too easily made, gaps too readily left. This is a point which is generally recognised to be true and it is for precisely this reason that the behavioural sciences attempt to follow the natural sciences in using "classical" mathematics as a more rigorous descriptive language. However, it is an unfortunate fact that, with a few notable exceptions, there has been a marked lack of success in this application. It is my belief that a different approach-a different mathematics-is needed, and that AI provides just this approach. (Hand, quoted in Hand, 1985, pp. 6-7)We might distinguish among four kinds of AI.Research of this kind involves building and programming computers to perform tasks which, to paraphrase Marvin Minsky, would require intelligence if they were done by us. Researchers in nonpsychological AI make no claims whatsoever about the psychological realism of their programs or the devices they build, that is, about whether or not computers perform tasks as humans do.Research here is guided by the view that the computer is a useful tool in the study of mind. In particular, we can write computer programs or build devices that simulate alleged psychological processes in humans and then test our predictions about how the alleged processes work. We can weave these programs and devices together with other programs and devices that simulate different alleged mental processes and thereby test the degree to which the AI system as a whole simulates human mentality. According to weak psychological AI, working with computer models is a way of refining and testing hypotheses about processes that are allegedly realized in human minds.... According to this view, our minds are computers and therefore can be duplicated by other computers. Sherry Turkle writes that the "real ambition is of mythic proportions, making a general purpose intelligence, a mind." (Turkle, 1984, p. 240) The authors of a major text announce that "the ultimate goal of AI research is to build a person or, more humbly, an animal." (Charniak & McDermott, 1985, p. 7)Research in this field, like strong psychological AI, takes seriously the functionalist view that mentality can be realized in many different types of physical devices. Suprapsychological AI, however, accuses strong psychological AI of being chauvinisticof being only interested in human intelligence! Suprapsychological AI claims to be interested in all the conceivable ways intelligence can be realized. (Flanagan, 1991, pp. 241-242)16) Determination of Relevance of Rules in Particular ContextsEven if the [rules] were stored in a context-free form the computer still couldn't use them. To do that the computer requires rules enabling it to draw on just those [ rules] which are relevant in each particular context. Determination of relevance will have to be based on further facts and rules, but the question will again arise as to which facts and rules are relevant for making each particular determination. One could always invoke further facts and rules to answer this question, but of course these must be only the relevant ones. And so it goes. It seems that AI workers will never be able to get started here unless they can settle the problem of relevance beforehand by cataloguing types of context and listing just those facts which are relevant in each. (Dreyfus & Dreyfus, 1986, p. 80)Perhaps the single most important idea to artificial intelligence is that there is no fundamental difference between form and content, that meaning can be captured in a set of symbols such as a semantic net. (G. Johnson, 1986, p. 250)Artificial intelligence is based on the assumption that the mind can be described as some kind of formal system manipulating symbols that stand for things in the world. Thus it doesn't matter what the brain is made of, or what it uses for tokens in the great game of thinking. Using an equivalent set of tokens and rules, we can do thinking with a digital computer, just as we can play chess using cups, salt and pepper shakers, knives, forks, and spoons. Using the right software, one system (the mind) can be mapped into the other (the computer). (G. Johnson, 1986, p. 250)19) A Statement of the Primary and Secondary Purposes of Artificial IntelligenceThe primary goal of Artificial Intelligence is to make machines smarter.The secondary goals of Artificial Intelligence are to understand what intelligence is (the Nobel laureate purpose) and to make machines more useful (the entrepreneurial purpose). (Winston, 1987, p. 1)The theoretical ideas of older branches of engineering are captured in the language of mathematics. We contend that mathematical logic provides the basis for theory in AI. Although many computer scientists already count logic as fundamental to computer science in general, we put forward an even stronger form of the logic-is-important argument....AI deals mainly with the problem of representing and using declarative (as opposed to procedural) knowledge. Declarative knowledge is the kind that is expressed as sentences, and AI needs a language in which to state these sentences. Because the languages in which this knowledge usually is originally captured (natural languages such as English) are not suitable for computer representations, some other language with the appropriate properties must be used. It turns out, we think, that the appropriate properties include at least those that have been uppermost in the minds of logicians in their development of logical languages such as the predicate calculus. Thus, we think that any language for expressing knowledge in AI systems must be at least as expressive as the first-order predicate calculus. (Genesereth & Nilsson, 1987, p. viii)21) Perceptual Structures Can Be Represented as Lists of Elementary PropositionsIn artificial intelligence studies, perceptual structures are represented as assemblages of description lists, the elementary components of which are propositions asserting that certain relations hold among elements. (Chase & Simon, 1988, p. 490)Artificial intelligence (AI) is sometimes defined as the study of how to build and/or program computers to enable them to do the sorts of things that minds can do. Some of these things are commonly regarded as requiring intelligence: offering a medical diagnosis and/or prescription, giving legal or scientific advice, proving theorems in logic or mathematics. Others are not, because they can be done by all normal adults irrespective of educational background (and sometimes by non-human animals too), and typically involve no conscious control: seeing things in sunlight and shadows, finding a path through cluttered terrain, fitting pegs into holes, speaking one's own native tongue, and using one's common sense. Because it covers AI research dealing with both these classes of mental capacity, this definition is preferable to one describing AI as making computers do "things that would require intelligence if done by people." However, it presupposes that computers could do what minds can do, that they might really diagnose, advise, infer, and understand. One could avoid this problematic assumption (and also side-step questions about whether computers do things in the same way as we do) by defining AI instead as "the development of computers whose observable performance has features which in humans we would attribute to mental processes." This bland characterization would be acceptable to some AI workers, especially amongst those focusing on the production of technological tools for commercial purposes. But many others would favour a more controversial definition, seeing AI as the science of intelligence in general-or, more accurately, as the intellectual core of cognitive science. As such, its goal is to provide a systematic theory that can explain (and perhaps enable us to replicate) both the general categories of intentionality and the diverse psychological capacities grounded in them. (Boden, 1990b, pp. 1-2)Because the ability to store data somewhat corresponds to what we call memory in human beings, and because the ability to follow logical procedures somewhat corresponds to what we call reasoning in human beings, many members of the cult have concluded that what computers do somewhat corresponds to what we call thinking. It is no great difficulty to persuade the general public of that conclusion since computers process data very fast in small spaces well below the level of visibility; they do not look like other machines when they are at work. They seem to be running along as smoothly and silently as the brain does when it remembers and reasons and thinks. On the other hand, those who design and build computers know exactly how the machines are working down in the hidden depths of their semiconductors. Computers can be taken apart, scrutinized, and put back together. Their activities can be tracked, analyzed, measured, and thus clearly understood-which is far from possible with the brain. This gives rise to the tempting assumption on the part of the builders and designers that computers can tell us something about brains, indeed, that the computer can serve as a model of the mind, which then comes to be seen as some manner of information processing machine, and possibly not as good at the job as the machine. (Roszak, 1994, pp. xiv-xv)The inner workings of the human mind are far more intricate than the most complicated systems of modern technology. Researchers in the field of artificial intelligence have been attempting to develop programs that will enable computers to display intelligent behavior. Although this field has been an active one for more than thirty-five years and has had many notable successes, AI researchers still do not know how to create a program that matches human intelligence. No existing program can recall facts, solve problems, reason, learn, and process language with human facility. This lack of success has occurred not because computers are inferior to human brains but rather because we do not yet know in sufficient detail how intelligence is organized in the brain. (Anderson, 1995, p. 2)Historical dictionary of quotations in cognitive science > Artificial Intelligence
-
45 тестовая программа
1) Computers: benchmark2) Engineering: DNC program, diagnosis program, diagnostic program, test program, test routine, testing routine3) Information technology: B-program, check program, personal computer world benchmark, test harness4) Network technologies: PCW-benchmark5) Makarov: benchmark program, test programmeУниверсальный русско-английский словарь > тестовая программа
-
46 контроль
control, check, checking, checkout, exercising, gaging, inspection, measurement, measuring, test, testing, prove-out, sense, sensing, supervision, surveillance, verification, watch* * *контро́ль м.
( периодический) check(ing), control, inspection; ( обычно непрерывный) monitoringавтомати́ческий контро́ль маш. — automatic gauging, automatic inspectionакти́вный контро́ль — in-process [on-line] gaugingвизуа́льный контро́ль ( качества) — visual inspectionвходно́й контро́ль ( потребителем от других предприятий) — incoming controlвы́борочный контро́ль — random inspection, spot check, samplingвы́борочный, двукра́тный контро́ль — double samplingвы́борочный, многокра́тный контро́ль — multiple samplingвы́борочный, однокра́тный контро́ль — single samplingвы́борочный, после́довательный контро́ль — sequential testградацио́нный контро́ль полигр. — tonal gradation controlдистанцио́нный контро́ль — remote monitoringдозиметри́ческий контро́ль — radiation monitoring; (помещений, местности) radiation surveyдозиметри́ческий, индивидуа́льный контро́ль — personal monitoringконтро́ль излуче́ния анте́нны — radiation monitoringконтро́ль ка́чества (проду́кции) — quality control, product inspectionконтро́ль материа́лов вихревы́ми то́ками ( в дефектоскопии) — eddy-current test(ing), eddy-current inspectionконтро́ль материа́лов вихревы́ми то́ками с накладно́й кату́шкой ( в дефектоскопии) — solenoid-coil eddy-current test(ing)контро́ль материа́лов вихревы́ми то́ками с проходно́й кату́шкой ( в дефектоскопии) — inside-coil eddy-current test(ing)контро́ль материа́лов га́мма-просве́чиванием ( в дефектоскопии) — gamma-ray radiography, gamma-ray inspectionконтро́ль материа́лов, люминесце́нтный ( в дефектоскопии) — fluorescent-penetrant inspectionконтро́ль материа́лов, магни́тно-порошко́вый ( в дефектоскопии) — magnetic-particle test(ing), magnetic-particle inspectionконтро́ль материа́лов, магнитографи́ческий ( в дефектоскопии) — magnetic-tape test(ing), magnetic-tape inspectionконтро́ль материа́лов ме́тодом кра́сок ( в дефектоскопии) — dye-penetrant test(ing)контро́ль материа́лов, неразруша́ющий ( в дефектоскопии) — nondestructive (materials) testingконтро́ль материа́лов рентгенопросве́чиванием ( в дефектоскопии) — X-ray test(ing), X-ray inspectionконтро́ль материа́лов, ультразвуково́й ( в дефектоскопии) — ultrasonic test(ing), ultrasonic inspectionконтро́ль материа́лов, цветно́й ( в дефектоскопии) — dye-penetrant test(ing)контро́ль материа́лов, феррозо́ндовый ( в дефектоскопии) — probe-coil magnetic-field test(ing)обега́ющий контро́ль — scanning-type data logging (system)обра́тный контро́ль свз. — revertive monitoringконтро́ль оши́бок — error control, error checkконтро́ль переда́чи, печа́тный свз. — home copyрабо́тать [передава́ть] без печа́тного контро́ля переда́чи — send blind, send with the home copy suppressedконтро́ль переполне́ния вчт. — overflow checkконтро́ль перфока́рт на просве́т — sight check of punch (ed) cardsконтро́ль перфока́рт, счё́тный контро́ль — punch(ed)-card verification by batch totalsпооперацио́нный контро́ль маш. — step-by-step [operation] checkingконтро́ль пра́вильности реше́ния или результа́тов — check on the solution or resultsприё́мочный контро́ль — acceptance inspection, acceptance testingпрогра́ммный контро́ль ( с помощью программы) — program(me) checkпылево́й контро́ль горн. — dust controlконтро́ль радиоакти́вности — radiation [radioactivity] monitoringконтро́ль радиоакти́вности атмосфе́ры — air monitoringконтро́ль разме́ров — gauging, dimension inspectionконтро́ль систе́мы (в це́лом) — system checkсплошно́й контро́ль — complete controlтехни́ческий контро́ль — technical controlконтро́ль технологи́ческого проце́сса — process monitoringконтро́ль хими́ческого соста́ва — chemical analysis inspectionконтро́ль ЭВМ [цифрово́й вычисли́тельной маши́ны], аппара́т(ур)ный — automatic [built-in, hardware] checkконтро́ль частоты́ — frequency monitoringэксплуатацио́нный контро́ль — field inspectionконтро́ль ЭВМ, логи́ческий — logical checkконтро́ль ЭВМ по запрещё́нным комбина́циям — forbidden-combination [forbidden-character] checkконтро́ль ЭВМ по избы́точности — redundancy checkконтро́ль ЭВМ по мо́дулю — N mod(ulo) N checkконтро́ль ЭВМ по оста́тку — residue checkконтро́ль ЭВМ по су́мме — sum checkконтро́ль ЭВМ по чё́тности — (even-)parity [(odd-)parity, odd-even] checkконтро́ль ЭВМ, програ́ммный — programmed checkконтро́ль ЦВМ, профилакти́ческий — marginal checkконтро́ль ЦВМ сумми́рованием — summation checkконтро́ль ЦВМ, схе́мный — automatic [built-in, hardware] checkконтро́ль ЦВМ, теку́щий — current [running] checkконтро́ль электро́нной аппарату́ры, диагности́ческий — marginal check(ing), marginal testing -
47 метод
approach, device, manner, mean, method, mode, practice, procedure, system, technique, technology, theory, way* * *ме́тод м.
method; procedure; techniqueагрегатнопото́чный ме́тод — conveyor-type production [production-line] methodаксиомати́ческий ме́тод — axiomatic [postulational] methodме́тод амплиту́дного ана́лиза — kick-sorting methodанаглифи́ческий ме́тод картогр. — anaglyphic(al) methodме́тод аналити́ческой вста́вки топ. — cantilever extension, cantilever (strip) triangulationме́тод быстре́йшего спу́ска стат. — steepest descent methodвариацио́нный ме́тод — variational methodме́тод Верне́йля радио — Verneuil methodвесово́й ме́тод — gravimetric methodме́тод ветве́й и грани́ц киб. — branch and bound methodме́тод взба́лтывания — shake methodвизуа́льный ме́тод — visual methodме́тод возду́шной прое́кции — aero-projection methodме́тод враще́ния — method of revolutionме́тод вреза́ния — plunge-cut methodме́тод вре́мени пролё́та — time-of-flight methodвре́мя-и́мпульсный ме́тод ( преобразования аналоговой информации в дискретную) — pulse-counting method (of analog-to-digital conversion)ме́тод встре́чного фрезерова́ния — conventional [cut-up] milling methodме́тод вы́бега эл. — retardation methodме́тод вымета́ния мат. — sweep(ing)-out methodме́тод гармони́ческого бала́нса киб., автмт. — describing function methodме́тод гармони́ческой линеариза́ции — describing function methodголографи́ческий ме́тод — holographic methodгравиметри́ческий ме́тод — gravimetric(al) methodграфи́ческий ме́тод — graphical methodме́тод графи́ческого трансформи́рования топ. — grid methodграфоаналити́ческий ме́тод — semigraphical methodме́тод гра́фов мат. — graph methodгруппово́й ме́тод ( в высокочастотной телефонии) — grouped-frequency basisсисте́ма рабо́тает групповы́м ме́тодом — the system operates on the grouped-frequency basisме́тод двух ре́ек геод., топ. — two-staff [two-base] methodме́тод двух узло́в ( в анализе электрических цепей) — nodal-pair methodме́тод дирекцио́нных угло́в геод. — method of gisementsме́тод запа́са про́чности ( в расчетах конструкции) — load factor methodме́тод засе́чек афс. — resection methodме́тод зерка́льных изображе́ний эл. — method of electrical imagesме́тод зо́нной пла́вки ( в производстве монокристаллов полупроводниковых материалов) — floating-zone method, floating-zone techniqueме́тод избы́точных концентра́ций ( для опробования гипотетического механизма реакции) — isolation method (of the testing the rate equations)ме́тод измере́ния, абсолю́тный — absolute [fundamental] method of measurementме́тод измере́ния, конта́ктный — contact method of measurementме́тод измере́ния, ко́свенный — indirect method of measurementме́тод измере́ния, относи́тельный — relative method of measurementме́тод измере́ния по то́чкам — point-by-point methodме́тод измере́ния, прямо́й — direct method of measurementме́тод измере́ния угло́в по аэросни́мкам — photogoniometric methodме́тод изображе́ний эл. — method of images, image methodме́тод изото́пных индика́торов — tracer methodиммерсио́нный ме́тод — immersion methodи́мпульсный ме́тод свар. — pulse methodме́тод и́мпульсов — momentum-transfer methodме́тод инве́рсии — inversion methodи́ндексно-после́довательный ме́тод до́ступа, основно́й вчт. — basic indexed sequential access method, BISAMи́ндексно-после́довательный ме́тод до́ступа с очередя́ми вчт. — queued indexed sequential access method, BISAMинтерференцио́нный ме́тод — interferometric methodме́тод испыта́ний — testing procedure, testing methodме́тод испыта́ний, кисло́тный — acid testме́тод испыта́ний, пане́льный — panel-spalling testме́тод испыта́тельной строки́ тлв. — test-line methodме́тод иссле́дований напряже́ний, опти́ческий — optical stress analysisме́тод истече́ния — efflux methodме́тод итера́ции — iteration method, iteration techniqueме́тод итера́ции приво́дит к сходи́мости проце́сса — the iteration (process) converges to a solutionме́тод итера́ции приво́дит к (бы́строй или ме́дленной) сходи́мости проце́сса — the iteration (process) converges quickly or slowlyме́тод картосоставле́ния — map-compilation [plotting] methodме́тод кача́ющегося криста́лла ( в рентгеноструктурном анализе) — rotating-crystal methodка́чественный ме́тод — qualitative methodкессо́нный ме́тод — caisson methodколи́чественный ме́тод — quantitative methodколориметри́ческий ме́тод — colorimetric methodме́тод кольца́ и ша́ра — ball-and-ring methodкомплексометри́ческий ме́тод ( для определения жёсткости воды) — complexometric methodкондуктометри́ческий ме́тод — conductance-measuring methodме́тод коне́чных ра́зностей — finite difference methodме́тод консерви́рования — curing methodме́тод контро́ля, дифференци́рованный — differential control methodме́тод контро́ля ка́чества — quality control methodме́тод ко́нтурных то́ков — mesh-current [loop] methodме́тод ко́нуса — cone methodме́тод корнево́го годо́графа киб., автмт. — root-locus methodкорреляцио́нный ме́тод — correlation methodко́свенный ме́тод — indirect methodме́тод кра́сок ( в дефектоскопии) — dye-penetrant methodлаборато́рный ме́тод — laboratory methodме́тод ла́ковых покры́тий ( в сопротивлении материалов) — brittle-varnish methodме́тод лине́йной интерполя́ции — method of proportional partsме́тод Ляпуно́ва аргд. — Lyapunov's methodме́тод магни́тного порошка́ ( в дефектоскопии) — magnetic particle [magnetic powder] methodмагни́тно-люминесце́нтный ме́тод ( в дефектоскопии) — fluorescent magnetic particle methodме́тод ма́лого пара́метра киб., автмт. — perturbation theory, perturbation methodме́тод ма́лых возмуще́ний аргд. — perturbation methodме́тод мгнове́нной равносигна́льной зо́ны рлк. — simultaneous lobing [monopulse] methodме́тод механи́ческой обрабо́тки — machining methodме́тод ме́ченых а́томов — tracer methodме́тод микрометри́рования — micrometer methodме́тод мно́жителей Лагра́нжа — Lagrangian multiplier method, Lagrange's method of undetermined multipliersме́тод моме́нтных площаде́й мех. — area moment methodме́тод Мо́нте-Ка́рло мат. — Monte Carlo methodме́тод навига́ции, дальноме́рный ( пересечение двух окружностей) — rho-rho [r-r] navigationме́тод навига́ции, угломе́рный ( пересечение двух линий пеленга) — theta-theta [q-q] navigationме́тод наиме́ньших квадра́тов — method of least squares, least-squares techniqueме́тод наискоре́йшего спу́ска мат. — method of steepest descentме́тод нака́чки ( лазера) — pumping [excitation] methodме́тод накопле́ния яд. физ. — “backing-space” methodме́тод наложе́ния — method of superpositionме́тод напыле́ния — evaporation techniqueме́тод нару́жных заря́дов горн. — adobe blasting methodме́тод незави́симых стереопа́р топ. — method of independent image pairsненулево́й ме́тод — deflection methodме́тод неопределё́нных мно́жителей Лагра́нжа — Lagrangian multiplier method, Lagrange's method of undetermined multipliersме́тод неподви́жных то́чек — method of fixed pointsнеразруша́ющий ме́тод — non-destructive method, non-destructive testingнерекурси́вный ме́тод — non-recursive methodнето́чный ме́тод — inexact methodнефелометри́ческий ме́тод — nephelometric methodме́тод нивели́рования по частя́м — method of fraction levellingнулево́й ме́тод — null [zero(-deflection) ] methodме́тод нулевы́х бие́ний — zero-beat methodме́тод нулевы́х то́чек — neutral-points methodме́тод обеспе́чения надё́жности — reliability methodме́тод обрабо́тки — processing [working, tooling] methodме́тод обра́тной простра́нственной засе́чки топ. — method of pyramidобра́тно-ступе́нчатый ме́тод свар. — step-back methodме́тод объединё́нного а́тома — associate atom methodобъекти́вный ме́тод — objective methodобъё́мный ме́тод — volumetric methodме́тод одного́ отсчё́та ( преобразование непрерывной информации в дискретную) — the total value method (of analog-to-digital conversion)окисли́тельно-восстанови́тельный ме́тод — redox methodопера́торный ме́тод — operational methodме́тод определе́ния ме́ста, дальноме́рно-пеленгацио́нный ( пересечение прямой и окружности) — rho-theta [r-q] fixingме́тод определе́ния ме́ста, дальноме́рный ( пересечение двух окружностей) — rho-rho [r-r] fixingме́тод определе́ния ме́ста, пеленгацио́нный ( пересечение двух линий пеленга) — theta-theta [q-q] fixingме́тод определе́ния отбе́ливаемости и цве́тности ма́сел — bleach-and-colour methodме́тод определе́ния положе́ния ли́нии, двукра́тный геод. — double-line methodме́тод опти́ческой корреля́ции — optical correlation techniqueме́тод осажде́ния — sedimentation methodме́тод осо́бых возмуще́ний аргд. — singular perturbation methodме́тод осредне́ния — averaging [smoothing] methodме́тод отбо́ра проб — sampling method, sampling techniqueме́тод отклоне́ния — deflection methodме́тод отопле́ния метал. — fuel practiceме́тод отраже́ния — reflection methodме́тод отражё́нных и́мпульсов — pulse-echo methodме́тод отыска́ния произво́дной, непосре́дственный — delta methodме́тод па́дающего те́ла — falling body methodме́тод парамагни́тного резона́нса — paramagnetic-resonance methodме́тод пе́рвого приближе́ния — first approximation methodме́тод перева́ла мат. — saddle-point methodме́тод перено́са коли́чества движе́ния аргд. — momentum-transfer methodме́тод перераспределе́ния моме́нтов ( в расчёте конструкций) — moment distribution methodме́тод пересека́ющихся луче́й — crossed beam methodме́тод перехо́дного состоя́ния ( в аналитической химии) — transition state methodме́тод перпендикуля́ров — offset methodме́тод перспекти́вных се́ток топ. — grid methodме́тод пескова́ния с.-х. — sanding methodпикнометри́ческий ме́тод — bottle methodме́тод площаде́й физ. — area methodме́тод повторе́ний геод. — method of reiteration, repetition methodме́тод подбо́ра — trial-and-error [cut-and-try] methodме́тод подо́бия — similitude methodме́тод подориенти́рования топ. — setting on points of controlме́тод по́лной деформа́ции — total-strain methodме́тод полови́нных отклоне́ний — half-deflection methodме́тод положе́ния геод. — method of bearings, method of gisementsполуколи́чественный ме́тод — semiquantitative methodме́тод поля́рных координа́т — polar methodме́тод попу́тного фрезерова́ния — climb [cut-down] milling methodпорошко́вый ме́тод ( в рентгеноструктурном анализе) — powder [Debye-Scherer-Hull] methodме́тод посе́ва — seeding techniqueме́тод после́довательного счё́та ( преобразования аналоговой информации в дискретную) — incremental method (of analog-to-digital conversion)ме́тод после́довательных исключе́ний — successive exclusion methodме́тод после́довательных подстано́вок — method of successive substitution, substitution processме́тод после́довательных попра́вок — successive correction methodме́тод после́довательных приближе́ний — successive approximation methodме́тод после́довательных элимина́ций — method of exhaustionме́тод послесплавно́й диффу́зии полупр. — post-alloy-diffusion techniqueпотенциометри́ческий компенсацио́нный ме́тод — potentiometric methodпото́чно-конве́йерный ме́тод — flow-line conveyor methodпото́чный ме́тод — straight-line flow methodме́тод прерыва́ний ( для измерения скорости света) — chopped-beam methodприближё́нный ме́тод — approximate methodме́тод проб и оши́бок — trial-and-error [cut-and-try] methodме́тод программи́рующих програ́мм — programming program methodме́тод продолже́ния топ. — setting on points on controlме́тод проекти́рования, моде́льно-маке́тный — model-and-mock-up method of designме́тод простра́нственного коди́рования ( преобразования аналоговой информации в дискретную) — coded pattern method (OF analog-to-digital conversion)ме́тод простра́нственной самофикса́ции — self-fixation space methodпрямо́й ме́тод — direct methodме́тод псевдослуча́йных чи́сел — pseudorandom number methodме́тод равносигна́льной зо́ны рлк. — lobing, beam [lobe] switchingме́тод равносигна́льной зо́ны, мгнове́нный рлк. — simultaneous lobing, monopulseме́тод ра́вных высо́т геод. — equal-altitude methodме́тод ра́вных деформа́ций ( в проектировании бетонных конструкций) — equal-strain methodме́тод ра́вных отклоне́ний — equal-deflection methodрадиацио́нный ме́тод — radiation methodме́тод радиоавтогра́фии — radioautograph techniqueме́тод радиоакти́вных индика́торов — tracer methodрадиометри́ческий ме́тод — radiometric methodме́тод разбавле́ния — dilution methodме́тод разделе́ния тлв. — separation methodме́тод разделе́ния переме́нных — method of separation of variablesме́тод разли́вки метал. — teeming [pouring, casting] practiceме́тод разме́рностей — dimensional methodра́зностный ме́тод — difference methodме́тод разруша́ющей нагру́зки — load-factor methodразруша́ющий ме́тод — destructive checkме́тод рассе́яния Рэле́я — Rayleigh scattering methodме́тод ра́стра тлв. — grid methodме́тод ра́стрового скани́рования — raster-scan methodме́тод расчё́та по допусти́мым нагру́зкам — working stress design [WSD] methodме́тод расчё́та по разруша́ющим нагру́зкам стр. — ultimate-strength design [USD] methodме́тод расчё́та при по́мощи про́бной нагру́зки стр. — trial-load methodме́тод расчё́та, упру́гий стр. — elastic methodрезона́нсный ме́тод — resonance methodме́тод реитера́ций геод. — method of reiteration, repetition methodрентгенострукту́рный ме́тод — X-ray diffraction methodме́тод реше́ния зада́чи о четвё́ртой то́чке геод. — three-point methodме́тод решета́ мат. — sieve methodру́порно-ли́нзовый ме́тод радио — horn-and-lens methodме́тод самоторможе́ния — retardation methodме́тод сви́лей — schlieren technique, schlieren methodме́тод сдви́нутого сигна́ла — offset-signal methodме́тод секу́щих — secant methodме́тод се́рого кли́на физ. — gray-wedge methodме́тод се́ток мат., вчт. — net(-point) methodме́тод сече́ний ( в расчёте напряжений в фермах) — method of sectionsме́тод сил ( определение усилий в статически неопределимой системе) — work methodсимволи́ческий ме́тод — method of complex numbersме́тод симметри́чных составля́ющих — method of symmetrical components, symmetrical component methodме́тод синхро́нного накопле́ния — synchronous storage methodме́тод скани́рования полосо́й — single-line-scan television methodме́тод скани́рования пятно́м — spot-scan photomultiplier methodме́тод смеще́ния отде́льных узло́в стр. — method of separate joint displacementме́тод совпаде́ний — coincidence methodме́тод сосредото́ченных пара́метров — lumped-parameter methodме́тод спада́ния заря́да — fall-of-charge methodспектроскопи́ческий ме́тод — spectroscopic methodме́тод спира́льного скани́рования — spiral-scan methodме́тод сплавле́ния — fusion methodме́тод сплошны́х сред ( в моделировании) — continuous field analog techniqueме́тод сре́дних квадра́тов — midsquare methodстатисти́ческий ме́тод — statistical techniqueстатисти́ческий ме́тод оце́нки — statistical estimationме́тод статисти́ческих испыта́ний — Monte Carlo methodстробоголографи́ческий ме́тод — strobo-holographic methodстробоскопи́ческий ме́тод — stroboscopic methodстру́йный ме́тод метал. — jet testступе́нчатый ме́тод ( сварки или сверления) — step-by-step methodсубъекти́вный ме́тод — subjective methodме́тод сухо́го озоле́ния — dry combustion methodме́тод сухо́го порошка́ ( в дефектоскопии) — dry methodсчё́тно-и́мпульсный ме́тод — pulse-counting methodтабли́чный ме́тод — diagram methodтелевизио́нный ме́тод электро́нной аэросъё́мки — television methodтелевизио́нный ме́тод электро́нной фотограмме́трии — television methodтенево́й ме́тод — (direct-)shadow methodтермоанемометри́ческий ме́тод — hot-wire methodтопологи́ческий ме́тод — topological methodме́тод то́чечного вплавле́ния полупр. — dot alloying methodто́чный ме́тод — exact [precision] methodме́тод травле́ния, гидри́дный — sodium hydride descalingме́тод трапецеида́льных характери́стик — Floyd's trapezoidal approximation method, approximation procedureме́тод трёх баз геод. — three-base methodме́тод триангуля́ции — triangulation methodме́тод трилатера́ции геод. — trilateration methodме́тод углово́й деформа́ции — slope-deflection methodме́тод углово́й модуля́ции — angular modulation methodме́тод удаля́емого трафаре́та полупр. — rejection mask methodме́тод удаля́емой ма́ски рад. — rejection mask methodме́тод узло́в ( в расчёте напряжении в фермах) — method of jointsме́тод узловы́х потенциа́лов — node-voltage methodме́тод ура́внивания по направле́ниям геод. — method of directions, direction methodме́тод ура́внивания по угла́м геод. — method of angles, angle methodме́тод уравнове́шивания — balancing methodме́тод усредне́ния — averaging [smoothing] methodме́тод фа́зового контра́ста ( в микроскопии) — phase contrastнаблюда́ть ме́тодом фа́зового контра́ста — examine [study] by phase contrastме́тод фа́зовой пло́скости — phase plane methodме́тод факториза́ции — factorization methodфлотацио́нный ме́тод — floatation methodме́тод формирова́ния сигна́лов цве́тности тлв. — colour-processing methodме́тод центрифуги́рования — centrifuge methodцепно́й ме́тод астр. — chain methodчи́сленный ме́тод — numerical methodме́тод Чохра́льского ( в выращивании полупроводниковых кристаллов) — Czochralski method, vertical pulling techniqueме́тод Шо́ра — Shore hardnessщупово́й ме́тод — stylus methodме́тод электрофоре́за — electrophoretic methodэмпири́ческий ме́тод — trial-and-error [cut-and-try] methodэнергети́ческий ме́тод1. косм. energy method2. стр. strain energy methodме́тод энергети́ческого бала́нса — power balance methodэргати́ческий ме́тод ( при общении человека с ЭВМ) — interactive [conversational] technique -
48 международный стандарт проведения (допинг-)тестов
международный стандарт проведения (допинг-)тестов
Обязательный международный стандарт, принятый в рамках реализации Всемирной антидопинговой программы. Главной целью данного стандарта является предоставление стандартизированного подхода к планированию эффективного тестирования и обеспечению целостности и подлинности взятых проб для антидопинговых организаций.
[Департамент лингвистических услуг Оргкомитета «Сочи 2014». Глоссарий терминов]EN
international standard for testing (IST)
Mandatory international standard developed as part of the World Anti-Doping Program. The main purpose of the IST is to ensure a standardized approach for ADOs to plan effective testing and to maintain the integrity and identity of the samples.
[Департамент лингвистических услуг Оргкомитета «Сочи 2014». Глоссарий терминов]Тематики
EN
Русско-английский словарь нормативно-технической терминологии > международный стандарт проведения (допинг-)тестов
-
49 время отладки программы
1) Electronics: program development time2) Makarov: program testing time, programme testing timeУниверсальный русско-английский словарь > время отладки программы
-
50 тест
1) General subject: Schirmer's test, multiple-choice exam (единый государственный экзамен)2) Medicine: assay, scale, screen (AIDS screen)3) Sports: tremor-test4) Engineering: test program, test routine, testing routine5) Grammar: cloze (тест, выполнение которого подразумевает заполнение удаленных из предложений слов (требуется вписать пропущенные слова))6) Psychology: culture-fair test, test form8) Oil: tst9) Immunology: check10) Ecology: procedure11) Advertising: test (для проверки)12) Network technologies: diagnostics13) Makarov: diagnostic program -
51 Programmtest
-
52 Bibliography
■ Aitchison, J. (1987). Noam Chomsky: Consensus and controversy. New York: Falmer Press.■ Anderson, J. R. (1980). Cognitive psychology and its implications. San Francisco: W. H. Freeman.■ Anderson, J. R. (1983). The architecture of cognition. Cambridge, MA: Harvard University Press.■ Anderson, J. R. (1995). Cognitive psychology and its implications (4th ed.). New York: W. H. Freeman.■ Archilochus (1971). In M. L. West (Ed.), Iambi et elegi graeci (Vol. 1). Oxford: Oxford University Press.■ Armstrong, D. M. (1990). The causal theory of the mind. In W. G. Lycan (Ed.), Mind and cognition: A reader (pp. 37-47). Cambridge, MA: Basil Blackwell. (Originally published in 1981 in The nature of mind and other essays, Ithaca, NY: University Press).■ Atkins, P. W. (1992). Creation revisited. Oxford: W. H. Freeman & Company.■ Austin, J. L. (1962). How to do things with words. Cambridge, MA: Harvard University Press.■ Bacon, F. (1878). Of the proficience and advancement of learning divine and human. In The works of Francis Bacon (Vol. 1). Cambridge, MA: Hurd & Houghton.■ Bacon, R. (1928). Opus majus (Vol. 2). R. B. Burke (Trans.). Philadelphia, PA: University of Pennsylvania Press.■ Bar-Hillel, Y. (1960). The present status of automatic translation of languages. In F. L. Alt (Ed.), Advances in computers (Vol. 1). New York: Academic Press.■ Barr, A., & E. A. Feigenbaum (Eds.) (1981). The handbook of artificial intelligence (Vol. 1). Reading, MA: Addison-Wesley.■ Barr, A., & E. A. Feigenbaum (Eds.) (1982). The handbook of artificial intelligence (Vol. 2). Los Altos, CA: William Kaufman.■ Barron, F. X. (1963). The needs for order and for disorder as motives in creative activity. In C. W. Taylor & F. X. Barron (Eds.), Scientific creativity: Its rec ognition and development (pp. 153-160). New York: Wiley.■ Bartlett, F. C. (1932). Remembering: A study in experimental and social psychology. Cambridge: Cambridge University Press.■ Bartley, S. H. (1969). Principles of perception. London: Harper & Row.■ Barzun, J. (1959). The house of intellect. New York: Harper & Row.■ Beach, F. A., D. O. Hebb, C. T. Morgan & H. W. Nissen (Eds.) (1960). The neu ropsychology of Lashley. New York: McGraw-Hill.■ Berkeley, G. (1996). Principles of human knowledge: Three Dialogues. Oxford: Oxford University Press. (Originally published in 1710.)■ Berlin, I. (1953). The hedgehog and the fox: An essay on Tolstoy's view of history. NY: Simon & Schuster.■ Bierwisch, J. (1970). Semantics. In J. Lyons (Ed.), New horizons in linguistics. Baltimore: Penguin Books.■ Black, H. C. (1951). Black's law dictionary. St. Paul, MN: West Publishing.■ Bloom, A. (1981). The linguistic shaping of thought: A study in the impact of language on thinking in China and the West. Hillsdale, NJ: Erlbaum.■ Bobrow, D. G., & D. A. Norman (1975). Some principles of memory schemata. In D. G. Bobrow & A. Collins (Eds.), Representation and understanding: Stud ies in Cognitive Science (pp. 131-149). New York: Academic Press.■ Boden, M. A. (1977). Artificial intelligence and natural man. New York: Basic Books.■ Boden, M. A. (1981). Minds and mechanisms. Ithaca, NY: Cornell University Press.■ Boden, M. A. (1990a). The creative mind: Myths and mechanisms. London: Cardinal.■ Boden, M. A. (1990b). The philosophy of artificial intelligence. Oxford: Oxford University Press.■ Boden, M. A. (1994). Precis of The creative mind: Myths and mechanisms. Behavioral and brain sciences 17, 519-570.■ Boden, M. (1996). Creativity. In M. Boden (Ed.), Artificial Intelligence (2nd ed.). San Diego: Academic Press.■ Bolter, J. D. (1984). Turing's man: Western culture in the computer age. Chapel Hill, NC: University of North Carolina Press.■ Bolton, N. (1972). The psychology of thinking. London: Methuen.■ Bourne, L. E. (1973). Some forms of cognition: A critical analysis of several papers. In R. Solso (Ed.), Contemporary issues in cognitive psychology (pp. 313324). Loyola Symposium on Cognitive Psychology (Chicago 1972). Washington, DC: Winston.■ Bransford, J. D., N. S. McCarrell, J. J. Franks & K. E. Nitsch (1977). Toward unexplaining memory. In R. Shaw & J. D. Bransford (Eds.), Perceiving, acting, and knowing (pp. 431-466). Hillsdale, NJ: Lawrence Erlbaum Associates.■ Breger, L. (1981). Freud's unfinished journey. London: Routledge & Kegan Paul.■ Brehmer, B. (1986). In one word: Not from experience. In H. R. Arkes & K. Hammond (Eds.), Judgment and decision making: An interdisciplinary reader (pp. 705-719). Cambridge: Cambridge University Press.■ Bresnan, J. (1978). A realistic transformational grammar. In M. Halle, J. Bresnan & G. A. Miller (Eds.), Linguistic theory and psychological reality (pp. 1-59). Cambridge, MA: MIT Press.■ Brislin, R. W., W. J. Lonner & R. M. Thorndike (Eds.) (1973). Cross- cultural research methods. New York: Wiley.■ Bronowski, J. (1977). A sense of the future: Essays in natural philosophy. P. E. Ariotti with R. Bronowski (Eds.). Cambridge, MA: MIT Press.■ Bronowski, J. (1978). The origins of knowledge and imagination. New Haven, CT: Yale University Press.■ Brown, R. O. (1973). A first language: The early stages. Cambridge, MA: Harvard University Press.■ Brown, T. (1970). Lectures on the philosophy of the human mind. In R. Brown (Ed.), Between Hume and Mill: An anthology of British philosophy- 1749- 1843 (pp. 330-387). New York: Random House/Modern Library.■ Bruner, J. S., J. Goodnow & G. Austin (1956). A study of thinking. New York: Wiley.■ Calvin, W. H. (1990). The cerebral symphony: Seashore reflections on the structure of consciousness. New York: Bantam.■ Campbell, J. (1982). Grammatical man: Information, entropy, language, and life. New York: Simon & Schuster.■ Campbell, J. (1989). The improbable machine. New York: Simon & Schuster.■ Carlyle, T. (1966). On heroes, hero- worship and the heroic in history. Lincoln: University of Nebraska Press. (Originally published in 1841.)■ Carnap, R. (1959). The elimination of metaphysics through logical analysis of language [Ueberwindung der Metaphysik durch logische Analyse der Sprache]. In A. J. Ayer (Ed.), Logical positivism (pp. 60-81) A. Pap (Trans). New York: Free Press. (Originally published in 1932.)■ Cassirer, E. (1946). Language and myth. New York: Harper and Brothers. Reprinted. New York: Dover Publications, 1953.■ Cattell, R. B., & H. J. Butcher (1970). Creativity and personality. In P. E. Vernon (Ed.), Creativity. Harmondsworth, England: Penguin Books.■ Caudill, M., & C. Butler (1990). Naturally intelligent systems. Cambridge, MA: MIT Press/Bradford Books.■ Chandrasekaran, B. (1990). What kind of information processing is intelligence? A perspective on AI paradigms and a proposal. In D. Partridge & R. Wilks (Eds.), The foundations of artificial intelligence: A sourcebook (pp. 14-46). Cambridge: Cambridge University Press.■ Charniak, E., & McDermott, D. (1985). Introduction to artificial intelligence. Reading, MA: Addison-Wesley.■ Chase, W. G., & H. A. Simon (1988). The mind's eye in chess. In A. Collins & E. E. Smith (Eds.), Readings in cognitive science: A perspective from psychology and artificial intelligence (pp. 461-493). San Mateo, CA: Kaufmann.■ Cheney, D. L., & R. M. Seyfarth (1990). How monkeys see the world: Inside the mind of another species. Chicago: University of Chicago Press.■ Chi, M.T.H., R. Glaser & E. Rees (1982). Expertise in problem solving. In R. J. Sternberg (Ed.), Advances in the psychology of human intelligence (pp. 7-73). Hillsdale, NJ: Lawrence Erlbaum Associates.■ Chomsky, N. (1957). Syntactic structures. The Hague: Mouton. Janua Linguarum.■ Chomsky, N. (1964). A transformational approach to syntax. In J. A. Fodor & J. J. Katz (Eds.), The structure of language: Readings in the philosophy of lan guage (pp. 211-245). Englewood Cliffs, NJ: Prentice-Hall.■ Chomsky, N. (1965). Aspects of the theory of syntax. Cambridge, MA: MIT Press.■ Chomsky, N. (1972). Language and mind (enlarged ed.). New York: Harcourt Brace Jovanovich.■ Chomsky, N. (1979). Language and responsibility. New York: Pantheon.■ Chomsky, N. (1986). Knowledge of language: Its nature, origin and use. New York: Praeger Special Studies.■ Churchland, P. (1979). Scientific realism and the plasticity of mind. New York: Cambridge University Press.■ Churchland, P. M. (1989). A neurocomputational perspective: The nature of mind and the structure of science. Cambridge, MA: MIT Press.■ Churchland, P. S. (1986). Neurophilosophy. Cambridge, MA: MIT Press/Bradford Books.■ Clark, A. (1996). Philosophical Foundations. In M. A. Boden (Ed.), Artificial in telligence (2nd ed.). San Diego: Academic Press.■ Clark, H. H., & T. B. Carlson (1981). Context for comprehension. In J. Long & A. Baddeley (Eds.), Attention and performance (Vol. 9, pp. 313-330). Hillsdale, NJ: Lawrence Erlbaum Associates.■ Clarke, A. C. (1984). Profiles of the future: An inquiry into the limits of the possible. New York: Holt, Rinehart & Winston.■ Claxton, G. (1980). Cognitive psychology: A suitable case for what sort of treatment? In G. Claxton (Ed.), Cognitive psychology: New directions (pp. 1-25). London: Routledge & Kegan Paul.■ Code, M. (1985). Order and organism. Albany, NY: State University of New York Press.■ Collingwood, R. G. (1972). The idea of history. New York: Oxford University Press.■ Coopersmith, S. (1967). The antecedents of self- esteem. San Francisco: W. H. Freeman.■ Copland, A. (1952). Music and imagination. London: Oxford University Press.■ Coren, S. (1994). The intelligence of dogs. New York: Bantam Books.■ Cottingham, J. (Ed.) (1996). Western philosophy: An anthology. Oxford: Blackwell Publishers.■ Cox, C. (1926). The early mental traits of three hundred geniuses. Stanford, CA: Stanford University Press.■ Craik, K.J.W. (1943). The nature of explanation. Cambridge: Cambridge University Press.■ Cronbach, L. J. (1990). Essentials of psychological testing (5th ed.). New York: HarperCollins.■ Cronbach, L. J., & R. E. Snow (1977). Aptitudes and instructional methods. New York: Irvington. Paperback edition, 1981.■ Csikszentmihalyi, M. (1993). The evolving self. New York: Harper Perennial.■ Culler, J. (1976). Ferdinand de Saussure. New York: Penguin Books.■ Curtius, E. R. (1973). European literature and the Latin Middle Ages. W. R. Trask (Trans.). Princeton, NJ: Princeton University Press.■ D'Alembert, J.L.R. (1963). Preliminary discourse to the encyclopedia of Diderot. R. N. Schwab (Trans.). Indianapolis: Bobbs-Merrill.■ Dampier, W. C. (1966). A history of modern science. Cambridge: Cambridge University Press.■ Darwin, C. (1911). The life and letters of Charles Darwin (Vol. 1). Francis Darwin (Ed.). New York: Appleton.■ Davidson, D. (1970) Mental events. In L. Foster & J. W. Swanson (Eds.), Experience and theory (pp. 79-101). Amherst: University of Massachussetts Press.■ Davies, P. (1995). About time: Einstein's unfinished revolution. New York: Simon & Schuster/Touchstone.■ Davis, R., & J. J. King (1977). An overview of production systems. In E. Elcock & D. Michie (Eds.), Machine intelligence 8. Chichester, England: Ellis Horwood.■ Davis, R., & D. B. Lenat (1982). Knowledge- based systems in artificial intelligence. New York: McGraw-Hill.■ Dawkins, R. (1982). The extended phenotype: The gene as the unit of selection. Oxford: W. H. Freeman.■ deKleer, J., & J. S. Brown (1983). Assumptions and ambiguities in mechanistic mental models (1983). In D. Gentner & A. L. Stevens (Eds.), Mental modes (pp. 155-190). Hillsdale, NJ: Lawrence Erlbaum Associates.■ Dennett, D. C. (1978a). Brainstorms: Philosophical essays on mind and psychology. Montgomery, VT: Bradford Books.■ Dennett, D. C. (1978b). Toward a cognitive theory of consciousness. In D. C. Dennett, Brainstorms: Philosophical Essays on Mind and Psychology. Montgomery, VT: Bradford Books.■ Dennett, D. C. (1995). Darwin's dangerous idea: Evolution and the meanings of life. New York: Simon & Schuster/Touchstone.■ Descartes, R. (1897-1910). Traite de l'homme. In Oeuvres de Descartes (Vol. 11, pp. 119-215). Paris: Charles Adam & Paul Tannery. (Originally published in 1634.)■ Descartes, R. (1950). Discourse on method. L. J. Lafleur (Trans.). New York: Liberal Arts Press. (Originally published in 1637.)■ Descartes, R. (1951). Meditation on first philosophy. L. J. Lafleur (Trans.). New York: Liberal Arts Press. (Originally published in 1641.)■ Descartes, R. (1955). The philosophical works of Descartes. E. S. Haldane and G.R.T. Ross (Trans.). New York: Dover. (Originally published in 1911 by Cambridge University Press.)■ Descartes, R. (1967). Discourse on method (Pt. V). In E. S. Haldane and G.R.T. Ross (Eds.), The philosophical works of Descartes (Vol. 1, pp. 106-118). Cambridge: Cambridge University Press. (Originally published in 1637.)■ Descartes, R. (1970a). Discourse on method. In E. S. Haldane & G.R.T. Ross (Eds.), The philosophical works of Descartes (Vol. 1, pp. 181-200). Cambridge: Cambridge University Press. (Originally published in 1637.)■ Descartes, R. (1970b). Principles of philosophy. In E. S. Haldane & G.R.T. Ross (Eds.), The philosophical works of Descartes (Vol. 1, pp. 178-291). Cambridge: Cambridge University Press. (Originally published in 1644.)■ Descartes, R. (1984). Meditations on first philosophy. In J. Cottingham, R. Stoothoff & D. Murduch (Trans.), The philosophical works of Descartes (Vol. 2). Cambridge: Cambridge University Press. (Originally published in 1641.)■ Descartes, R. (1986). Meditations on first philosophy. J. Cottingham (Trans.). Cambridge: Cambridge University Press. (Originally published in 1641 as Med itationes de prima philosophia.)■ deWulf, M. (1956). An introduction to scholastic philosophy. Mineola, NY: Dover Books.■ Dixon, N. F. (1981). Preconscious processing. London: Wiley.■ Doyle, A. C. (1986). The Boscombe Valley mystery. In Sherlock Holmes: The com plete novels and stories (Vol. 1). New York: Bantam.■ Dreyfus, H., & S. Dreyfus (1986). Mind over machine. New York: Free Press.■ Dreyfus, H. L. (1972). What computers can't do: The limits of artificial intelligence (revised ed.). New York: Harper & Row.■ Dreyfus, H. L., & S. E. Dreyfus (1986). Mind over machine: The power of human intuition and expertise in the era of the computer. New York: Free Press.■ Edelman, G. M. (1992). Bright air, brilliant fire: On the matter of the mind. New York: Basic Books.■ Ehrenzweig, A. (1967). The hidden order of art. London: Weidenfeld & Nicolson.■ Einstein, A., & L. Infeld (1938). The evolution of physics. New York: Simon & Schuster.■ Eisenstein, S. (1947). Film sense. New York: Harcourt, Brace & World.■ Everdell, W. R. (1997). The first moderns. Chicago: University of Chicago Press.■ Eysenck, M. W. (1977). Human memory: Theory, research and individual difference. Oxford: Pergamon.■ Eysenck, M. W. (1982). Attention and arousal: Cognition and performance. Berlin: Springer.■ Eysenck, M. W. (1984). A handbook of cognitive psychology. Hillsdale, NJ: Lawrence Erlbaum Associates.■ Fancher, R. E. (1979). Pioneers of psychology. New York: W. W. Norton.■ Farrell, B. A. (1981). The standing of psychoanalysis. New York: Oxford University Press.■ Feldman, D. H. (1980). Beyond universals in cognitive development. Norwood, NJ: Ablex.■ Fetzer, J. H. (1996). Philosophy and cognitive science (2nd ed.). New York: Paragon House.■ Finke, R. A. (1990). Creative imagery: Discoveries and inventions in visualization. Hillsdale, NJ: Lawrence Erlbaum Associates.■ Flanagan, O. (1991). The science of the mind. Cambridge MA: MIT Press/Bradford Books.■ Fodor, J. (1983). The modularity of mind. Cambridge, MA: MIT Press/Bradford Books.■ Frege, G. (1972). Conceptual notation. T. W. Bynum (Trans.). Oxford: Clarendon Press. (Originally published in 1879.)■ Frege, G. (1979). Logic. In H. Hermes, F. Kambartel & F. Kaulbach (Eds.), Gottlob Frege: Posthumous writings. Chicago: University of Chicago Press. (Originally published in 1879-1891.)■ Freud, S. (1959). Creative writers and day-dreaming. In J. Strachey (Ed.), The standard edition of the complete psychological works of Sigmund Freud (Vol. 9, pp. 143-153). London: Hogarth Press.■ Freud, S. (1966). Project for a scientific psychology. In J. Strachey (Ed.), The stan dard edition of the complete psychological works of Sigmund Freud (Vol. 1, pp. 295-398). London: Hogarth Press. (Originally published in 1950 as Aus den AnfaЁngen der Psychoanalyse, in London by Imago Publishing.)■ Freud, S. (1976). Lecture 18-Fixation to traumas-the unconscious. In J. Strachey (Ed.), The standard edition of the complete psychological works of Sigmund Freud (Vol. 16, p. 285). London: Hogarth Press.■ Galileo, G. (1990). Il saggiatore [The assayer]. In S. Drake (Ed.), Discoveries and opinions of Galileo. New York: Anchor Books. (Originally published in 1623.)■ Gassendi, P. (1970). Letter to Descartes. In "Objections and replies." In E. S. Haldane & G.R.T. Ross (Eds.), The philosophical works of Descartes (Vol. 2, pp. 179-240). Cambridge: Cambridge University Press. (Originally published in 1641.)■ Gazzaniga, M. S. (1988). Mind matters: How mind and brain interact to create our conscious lives. Boston: Houghton Mifflin in association with MIT Press/Bradford Books.■ Genesereth, M. R., & N. J. Nilsson (1987). Logical foundations of artificial intelligence. Palo Alto, CA: Morgan Kaufmann.■ Ghiselin, B. (1952). The creative process. New York: Mentor.■ Ghiselin, B. (1985). The creative process. Berkeley, CA: University of California Press. (Originally published in 1952.)■ Gilhooly, K. J. (1996). Thinking: Directed, undirected and creative (3rd ed.). London: Academic Press.■ Glass, A. L., K. J. Holyoak & J. L. Santa (1979). Cognition. Reading, MA: AddisonWesley.■ Goody, J. (1977). The domestication of the savage mind. Cambridge: Cambridge University Press.■ Gruber, H. E. (1980). Darwin on man: A psychological study of scientific creativity (2nd ed.). Chicago: University of Chicago Press.■ Gruber, H. E., & S. Davis (1988). Inching our way up Mount Olympus: The evolving systems approach to creative thinking. In R. J. Sternberg (Ed.), The nature of creativity: Contemporary psychological perspectives. Cambridge: Cambridge University Press.■ Guthrie, E. R. (1972). The psychology of learning. New York: Harper. (Originally published in 1935.)■ Habermas, J. (1972). Knowledge and human interests. Boston: Beacon Press.■ Hadamard, J. (1945). The psychology of invention in the mathematical field. Princeton, NJ: Princeton University Press.■ Hand, D. J. (1985). Artificial intelligence and psychiatry. Cambridge: Cambridge University Press.■ Harris, M. (1981). The language myth. London: Duckworth.■ Haugeland, J. (Ed.) (1981). Mind design: Philosophy, psychology, artificial intelligence. Cambridge, MA: MIT Press/Bradford Books.■ Haugeland, J. (1981a). The nature and plausibility of cognitivism. In J. Haugeland (Ed.), Mind design: Philosophy, psychology, artificial intelligence (pp. 243-281). Cambridge, MA: MIT Press.■ Haugeland, J. (1981b). Semantic engines: An introduction to mind design. In J. Haugeland (Ed.), Mind design: Philosophy, psychology, artificial intelligence (pp. 1-34). Cambridge, MA: MIT Press/Bradford Books.■ Haugeland, J. (1985). Artificial intelligence: The very idea. Cambridge, MA: MIT Press.■ Hawkes, T. (1977). Structuralism and semiotics. Berkeley: University of California Press.■ Hebb, D. O. (1949). The organisation of behaviour. New York: Wiley.■ Hebb, D. O. (1958). A textbook of psychology. Philadelphia: Saunders.■ Hegel, G.W.F. (1910). The phenomenology of mind. J. B. Baille (Trans.). London: Sonnenschein. (Originally published as Phaenomenologie des Geistes, 1807.)■ Heisenberg, W. (1958). Physics and philosophy. New York: Harper & Row.■ Hempel, C. G. (1966). Philosophy of natural science. Englewood Cliffs, NJ: PrenticeHall.■ Herman, A. (1997). The idea of decline in Western history. New York: Free Press.■ Herrnstein, R. J., & E. G. Boring (Eds.) (1965). A source book in the history of psy chology. Cambridge, MA: Harvard University Press.■ Herzmann, E. (1964). Mozart's creative process. In P. H. Lang (Ed.), The creative world of Mozart (pp. 17-30). London: Oldbourne Press.■ Hilgard, E. R. (1957). Introduction to psychology. London: Methuen.■ Hobbes, T. (1651). Leviathan. London: Crooke.■ Holliday, S. G., & M. J. Chandler (1986). Wisdom: Explorations in adult competence. Basel, Switzerland: Karger.■ Horn, J. L. (1986). In R. J. Sternberg (Ed.), Advances in the psychology of human intelligence (Vol. 3). Hillsdale, NJ: Erlbaum.■ Hull, C. (1943). Principles of behavior. New York: Appleton-Century-Crofts.■ Hume, D. (1955). An inquiry concerning human understanding. New York: Liberal Arts Press. (Originally published in 1748.)■ Hume, D. (1975). An enquiry concerning human understanding. In L. A. SelbyBigge (Ed.), Hume's enquiries (3rd. ed., revised P. H. Nidditch). Oxford: Clarendon. (Spelling and punctuation revised.) (Originally published in 1748.)■ Hume, D. (1978). A treatise of human nature. L. A. Selby-Bigge (Ed.), Hume's enquiries (3rd. ed., revised P. H. Nidditch). Oxford: Clarendon. (With some modifications of spelling and punctuation.) (Originally published in 1690.)■ Hunt, E. (1973). The memory we must have. In R. C. Schank & K. M. Colby (Eds.), Computer models of thought and language. (pp. 343-371) San Francisco: W. H. Freeman.■ Husserl, E. (1960). Cartesian meditations. The Hague: Martinus Nijhoff.■ Inhelder, B., & J. Piaget (1958). The growth of logical thinking from childhood to adolescence. New York: Basic Books. (Originally published in 1955 as De la logique de l'enfant a` la logique de l'adolescent. [Paris: Presses Universitaire de France])■ James, W. (1890a). The principles of psychology (Vol. 1). New York: Dover Books.■ James, W. (1890b). The principles of psychology. New York: Henry Holt.■ Jevons, W. S. (1900). The principles of science (2nd ed.). London: Macmillan.■ Johnson, G. (1986). Machinery of the mind: Inside the new science of artificial intelli gence. New York: Random House.■ Johnson-Laird, P. N. (1983). Mental models: Toward a cognitive science of language, inference, and consciousness. Cambridge, MA: Harvard University Press.■ Johnson-Laird, P. N. (1988). The computer and the mind: An introduction to cognitive science. Cambridge, MA: Harvard University Press.■ Jones, E. (1961). The life and work of Sigmund Freud. L. Trilling & S. Marcus (Eds.). London: Hogarth.■ Jones, R. V. (1985). Complementarity as a way of life. In A. P. French & P. J. Kennedy (Eds.), Niels Bohr: A centenary volume. Cambridge, MA: Harvard University Press.■ Kant, I. (1933). Critique of Pure Reason (2nd ed.). N. K. Smith (Trans.). London: Macmillan. (Originally published in 1781 as Kritik der reinen Vernunft.)■ Kant, I. (1891). Solution of the general problems of the Prolegomena. In E. Belfort (Trans.), Kant's Prolegomena. London: Bell. (With minor modifications.) (Originally published in 1783.)■ Katona, G. (1940). Organizing and memorizing: Studies in the psychology of learning and teaching. New York: Columbia University Press.■ Kaufman, A. S. (1979). Intelligent testing with the WISC-R. New York: Wiley.■ Koestler, A. (1964). The act of creation. New York: Arkana (Penguin).■ Kohlberg, L. (1971). From is to ought. In T. Mischel (Ed.), Cognitive development and epistemology. (pp. 151-235) New York: Academic Press.■ KoЁhler, W. (1925). The mentality of apes. New York: Liveright.■ KoЁhler, W. (1927). The mentality of apes (2nd ed.). Ella Winter (Trans.). London: Routledge & Kegan Paul.■ KoЁhler, W. (1930). Gestalt psychology. London: G. Bell.■ KoЁhler, W. (1947). Gestalt psychology. New York: Liveright.■ KoЁhler, W. (1969). The task of Gestalt psychology. Princeton, NJ: Princeton University Press.■ Kuhn, T. (1970). The structure of scientific revolutions (2nd ed.). Chicago: University of Chicago Press.■ Langer, E. J. (1989). Mindfulness. Reading, MA: Addison-Wesley.■ Langer, S. (1962). Philosophical sketches. Baltimore: Johns Hopkins University Press.■ Langley, P., H. A. Simon, G. L. Bradshaw & J. M. Zytkow (1987). Scientific dis covery: Computational explorations of the creative process. Cambridge, MA: MIT Press.■ Lashley, K. S. (1951). The problem of serial order in behavior. In L. A. Jeffress (Ed.), Cerebral mechanisms in behavior, the Hixon Symposium (pp. 112-146) New York: Wiley.■ LeDoux, J. E., & W. Hirst (1986). Mind and brain: Dialogues in cognitive neuroscience. Cambridge: Cambridge University Press.■ Lehnert, W. (1978). The process of question answering. Hillsdale, NJ: Lawrence Erlbaum Associates.■ Leiber, J. (1991). Invitation to cognitive science. Oxford: Blackwell.■ Lenat, D. B., & G. Harris (1978). Designing a rule system that searches for scientific discoveries. In D. A. Waterman & F. Hayes-Roth (Eds.), Pattern directed inference systems (pp. 25-52) New York: Academic Press.■ Levenson, T. (1995). Measure for measure: A musical history of science. New York: Touchstone. (Originally published in 1994.)■ Leґvi-Strauss, C. (1963). Structural anthropology. C. Jacobson & B. Grundfest Schoepf (Trans.). New York: Basic Books. (Originally published in 1958.)■ Levine, M. W., & J. M. Schefner (1981). Fundamentals of sensation and perception. London: Addison-Wesley.■ Lewis, C. I. (1946). An analysis of knowledge and valuation. LaSalle, IL: Open Court.■ Lighthill, J. (1972). A report on artificial intelligence. Unpublished manuscript, Science Research Council.■ Lipman, M., A. M. Sharp & F. S. Oscanyan (1980). Philosophy in the classroom. Philadelphia: Temple University Press.■ Lippmann, W. (1965). Public opinion. New York: Free Press. (Originally published in 1922.)■ Locke, J. (1956). An essay concerning human understanding. Chicago: Henry Regnery Co. (Originally published in 1690.)■ Locke, J. (1975). An essay concerning human understanding. P. H. Nidditch (Ed.). Oxford: Clarendon. (Originally published in 1690.) (With spelling and punctuation modernized and some minor modifications of phrasing.)■ Lopate, P. (1994). The art of the personal essay. New York: Doubleday/Anchor Books.■ Lorimer, F. (1929). The growth of reason. London: Kegan Paul. Machlup, F., & U. Mansfield (Eds.) (1983). The study of information. New York: Wiley.■ Manguel, A. (1996). A history of reading. New York: Viking.■ Markey, J. F. (1928). The symbolic process. London: Kegan Paul.■ Martin, R. M. (1969). On Ziff's "Natural and formal languages." In S. Hook (Ed.), Language and philosophy: A symposium (pp. 249-263). New York: New York University Press.■ Mazlish, B. (1993). The fourth discontinuity: the co- evolution of humans and machines. New Haven, CT: Yale University Press.■ McCarthy, J., & P. J. Hayes (1969). Some philosophical problems from the standpoint of artificial intelligence. In B. Meltzer & D. Michie (Eds.), Machine intelligence 4. Edinburgh: Edinburgh University Press.■ McClelland, J. L., D. E. Rumelhart & G. E. Hinton (1986). The appeal of parallel distributed processing. In D. E. Rumelhart, J. L. McClelland & the PDP Research Group (Eds.), Parallel distributed processing: Explorations in the mi crostructure of cognition (Vol. 1, pp. 3-40). Cambridge, MA: MIT Press/ Bradford Books.■ McCorduck, P. (1979). Machines who think. San Francisco: W. H. Freeman.■ McLaughlin, T. (1970). Music and communication. London: Faber & Faber.■ Mednick, S. A. (1962). The associative basis of the creative process. Psychological Review 69, 431-436.■ Meehl, P. E., & C. J. Golden (1982). Taxometric methods. In Kendall, P. C., & Butcher, J. N. (Eds.), Handbook of research methods in clinical psychology (pp. 127-182). New York: Wiley.■ Mehler, J., E.C.T. Walker & M. Garrett (Eds.) (1982). Perspectives on mental rep resentation: Experimental and theoretical studies of cognitive processes and ca pacities. Hillsdale, NJ: Lawrence Erlbaum Associates.■ Mill, J. S. (1900). A system of logic, ratiocinative and inductive: Being a connected view of the principles of evidence and the methods of scientific investigation. London: Longmans, Green.■ Miller, G. A. (1979, June). A very personal history. Talk to the Cognitive Science Workshop, Cambridge, MA.■ Miller, J. (1983). States of mind. New York: Pantheon Books.■ Minsky, M. (1975). A framework for representing knowledge. In P. H. Winston (Ed.), The psychology of computer vision (pp. 211-277). New York: McGrawHill.■ Minsky, M., & S. Papert (1973). Artificial intelligence. Condon Lectures, Oregon State System of Higher Education, Eugene, Oregon.■ Minsky, M. L. (1986). The society of mind. New York: Simon & Schuster.■ Mischel, T. (1976). Psychological explanations and their vicissitudes. In J. K. Cole & W. J. Arnold (Eds.), Nebraska Symposium on motivation (Vol. 23). Lincoln, NB: University of Nebraska Press.■ Morford, M.P.O., & R. J. Lenardon (1995). Classical mythology (5th ed.). New York: Longman.■ Murdoch, I. (1954). Under the net. New York: Penguin.■ Nagel, E. (1959). Methodological issues in psychoanalytic theory. In S. Hook (Ed.), Psychoanalysis, scientific method, and philosophy: A symposium. New York: New York University Press.■ Nagel, T. (1979). Mortal questions. London: Cambridge University Press.■ Nagel, T. (1986). The view from nowhere. Oxford: Oxford University Press.■ Neisser, U. (1967). Cognitive psychology. New York: Appleton-Century-Crofts.■ Neisser, U. (1972). Changing conceptions of imagery. In P. W. Sheehan (Ed.), The function and nature of imagery (pp. 233-251). London: Academic Press.■ Neisser, U. (1976). Cognition and reality. San Francisco: W. H. Freeman.■ Neisser, U. (1978). Memory: What are the important questions? In M. M. Gruneberg, P. E. Morris & R. N. Sykes (Eds.), Practical aspects of memory (pp. 3-24). London: Academic Press.■ Neisser, U. (1979). The concept of intelligence. In R. J. Sternberg & D. K. Detterman (Eds.), Human intelligence: Perspectives on its theory and measurement (pp. 179-190). Norwood, NJ: Ablex.■ Nersessian, N. (1992). How do scientists think? Capturing the dynamics of conceptual change in science. In R. N. Giere (Ed.), Cognitive models of science (pp. 3-44). Minneapolis: University of Minnesota Press.■ Newell, A. (1973a). Artificial intelligence and the concept of mind. In R. C. Schank & K. M. Colby (Eds.), Computer models of thought and language (pp. 1-60). San Francisco: W. H. Freeman.■ Newell, A. (1973b). You can't play 20 questions with nature and win. In W. G. Chase (Ed.), Visual information processing (pp. 283-310). New York: Academic Press.■ Newell, A., & H. A. Simon (1963). GPS: A program that simulates human thought. In E. A. Feigenbaum & J. Feldman (Eds.), Computers and thought (pp. 279-293). New York & McGraw-Hill.■ Newell, A., & H. A. Simon (1972). Human problem solving. Englewood Cliffs, NJ: Prentice-Hall.■ Nietzsche, F. (1966). Beyond good and evil. W. Kaufmann (Trans.). New York: Vintage. (Originally published in 1885.)■ Nilsson, N. J. (1971). Problem- solving methods in artificial intelligence. New York: McGraw-Hill.■ Nussbaum, M. C. (1978). Aristotle's Princeton University Press. De Motu Anamalium. Princeton, NJ:■ Oersted, H. C. (1920). Thermo-electricity. In Kirstine Meyer (Ed.), H. C. Oersted, Natuurvidenskabelige Skrifter (Vol. 2). Copenhagen: n.p. (Originally published in 1830 in The Edinburgh encyclopaedia.)■ Ong, W. J. (1982). Orality and literacy: The technologizing of the word. London: Methuen.■ Onians, R. B. (1954). The origins of European thought. Cambridge, MA: Cambridge University Press.■ Osgood, C. E. (1960). Method and theory in experimental psychology. New York: Oxford University Press. (Originally published in 1953.)■ Osgood, C. E. (1966). Language universals and psycholinguistics. In J. H. Greenberg (Ed.), Universals of language (2nd ed., pp. 299-322). Cambridge, MA: MIT Press.■ Palmer, R. E. (1969). Hermeneutics. Evanston, IL: Northwestern University Press.■ Peirce, C. S. (1934). Some consequences of four incapacities-Man, a sign. In C. Hartsborne & P. Weiss (Eds.), Collected papers of Charles Saunders Peirce (Vol. 5, pp. 185-189). Cambridge, MA: Harvard University Press.■ Penfield, W. (1959). In W. Penfield & L. Roberts, Speech and brain mechanisms. Princeton, NJ: Princeton University Press.■ Penrose, R. (1994). Shadows of the mind: A search for the missing science of conscious ness. Oxford: Oxford University Press.■ Perkins, D. N. (1981). The mind's best work. Cambridge, MA: Harvard University Press.■ Peterfreund, E. (1986). The heuristic approach to psychoanalytic therapy. In■ J. Reppen (Ed.), Analysts at work, (pp. 127-144). Hillsdale, NJ: Analytic Press.■ Piaget, J. (1952). The origin of intelligence in children. New York: International Universities Press. (Originally published in 1936.)■ Piaget, J. (1954). Le langage et les opeґrations intellectuelles. Proble` mes de psycho linguistique. Symposium de l'Association de Psychologie Scientifique de Langue Francёaise. Paris: Presses Universitaires de France.■ Piaget, J. (1977). Problems of equilibration. In H. E. Gruber & J. J. Voneche (Eds.), The essential Piaget (pp. 838-841). London: Routlege & Kegan Paul. (Originally published in 1975 as L'eґquilibration des structures cognitives [Paris: Presses Universitaires de France].)■ Piaget, J., & B. Inhelder. (1973). Memory and intelligence. New York: Basic Books.■ Pinker, S. (1994). The language instinct. New York: Morrow.■ Pinker, S. (1996). Facts about human language relevant to its evolution. In J.-P. Changeux & J. Chavaillon (Eds.), Origins of the human brain. A symposium of the Fyssen foundation (pp. 262-283). Oxford: Clarendon Press. Planck, M. (1949). Scientific autobiography and other papers. F. Gaynor (Trans.). New York: Philosophical Library.■ Planck, M. (1990). Wissenschaftliche Selbstbiographie. W. Berg (Ed.). Halle, Germany: Deutsche Akademie der Naturforscher Leopoldina.■ Plato (1892). Meno. In The Dialogues of Plato (B. Jowett, Trans.; Vol. 2). New York: Clarendon. (Originally published circa 380 B.C.)■ Poincareґ, H. (1913). Mathematical creation. In The foundations of science. G. B. Halsted (Trans.). New York: Science Press.■ Poincareґ, H. (1921). The foundations of science: Science and hypothesis, the value of science, science and method. G. B. Halstead (Trans.). New York: Science Press.■ Poincareґ, H. (1929). The foundations of science: Science and hypothesis, the value of science, science and method. New York: Science Press.■ Poincareґ, H. (1952). Science and method. F. Maitland (Trans.) New York: Dover.■ Polya, G. (1945). How to solve it. Princeton, NJ: Princeton University Press.■ Polanyi, M. (1958). Personal knowledge. London: Routledge & Kegan Paul.■ Popper, K. (1968). Conjectures and refutations: The growth of scientific knowledge. New York: Harper & Row/Basic Books.■ Popper, K., & J. Eccles (1977). The self and its brain. New York: Springer-Verlag.■ Popper, K. R. (1959). The logic of scientific discovery. London: Hutchinson.■ Putnam, H. (1975). Mind, language and reality: Philosophical papers (Vol. 2). Cambridge: Cambridge University Press.■ Putnam, H. (1987). The faces of realism. LaSalle, IL: Open Court.■ Pylyshyn, Z. W. (1981). The imagery debate: Analog media versus tacit knowledge. In N. Block (Ed.), Imagery (pp. 151-206). Cambridge, MA: MIT Press.■ Pylyshyn, Z. W. (1984). Computation and cognition: Towards a foundation for cog nitive science. Cambridge, MA: MIT Press/Bradford Books.■ Quillian, M. R. (1968). Semantic memory. In M. Minsky (Ed.), Semantic information processing (pp. 216-260). Cambridge, MA: MIT Press.■ Quine, W.V.O. (1960). Word and object. Cambridge, MA: Harvard University Press.■ Rabbitt, P.M.A., & S. Dornic (Eds.). Attention and performance (Vol. 5). London: Academic Press.■ Rawlins, G.J.E. (1997). Slaves of the Machine: The quickening of computer technology. Cambridge, MA: MIT Press/Bradford Books.■ Reid, T. (1970). An inquiry into the human mind on the principles of common sense. In R. Brown (Ed.), Between Hume and Mill: An anthology of British philosophy- 1749- 1843 (pp. 151-178). New York: Random House/Modern Library.■ Reitman, W. (1970). What does it take to remember? In D. A. Norman (Ed.), Models of human memory (pp. 470-510). London: Academic Press.■ Ricoeur, P. (1974). Structure and hermeneutics. In D. I. Ihde (Ed.), The conflict of interpretations: Essays in hermeneutics (pp. 27-61). Evanston, IL: Northwestern University Press.■ Robinson, D. N. (1986). An intellectual history of psychology. Madison: University of Wisconsin Press.■ Rorty, R. (1979). Philosophy and the mirror of nature. Princeton, NJ: Princeton University Press.■ Rosch, E. (1977). Human categorization. In N. Warren (Ed.), Studies in cross cultural psychology (Vol. 1, pp. 1-49) London: Academic Press.■ Rosch, E. (1978). Principles of categorization. In E. Rosch & B. B. Lloyd (Eds.), Cognition and categorization (pp. 27-48). Hillsdale, NJ: Lawrence Erlbaum Associates.■ Rosch, E., & B. B. Lloyd (1978). Principles of categorization. In E. Rosch & B. B. Lloyd (Eds.), Cognition and categorization. Hillsdale, NJ: Lawrence Erlbaum Associates.■ Rose, S. (1970). The chemistry of life. Baltimore: Penguin Books.■ Rose, S. (1976). The conscious brain (updated ed.). New York: Random House.■ Rose, S. (1993). The making of memory: From molecules to mind. New York: Anchor Books. (Originally published in 1992)■ Roszak, T. (1994). The cult of information: A neo- Luddite treatise on high- tech, artificial intelligence, and the true art of thinking (2nd ed.). Berkeley: University of California Press.■ Royce, J. R., & W. W. Rozeboom (Eds.) (1972). The psychology of knowing. New York: Gordon & Breach.■ Rumelhart, D. E. (1977). Introduction to human information processing. New York: Wiley.■ Rumelhart, D. E. (1980). Schemata: The building blocks of cognition. In R. J. Spiro, B. Bruce & W. F. Brewer (Eds.), Theoretical issues in reading comprehension. Hillsdale, NJ: Lawrence Erlbaum Associates.■ Rumelhart, D. E., & J. L. McClelland (1986). On learning the past tenses of English verbs. In J. L. McClelland & D. E. Rumelhart (Eds.), Parallel distributed processing: Explorations in the microstructure of cognition (Vol. 2). Cambridge, MA: MIT Press.■ Rumelhart, D. E., P. Smolensky, J. L. McClelland & G. E. Hinton (1986). Schemata and sequential thought processes in PDP models. In J. L. McClelland, D. E. Rumelhart & the PDP Research Group (Eds.), Parallel Distributed Processing (Vol. 2, pp. 7-57). Cambridge, MA: MIT Press.■ Russell, B. (1927). An outline of philosophy. London: G. Allen & Unwin.■ Russell, B. (1961). History of Western philosophy. London: George Allen & Unwin.■ Russell, B. (1965). How I write. In Portraits from memory and other essays. London: Allen & Unwin.■ Russell, B. (1992). In N. Griffin (Ed.), The selected letters of Bertrand Russell (Vol. 1), The private years, 1884- 1914. Boston: Houghton Mifflin. Ryecroft, C. (1966). Psychoanalysis observed. London: Constable.■ Sagan, C. (1978). The dragons of Eden: Speculations on the evolution of human intel ligence. New York: Ballantine Books.■ Salthouse, T. A. (1992). Expertise as the circumvention of human processing limitations. In K. A. Ericsson & J. Smith (Eds.), Toward a general theory of expertise: Prospects and limits (pp. 172-194). Cambridge: Cambridge University Press.■ Sanford, A. J. (1987). The mind of man: Models of human understanding. New Haven, CT: Yale University Press.■ Sapir, E. (1921). Language. New York: Harcourt, Brace, and World.■ Sapir, E. (1964). Culture, language, and personality. Berkeley: University of California Press. (Originally published in 1941.)■ Sapir, E. (1985). The status of linguistics as a science. In D. G. Mandelbaum (Ed.), Selected writings of Edward Sapir in language, culture and personality (pp. 160166). Berkeley: University of California Press. (Originally published in 1929).■ Scardmalia, M., & C. Bereiter (1992). Literate expertise. In K. A. Ericsson & J. Smith (Eds.), Toward a general theory of expertise: Prospects and limits (pp. 172-194). Cambridge: Cambridge University Press.■ Schafer, R. (1954). Psychoanalytic interpretation in Rorschach testing. New York: Grune & Stratten.■ Schank, R. C. (1973). Identification of conceptualizations underlying natural language. In R. C. Schank & K. M. Colby (Eds.), Computer models of thought and language (pp. 187-248). San Francisco: W. H. Freeman.■ Schank, R. C. (1976). The role of memory in language processing. In C. N. Cofer (Ed.), The structure of human memory. (pp. 162-189) San Francisco: W. H. Freeman.■ Schank, R. C. (1986). Explanation patterns: Understanding mechanically and creatively. Hillsdale, NJ: Lawrence Erlbaum Associates.■ Schank, R. C., & R. P. Abelson (1977). Scripts, plans, goals, and understanding. Hillsdale, NJ: Lawrence Erlbaum Associates.■ SchroЁdinger, E. (1951). Science and humanism. Cambridge: Cambridge University Press.■ Searle, J. R. (1981a). Minds, brains, and programs. In J. Haugeland (Ed.), Mind design: Philosophy, psychology, artificial intelligence (pp. 282-306). Cambridge, MA: MIT Press.■ Searle, J. R. (1981b). Minds, brains and programs. In D. Hofstadter & D. Dennett (Eds.), The mind's I (pp. 353-373). New York: Basic Books.■ Searle, J. R. (1983). Intentionality. New York: Cambridge University Press.■ Serres, M. (1982). The origin of language: Biology, information theory, and thermodynamics. M. Anderson (Trans.). In J. V. Harari & D. F. Bell (Eds.), Hermes: Literature, science, philosophy (pp. 71-83). Baltimore: Johns Hopkins University Press.■ Simon, H. A. (1966). Scientific discovery and the psychology of problem solving. In R. G. Colodny (Ed.), Mind and cosmos: Essays in contemporary science and philosophy (pp. 22-40). Pittsburgh: University of Pittsburgh Press.■ Simon, H. A. (1979). Models of thought. New Haven, CT: Yale University Press.■ Simon, H. A. (1989). The scientist as a problem solver. In D. Klahr & K. Kotovsky (Eds.), Complex information processing: The impact of Herbert Simon. Hillsdale, N.J.: Lawrence Erlbaum Associates.■ Simon, H. A., & C. Kaplan (1989). Foundations of cognitive science. In M. Posner (Ed.), Foundations of cognitive science (pp. 1-47). Cambridge, MA: MIT Press.■ Simonton, D. K. (1988). Creativity, leadership and chance. In R. J. Sternberg (Ed.), The nature of creativity. Cambridge: Cambridge University Press.■ Skinner, B. F. (1974). About behaviorism. New York: Knopf.■ Smith, E. E. (1988). Concepts and thought. In J. Sternberg & E. E. Smith (Eds.), The psychology of human thought (pp. 19-49). Cambridge: Cambridge University Press.■ Smith, E. E. (1990). Thinking: Introduction. In D. N. Osherson & E. E. Smith (Eds.), Thinking. An invitation to cognitive science. (Vol. 3, pp. 1-2). Cambridge, MA: MIT Press.■ Socrates. (1958). Meno. In E. H. Warmington & P. O. Rouse (Eds.), Great dialogues of Plato W.H.D. Rouse (Trans.). New York: New American Library. (Original publication date unknown.)■ Solso, R. L. (1974). Theories of retrieval. In R. L. Solso (Ed.), Theories in cognitive psychology. Potomac, MD: Lawrence Erlbaum Associates.■ Spencer, H. (1896). The principles of psychology. New York: Appleton-CenturyCrofts.■ Steiner, G. (1975). After Babel: Aspects of language and translation. New York: Oxford University Press.■ Sternberg, R. J. (1977). Intelligence, information processing, and analogical reasoning. Hillsdale, NJ: Lawrence Erlbaum Associates.■ Sternberg, R. J. (1994). Intelligence. In R. J. Sternberg, Thinking and problem solving. San Diego: Academic Press.■ Sternberg, R. J., & J. E. Davidson (1985). Cognitive development in gifted and talented. In F. D. Horowitz & M. O'Brien (Eds.), The gifted and talented (pp. 103-135). Washington, DC: American Psychological Association.■ Storr, A. (1993). The dynamics of creation. New York: Ballantine Books. (Originally published in 1972.)■ Stumpf, S. E. (1994). Philosophy: History and problems (5th ed.). New York: McGraw-Hill.■ Sulloway, F. J. (1996). Born to rebel: Birth order, family dynamics, and creative lives. New York: Random House/Vintage Books.■ Thorndike, E. L. (1906). Principles of teaching. New York: A. G. Seiler.■ Thorndike, E. L. (1970). Animal intelligence: Experimental studies. Darien, CT: Hafner Publishing Co. (Originally published in 1911.)■ Titchener, E. B. (1910). A textbook of psychology. New York: Macmillan.■ Titchener, E. B. (1914). A primer of psychology. New York: Macmillan.■ Toulmin, S. (1957). The philosophy of science. London: Hutchinson.■ Tulving, E. (1972). Episodic and semantic memory. In E. Tulving & W. Donaldson (Eds.), Organisation of memory. London: Academic Press.■ Turing, A. (1946). In B. E. Carpenter & R. W. Doran (Eds.), ACE reports of 1946 and other papers. Cambridge, MA: MIT Press.■ Turkle, S. (1984). Computers and the second self: Computers and the human spirit. New York: Simon & Schuster.■ Tyler, S. A. (1978). The said and the unsaid: Mind, meaning, and culture. New York: Academic Press.■ van Heijenoort (Ed.) (1967). From Frege to Goedel. Cambridge: Harvard University Press.■ Varela, F. J. (1984). The creative circle: Sketches on the natural history of circularity. In P. Watzlawick (Ed.), The invented reality (pp. 309-324). New York: W. W. Norton.■ Voltaire (1961). On the Penseґs of M. Pascal. In Philosophical letters (pp. 119-146). E. Dilworth (Trans.). Indianapolis: Bobbs-Merrill.■ Wagman, M. (1991a). Artificial intelligence and human cognition: A theoretical inter comparison of two realms of intellect. Westport, CT: Praeger.■ Wagman, M. (1991b). Cognitive science and concepts of mind: Toward a general theory of human and artificial intelligence. Westport, CT: Praeger.■ Wagman, M. (1993). Cognitive psychology and artificial intelligence: Theory and re search in cognitive science. Westport, CT: Praeger.■ Wagman, M. (1995). The sciences of cognition: Theory and research in psychology and artificial intelligence. Westport, CT: Praeger.■ Wagman, M. (1996). Human intellect and cognitive science: Toward a general unified theory of intelligence. Westport, CT: Praeger.■ Wagman, M. (1997a). Cognitive science and the symbolic operations of human and artificial intelligence: Theory and research into the intellective processes. Westport, CT: Praeger.■ Wagman, M. (1997b). The general unified theory of intelligence: Central conceptions and specific application to domains of cognitive science. Westport, CT: Praeger.■ Wagman, M. (1998a). Cognitive science and the mind- body problem: From philosophy to psychology to artificial intelligence to imaging of the brain. Westport, CT: Praeger.■ Wagman, M. (1998b). Language and thought in humans and computers: Theory and research in psychology, artificial intelligence, and neural science. Westport, CT: Praeger.■ Wagman, M. (1998c). The ultimate objectives of artificial intelligence: Theoretical and research foundations, philosophical and psychological implications. Westport, CT: Praeger.■ Wagman, M. (1999). The human mind according to artificial intelligence: Theory, re search, and implications. Westport, CT: Praeger.■ Wagman, M. (2000). Scientific discovery processes in humans and computers: Theory and research in psychology and artificial intelligence. Westport, CT: Praeger.■ Wall, R. (1972). Introduction to mathematical linguistics. Englewood Cliffs, NJ: Prentice-Hall.■ Wallas, G. (1926). The Art of Thought. New York: Harcourt, Brace & Co.■ Wason, P. (1977). Self contradictions. In P. Johnson-Laird & P. Wason (Eds.), Thinking: Readings in cognitive science. Cambridge: Cambridge University Press.■ Wason, P. C., & P. N. Johnson-Laird. (1972). Psychology of reasoning: Structure and content. Cambridge, MA: Harvard University Press.■ Watson, J. (1930). Behaviorism. New York: W. W. Norton.■ Watzlawick, P. (1984). Epilogue. In P. Watzlawick (Ed.), The invented reality. New York: W. W. Norton, 1984.■ Weinberg, S. (1977). The first three minutes: A modern view of the origin of the uni verse. New York: Basic Books.■ Weisberg, R. W. (1986). Creativity: Genius and other myths. New York: W. H. Freeman.■ Weizenbaum, J. (1976). Computer power and human reason: From judgment to cal culation. San Francisco: W. H. Freeman.■ Wertheimer, M. (1945). Productive thinking. New York: Harper & Bros.■ Whitehead, A. N. (1925). Science and the modern world. New York: Macmillan.■ Whorf, B. L. (1956). In J. B. Carroll (Ed.), Language, thought and reality: Selected writings of Benjamin Lee Whorf. Cambridge, MA: MIT Press.■ Whyte, L. L. (1962). The unconscious before Freud. New York: Anchor Books.■ Wiener, N. (1954). The human use of human beings. Boston: Houghton Mifflin.■ Wiener, N. (1964). God & Golem, Inc.: A comment on certain points where cybernetics impinges on religion. Cambridge, MA: MIT Press.■ Winograd, T. (1972). Understanding natural language. New York: Academic Press.■ Winston, P. H. (1987). Artificial intelligence: A perspective. In E. L. Grimson & R. S. Patil (Eds.), AI in the 1980s and beyond (pp. 1-12). Cambridge, MA: MIT Press.■ Winston, P. H. (Ed.) (1975). The psychology of computer vision. New York: McGrawHill.■ Wittgenstein, L. (1953). Philosophical investigations. Oxford: Basil Blackwell.■ Wittgenstein, L. (1958). The blue and brown books. New York: Harper Colophon.■ Woods, W. A. (1975). What's in a link: Foundations for semantic networks. In D. G. Bobrow & A. Collins (Eds.), Representations and understanding: Studies in cognitive science (pp. 35-84). New York: Academic Press.■ Woodworth, R. S. (1938). Experimental psychology. New York: Holt; London: Methuen (1939).■ Wundt, W. (1904). Principles of physiological psychology (Vol. 1). E. B. Titchener (Trans.). New York: Macmillan.■ Wundt, W. (1907). Lectures on human and animal psychology. J. E. Creighton & E. B. Titchener (Trans.). New York: Macmillan.■ Young, J. Z. (1978). Programs of the brain. New York: Oxford University Press.■ Ziman, J. (1978). Reliable knowledge: An exploration of the grounds for belief in science. Cambridge: Cambridge University Press.Historical dictionary of quotations in cognitive science > Bibliography
-
53 программа тестирования
1) Sports: testing program2) Engineering: test program3) Information technology: exerciser4) Microelectronics: testout program5) Network technologies: test6) Marketology: trial program (продукта)Универсальный русско-английский словарь > программа тестирования
-
54 Prüfungsprogramm
Prüfungsprogramm n RW (AE) audit program, (BE) audit programme, audit schedule* * ** * *Prüfungsprogramm
testing program(me), (Revision) audit program(me) -
55 программа экспериментальной отработки комплексная
Русско-английский глоссарий по космической технике > программа экспериментальной отработки комплексная
-
56 программный контроль
1) Computers: check2) Engineering: program check, programed check (цифровой электронной вычислительной машины), programmed check (цифровой электронной вычислительной машины), programming check, routine check3) Information technology: program check (в отличие от аппаратного), program testing, programmed check (в отличие от аппаратного), programming check (в отличие от аппаратного), routine check (в отличие от аппаратного)4) Programming: software audit5) Robots: software check (в отличие от аппаратного)Универсальный русско-английский словарь > программный контроль
-
57 тест-программа
1) Engineering: test routine2) Economy: checking program3) Information technology: test problem4) Astronautics: test program5) Automation: testing program -
58 Prüfungsplan
Prüfungsplan m RW audit plan* * *m < Rechnung> audit plan* * *Prüfungsplan
(Revision) audit program(me);
• Prüfungsposten (Abnahme) inspection lot;
• Prüfungsprogramm testing program(me), (Revision) audit program(me);
• Prüfungsprotokoll test certificate, (Revision) accountant’s certificate, (Warenbeschaffung) certificate of inspection;
• Prüfungsrecht (Revision) audit privilege;
• Prüfungsrichtlinien (Revision) audit standards;
• Prüfungsschein (Lagerei) certificate of inspection;
• Prüfungssiegel inspection stamp;
• Prüfungsstelle control office, (Patentamt) examination, (Spediteur) inspection bureau;
• Prüfungstermin time of examination, (im Konkurs) public examination, audit date;
• Prüfungsumfang (Abnahme) amount of inspection, (Revision) audit scope, scope of audit;
• Prüfungsverfahren examination system, inspection (screening) process, (Revision) auditing procedure, (Statistik) test. -
59 контрольный прогон программы
Information technology: execution testing, execution testing of a programУниверсальный русско-английский словарь > контрольный прогон программы
-
60 программа совместных испытаний
1) Aviation: joint testing (например, самолетов)2) Advertising: joint testing programУниверсальный русско-английский словарь > программа совместных испытаний
См. также в других словарях:
testing — test‧ing [ˈtestɪŋ] noun [uncountable] 1. the process of checking something to see if it works, if it is suitable etc: • The company specializes in software testing and software inspection. • All our desktop computers undergo rigorous testing. •… … Financial and business terms
testing program — index experiment, research Burton s Legal Thesaurus. William C. Burton. 2006 … Law dictionary
Program animation — is a particular feature of some Testing tools allowing programs to be executed step by step at either source code level or machine code level. Some tools permit animation at both levels depending upon the availability of data collected at compile … Wikipedia
testing — See test. bench t. t. of a device against specifications in a simulated (nonliving) environment. contrast sensitivity t. examination of the visual recognition of the variation in brightness of an object. genetic t … Medical dictionary
Software testing — is an empirical investigation conducted to provide stakeholders with information about the quality of the product or service under test [ [http://www.kaner.com/pdfs/ETatQAI.pdf Exploratory Testing] , Cem Kaner, Florida Institute of Technology,… … Wikipedia
Standards for Educational and Psychological Testing — The Standards for Educational and Psychological Testing is a set of testing standards developed jointly by the American Educational Research Association (AERA), American Psychological Association (APA), and the National Council on Measurement in… … Wikipedia
Equine drug testing — Racehorse drug testing began in the early 1900s. It is the longest established, broadest in scope, and possibly the most sensitive drug testing program in existence. Racehorse drug testing is performed within an extremely stringent regulatory… … Wikipedia
Static program analysis — This article is about certain software quality assessment methods. For the statistical method, see Static analysis. Static program analysis (also Static code analysis or SCA) is the analysis of computer software that is performed without actually … Wikipedia
saturation testing — Program testing with a large volume of messages intended to expose errors that occur infrequently and can be triggered by such rare coincidences as two different messages arriving at the same time. Also called volume testing … IT glossary of terms, acronyms and abbreviations
Mutation testing — For the biological term, see: Gene mutation analysis. Software Testing portal Mutation testing (or Mutation analysis or Program mutation) is a method of software testing, which involves modifying programs source code or byte code in small ways … Wikipedia
Fuzz testing — Fuzzing redirects here. For other uses, see Fuzz (disambiguation). Fuzz testing or fuzzing is a software testing technique, often automated or semi automated, that involves providing invalid, unexpected, or random data to the inputs of a computer … Wikipedia