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1 Computing Significance, Status, Challenges COMPUTING IN SOCIETY Computing is inextricably and ubiquitously woven into the fabric of modern life. In nearly all sectors of the economy, computing makes it possible to deliver services and products of higher quality to more people in less time than would otherwise be possible (Box 1.1~. As seen from the perspective of other technical fields (Box 1.2) and in terms of its potential to enhance U.S. industrial strength and the national defense (Box 1.3), computing is a truly enabling and central technology. Consider: In large businesses, electronic mail enabled by computing is increasingly common. In communications, computing makes it possible to switch and route over 100 million long-distance telephone calls per day. In aeronautics, computer-aided design techniques are expected to save Boeing as much as a billion dollars in the development of the 777 airliner. In pharmaceuticals, computing enables chemists to conduct sys- tematic searches for compounds that will fight specific diseases. In automobile engineering, computing makes it possible to simulate automobile crash tests that would otherwise cost hundreds of thou- sands of dollars apiece.2 In the oil industry, computing has saved hundreds of millions 13

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14 COMPUTING THE FUTURE . ......................................... ..... . . .. .. .. . . . . . . . . . . . . . . ............................................................. T ~.~. ~.~. ~,.~.~.~.~ . . : ... ..... ... .. ....... . . . . . .. . . .: , _"''a"""~"""~.," ''''' ''''"'''''"''''' '''''''''' '' ''"'''""'""''''' .............. i. . . . . . . . . . . . . . . . ~.. A ......... ........... . . mt er ~: ~l Me WAS :0t=~:r:~mo~.~: ~ :~- ................... . . vI~61~ 1,=3.te...~t::c~0 per '~8 task ma| ., . . .. , . .. .. , .. - . ... . . . . . . C.~.. pew - p;~sal:~ ]1~ `~t=~\Q mat '.'.~'. "'''c""a'.""""'""' "' ''' ' ' ' ' " ' ' ' " '' ' "''' "" ' '" ''' ' ' "" ... . . . . .. . .. .. . . . .. . . . .... . . . i. * . . .. . . ~ - ~ i: ::: :: : :: ::::: :: : ::::: : :: : ~ : "''''.'.'.2. K '' . '' -' ' ' ' . ..... . . . ....... '.' ' ' ' '." 2 ' 2.,' ' ' .,, . '. ' .''.' .. ...... .... '' '''"''''"2m2'"a '' ' ''' '' ' ''' ' "' " " ' ' '' ' " ' ' ' ' ''' ' ' ' "' ' ' ' 'I' '"" '' "' ' "' ' ' '' ' ' ' ''" '' ' "' '. '2'.. 't"2''8"t','l''''''""""' ' '"" " " ' " .''""" """""""""""'"''""'": .''"'"' '''"'''"", """""""''""""" " """: :':"".""""''."" "'.'" "" "'""'"""""""'.' """.""'."'." "" te _ ~y~ss~eifl~ pta8~!l~ ~ ~6 ~e5~e ................................................................................................................ eme noes tn compu~r s'mu~ ~S 8~t t~t t0~?Y . ... ~ . ~l,~r,~ ....''.~"""'"~.,'" ' ''"""' ' ' " ' '' '' ' ' ' '"' ' ' ' '' ' ' '' ' ' '' ' ' ' ' ' ' ' ' "'" : ::: :: :: : : : : ::: :::; : :t :: : :: :: : : :::::::::::: : ::: ::::::::::: :::::: ::::::::::::: :::::::::::::: ::::::::::::::: ::: :: :: :::: ::: .::::::::: ::::: . . h ~ ::::::: ::::::::::: :: ::::: : :::: : :: :: : : : : :: : . .. ~ : :: i: : ::::::: :: ~ :::::: ::: ~:: ::: ::::::::: :::: :::::::: ::::: :: :: ::: ::::: :::: :::::: :::: ::: of dollars in the past five years by helping drillers to avoid "dry" wells.3 In offices, computer-based spreadsheets enable thousands of analysts and managers to model and predict financial and economic trends. In science, computing is becoming a third paradigm of scien- tific inquiry, on a par with theory and observation or experiment and often yielding unexpected or unanticipated insights not possible through purely theoretical or experimental means.

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COMPUTING-SIGNIFICANCE, STATUS, CHALLENGES 15

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16 COMPUTING THE FUTURE

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COMPUTING-SIGNIFICANCE, STATUS, CHALLENGES 17 Why should computing be so important even essential in these and so many other areas of human endeavor? Fundamentally, the answer is that computing can be usefully applied to any endeavor that uses or can be made to use information in large quantities (~nfor- mation-plenty) or information that has been highly processed and manipulated (information-rich). Information-rich and information-plenty endeavors primarily in- volve products of the human mind- numbers, pictures, ideas. As a device that excels in the storage and manipulation of information, the computer serves primarily as an amplifier of human intellectual capabilities. By operating very rapidly, it enables ~nformation-plenty activities. By undertaking efforts that are beyond the intellectual reach of human abilities, it enables information-rich activities. It is this enabling amplifier effect that is at the heart of today's information revolution, a revolution that may be as significant to human destiny as the agricultural and industrial revolutions. To paraphrase John Seely Brown, corporate vice president of the Xerox Corporation, mass and energy are being replaced by information and computing. The examples above include vignettes on how comput- ing makes automobiles more energy-efficient and manufacturing less materially wasteful. But what is obvious only at a macro-level is the change in the national economy itself. Once buttressed primarily by the sales of material artifacts such as inventory parts, airplanes, and automobiles that derive their value from structuring the atoms that give them substance, the economy is now increasingly one of infor- mation artifacts that may, for example, derive value from structuring musical notes into a symphony, words into a book, binary digits into a computer program, or figures from a business projection modeled on a spreadsheet. Nowhere is the shift from tangible artifact to information artifact better illustrated than in the computer industry itself. In its first few decades of existence, the computer industry made its money in the manufacture of computers. Today, the software sector is the most rapidly growing and profitable sector of the industry, as illustrated by its 19 percent growth rate in 1990 over 1989 levels versus a 9 percent growth rate in the industry overall.4 Yet software itself con- sumes no material, weighs nothing, and requires essentially no pow- er.5 Software is information crystallized in a particular form, and in this form it is valued at over $20 billion per year by the United States- and this estimate excludes the substantial amounts of custom software developed "in house" by computer users. Other examples of the increasing importance of information include the entertainment in- dustry (over $12 billion in sales in 1990 by five major entertainment

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18 COMPUTING THE FUTURE companies6 and videogame manufacturers7 ~ and telecommunications ($107 billion in sales of services by the telephone companies listed in The Business Week 10008), both industries that trade mostly in ideas, information, and imagination. Information technology (including com- puter and communications hardware, plus computer software and services) directly accounts for around 5 percent of the GNP,9 even disregarding its enabling role in other sectors of the economy. SCOPE AND PURPOSE OF THIS REPORT -or ^ L~^~_~V -^ ~rr~ As a key force driving the development of ever more sophisticat- =~1 rmn~miltin~ once tic the cil~nlier of a large proportion of the trained computing personnel in industry, academic computer science and engineering (CS&E) has had a substantial impact on the nation.~ But today, both the intellectual focus of academic CS&E and the envi- ronment in which academic CS&E is embedded are in the midst of significant change. The intellectual boundaries of academic CS&E are blurring with the rise of in-depth programs and activities in com- putational science-the application of computational techniques to advance such disciplines as physics, chemistry) biology, and materi- als science. Universities themselves are retrenching; the computer industry is undergoing substantial and rapid restructuring; and the increasingly apparent utility of computing in all aspects of society is creating demands for computing technology that is more powerful and easier to use. In light of these changes, the Committee to Assess the Scope and Direction of Computer Science and Technology was convened to de- termine how best to organize the conduct of research and teaching in CS&E for the future. The result of its two-year study is an action plan that calls both for sustaining traditional core activities within CS&E and broadening the scope of CS&E's intellectual agenda as the field evolves into the 21st century. This report is divided into two parts. Part I addresses in broad strokes the fundamental challenges facing the field and discusses what the committee believes is an appropriate response to these challeng- es Chapter 1 briefly discusses the intellectual nature of CS&E and then elaborates on the nature of the impending challenges. Chapter 2 provides the philosophical underpinning for an appropriate response by the academic CS&E community. Chapter 3 outlines a core re- search agenda to carry CS&E into the future. Chapter 4 discusses the state of CS&E education at all levels. Chapter 5 articulates a set of judgments and priorities for the field and presents recommendations informed by those judgments and priorities. Part II explains in greater

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COMPUTING- SIGNIFICANCE, STATUS, CHALLENGES 19 detail three aspects of the field: CS&E as an intellectual discipline, in Chapter 6; the institutional infrastructure of academic CS&E, in Chapter 7; and the demographics of the field, in Chapter 8. COMPUTER SCIENCE AND ENGINEERING Computational power however measured has increased dra- matically in the last several decades What is the source of this in- crease? The contributions of solid-state physicists arid materials scientists to the increase of computer power are undeniable; their efforts have made successive generations of electronic components ever smaller, faster, lighter, and cheaper. But the ability to organize these compo- nents into useful computer hardware (e.g., processors, storage de- vices, displays) and to write the software required (e.g., spreadsheets, electronic mail packages, databases) to exploit this hardware are pri- marily the fruits of CS&E. Further advances in computer power and usability will also depend in large part on pushing back the frontiers of CS&E. Intellectually, the "science" in "computer science and engineer- ing" connotes understanding of computing activities, through mathe- ~matical and engineering models and based on theory and abstrac- tion. The term "engineering" in "computer science and engineering" refers to the practical application, based on abstraction and design, of the scientific principles and methodologies to the development and maintenance of computer systems be they composed of hardware, software, or both. Thus both science and engineering characterize the approach of CS&E professionals to their object of study. What is the object of study? For the physicist, the object of study may be an atom or a star. For the biologist, it may be a cell or a plant. But computer scientists and engineers focus on information, on the ways of representing and processing information, and on the machines and systems that perform these tasks. The key intellectual themes in CS&E are algorithmic thinking, the representation of information, and computer programs. An algo- rithm is an unambiguous sequence of steps for processing informa- tion, arid computer scientists and engineers tend to believe in an algorithmic approach to solving problems. In the words of Donald Knuth, one of the leaders of CS&E: CS&E is a field that attracts a different kind of thinker. I believe that one who is a natural computer scientist thinks algorithmically. Such people are especially good at dealing with situations where different rules apply in different cases; they are individuals who can

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20 COMPUTING THE FUTURE rapidly change levels of abstraction, simultaneously seeing things "in the large" and "in the small.''l2 The second key theme is the selection of appropriate representa- tions of information; indeed, designing data structures is often the first step in designing an algorithm. Much as with physics, where picking the right frame of reference and right coordinate system is critical to a simple solution, picking one data structure or another can make a problem easy or hard, its solution slow or fast. The issues are twofold: (1) how should the abstraction be repre- sented, and (2) how should the representation be properly structured to allow efficient access for common operations? A classic example is the problem of representing parts, suppliers, and customers. Each of these entities is represented by its attributes (e.g., a customer has a name, an address, a billing number, and so on). Each supplier has a price list, and each customer has a set of outstanding orders to each supplier. Thus there are five record types: parts, suppliers, custom- ers, price, and orders. The problem is to organize the data so that it is easy to answer questions like: Which supplier has the lowest price on part P?, or, Who is the largest customer of supplier S? By cluster- ing related data together, and by constructing auxiliary indices on the data, it becomes possible to answer such questions quickly with- out having to search the entire database. The two examples below also illustrate the importance of proper representation of information: A "white pages" telephone directory is arranged by name: knowing the name, it is possible to look up a telephone number. But a "criss- cross" directory that is arranged by number is necessary when one needs to identify the caller associated with a given number. Each directory contains the same information, but the different structuring of the information makes each directory useful in its own way. A circle can be represented by an equation or by a set of points. A circle to be drawn on a display screen may be more conveniently represented as a set of points, whereas an equation may be a better representation if a problem calls for determining if a given point lies inside or outside the circle. A computer program expresses algorithms and structures infor- mation using a programming language. Such languages provide a way to represent an algorithm precisely enough that a "high-level" description (i.e., one that is easily understood by humans) can be mechanically translated ("compiled") into a "low-level" version that the computer can carry out (unexecuted; the execution of a program

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COMPUTING SIGNIFICANCE, STATUS, CHALLENGES 21 by a computer is what allows the algorithm to come alive, instructing the computer to perform the tasks the person has requested. Com- puter programs are thus the essential link between intellectual con- structs such as algorithms and information representations and the computers that enable the information revolution. Computer programs enable the computer scientist and engineer to feel the excitement of seeing something spring to life from the "mind's eye" and of creating information artifacts that have consid- erable practical utility for people in all walks of life. Fred Brooks has captured the excitement of programming: The programmer, like the poet, works only slightly removed from pure thought-stuff. He builds castles in the air, creating by the exertion of the imagination.... Yet the program construct, unlike the poet's words, is real in the sense that it moves and works, pro- ducir~g visible outputs separate from the construct itself.... The magic of myth and legend has come true in our time. One types the correct incantation on a keyboard, and a display screen comes to life, showing things that never were nor could be.~3 Programmers are in equal portions playwright and puppeteer, working as a novelist would if he could make his characters come to life simply by touching the keys of his typewriter. As Ivan Suther- land, the father of computer graphics, has said, Through computer displays I have landed an airplane on the deck of a moving carrier, observed a nuclear particle hit a potential well, flown in a rocket at nearly the speed of light, and watched a com- puter reveal its innermost workings.~4 Programming is an enormously challenging intellectual activity. Apart from deciding on appropriate algorithms and representations of information, perhaps the most fundamental issue in developing computer programs arises from the fact that the computer (unlike other similar devices such as non-programmable calculators) has the ability to take different courses of action based on the outcome of various decisions. Here are three examples of decisions that pro- grammers convey to a computer: Find a particular name in a list and dial the telephone number associated with it. If this point lies within this circle then color it black; otherwise color it white. While the input data are greater than zero, display them on the screen. When a program does not involve such decisions, the exact se

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22 COMPUTING THE FUTURE quence of steps (i.e., the "execution path") is known in advance. But in a program that involves many such decisions, the sequence of steps cannot be known in advance. Thus the programmer must an- ticipate all possible execution paths. The problem is that the number of possible paths grows very rapidly with the number of decisions: a program with only 10 "yes" or "no" decisions can have over 1000 possi- ble paths, and one with 20 such decisions can have over 1 million. Algorithmic thinking, information representation, and computer programs are themes central to all subfields of CS&E research. Box 1.4 illustrates a typical taxonomy of these subfields. Consider the subarea of computer architecture. Computer engineers must have a basic understanding of the algorithms that will be executed on the computers they design, as illustrated by today's designers of parallel and concurrent computers. Indeed, computer engineers are faced with many decisions that involve the selection of appropriate algo- rithms, since any programmable algorithm can be implemented in ... .. . . . ....... ... .. .... .... .. . ...... . ., ~.~.,,1.,. ~. XoN. ~.~.~. ~.~.~.~. ~. ~.~. : . . ..... .............................................. ~ ^~s and dam struct~ . ~.................... . ~.............. ................... .......... . .. .. . . ... * .. ....... 1 ... . . . ... .. . . ~ ,., ~.~.~. ~. ~I - ..... .... ~ . ~.. .. , ~.~. ~.~.~.~. ~. .... - ~ - -. ..... . . ~.~.~.e r] ( ~n d sy.~.~.~ ~.~.~.~.~ 5 oPerating~s~ms~ ~ ~ ~ ~ ~ ~ ~ ~* q ~= :: :: : Em: : : ~ :: :: :: : :::: ::: :: ::::: :::: ::: : :::::::: ::: ::: ~ -f ~ ~ ~ It~ . ~ - 1 . : ::: ::: . . :: ::::::: :: ::: :.: ::: ::::: :: :: :::: ::: ::.::::: ::::::: ::::: :::::: :: :::: :: ::: :::: i:: .. .. . .. ~ ~ ~ ~ ~ Add ' '."2d''e"''''' '' " ' '"'' ' ' '' ''' ' " ' '' '''" ' ':"'" ' '" ' ' ' '" ' ' ' ' ..... ......... ..... .... ...... .. . ~.t t ~ ~ ~ d [* ~ ~ ....'l.''"s'.'."'b'''' ' """ ""'''"'''""' '' "'' ' '' ' '"" ' ' ' ' " ' :'' "''' ' ''' ''' '' ' ' ' ' '' ' "': .............................. .. .. ... .... .... .. . ~.,.,~.k t., ~.~. ~. ~. ~. ~.~. ~.~.~.~. ~. ~.~ ~I . . ....... ...... ... . . . . ... . . . ~^.t,=~.t,.~. ~.: ~.~. ~: ~ . a. ~m .... ~ ~. ~.~ ~ ~ ~: ~ . . ~ ~ J . . : : :. : ,:., ,,, : : ~ : : : :: : : ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ! . ~ ~. ~, ~, ~,l. .. - ... . .............. . . . ... . . ash She," ~

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COMPUTING SIGNIFICANCE, STATUS, CHALLENGES 23 hardware. Through a better understanding of algorithms, computer engineers can better optimize the match between their hardware and the programs that will run on them. Those who design computer languages (item two in Box 1.4) with which people write programs also concern themselves with algorithms and information representation. Computer languages often differ in the ease with which various types of algorithms can be expressed and in their ability to represent different types of information. For example, a computer language such as Fortran is particularly conve- nient for implementing iterative algorithms for numerical calcula- tion, whereas Cobol may be much more convenient for problems that call for the manipulation and the input and output of large amounts of textual data. The language Lisp is useful for manipulating sym- bolic relations, while Ada is specifically designed for "embedded" computing problems (e.g., real-time flight control). The themes of algorithms, programs, and information representa- tion also provide material for intellectual study in and of themselves, often with important practical results. The study of algorithms with- in CS&E is as challenging as any area of mathematics; it has practical importance as well, since improperly chosen algorithms may solve problems in a highly inefficient manner, and problems can have in- trinsic limits on how many steps are needed to solve them (Box 1.5~. The study of programs is a broad area, ranging from the highly for- mal study of mathematically proving programs correct to very prac . . . . . . .. . . ..... . i .. .... .. .... ~ . . ..~ ~.. .~ . ~ ~

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44 COMPUTING THE FUTURE , ~ _...... I ~i~ !-~- ~ :::;:: ::: ::: ::a;: : :::: :::::: :::::: :: ::: ::-: :::::::: :::::::::::::::::::: :: ::.::::: : ; : :: ::::::; :: :::::: ::::::::::::.. ::: :: : :::~::::: ::: :::: : ::::::::::: ::-::: : ::: : ::::::::::::::: ::::::~:~::::i :: :: ::::::::::: :: :::::::: :: ::~:::::::: ::::::: ::::::: ::::::::::::::::::::::: ~1~-.~.,t,~ ' 11 : :: :::::::: :::...::::: : ::::::: : ' 1 ' ' ' '' "' ' ' ' ':'' ' ' ' ' ' ';' ' ' ' ' ' ' ' ' ' ' ' " '" ' ' ' ' ' ' ' . ... .. . ~ . ~ a. . ~ . . ~ =~lega~l~llll :::::::::.:. ::: ::-:i :::::: ::::, ::::: :::: ::::: ::: ~1~1~1~ Marl IET~1~3i={~ss~o~1~1~1i~ Bee 1~ Except an l t '''"'m'22a""e'S.""' ~ 1991. raised by the intangibility of software (Box 1.10), other concerns arise with respect to the knowledge gained through or with that software, the conflict between possible patent or copyright rights of the people who wrote that software versus the people who financed it versus the people who use it, and the granting of recognition to those who have done the work while protecting the entrepreneurial rights of the sponsors. As one example, many companies in the computer indus- try cross-license their patents with one another to ease the process of bringing individual products to market. But in an environment of pressures for exclusive licenses to maximize revenues (pressures of- ten exerted by universities) and legal uncertainties regarding patent and copyright protection for software, the interests of academia and industry may diverge. However these issues are resolved in any given case, resolution takes time. Universities and companies that

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COMPUTING SIGNIFICANCE, STATUS, CHALLENGES 45 have made use of umbrella agreements covering all joint work have found that the time between initial contact and final settlement of terms has been sharply reduced. THE CHANGING ENVIRONMENT FOR ACADEMIC CS&E In its infancy and adolescence, academic CS&E has experienced rapid growth and progress. Support for the field increased at a fast clip, and the founders of the new field sustained a high degree of productivity. Computers themselves, once housed in a few large buildings, are now everywhere on office desks. But many important changes are pending in the intellectual, eco- nomic, and social milieu in which academic CS&E is embedded. Per- haps the most important is that a solid record of success increases expectations of those inside the field for continued support and out- side the field for continued practical benefits. Fiscal constraints faced by the major funders of research in this country the federal govern- ment and industry are likely to result in greater pressure to trim research budgets and at the same time generate increased pressure for research to produce tangible benefits. Against this backdrop, several additional changes must also be considered. Changes in the Computer Industry The computer industry is itself undergoing massive change. The influence of formerly strong players such as Data General, Unisys (and its presecessors), and Control Data has waned considerably in the past 20 years, and an environment in which IBM and Apple Com- puter are motivated to collaborate is a different one indeed. Interna- tional competition is on the rise. And, although today's computer industry was built primarily on the sales of large mainframe comput- ers to a relatively few institutions, the computing environment of the future will emphasize to a much greater extent computers as con- sumer-oriented items tools for the masses. In this environment, computing technology both hardware and software will be specialized for intellectual work in much the same way that electric motors are specialized for physical work it will be invisible but ubiquitous. Just as electric motors are an important but invisible part of heaters, washing machines, refrigerators, and alarm clocks, so~also computers and software are today or will be embed- ded in telephones, televisions, automobiles, and lawnmowers. (Ac- tually, it will not be surprising to find them in washing machines and

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46 COMPUTING THE FUTURE refrigerators as well.) It is the increasing ubiquity of computing that has led many analysts to predict the eventual convergence of com- puter, communications, and entertainment technology and the emer- gence of information appliances that are dedicated to specific tasks (such as pocket calendars or remote library access devices). New computer systems will be increasingly portable and are likely to be interconnected to each other or to information service providers, and they may well embody new computing styles such as pen-based com- puting. Accompanying these changes in the computer industry per se are other major changes that are affecting all industries. In particular, changes in the business environment portend vastly greater global- ization and time compression. To survive, let alone prosper, indus- try in the future will have to respond to a much larger range of competitors than in the past, and to respond much more rapidly than it has in the past. For the computer industry, these changes mean that products will have to be fitted to customer needs much more precisely. Since customers are interested in computing technology primarily for its value in solving particular problems, knowledge of the customer's application will become more and more important; such knowledge will most likely become embedded in software written to serve these applications. Since customers will be understandably reluctant to abandon substantial investments in hardware, software, and human expertise, it will be necessary to design new products with a high degree of compatibility with earlier generations. Indeed, even today many customers are unable to keep up with, let alone exploit to best advantage, the capabilities of new computing technologies. Since the particular computer products needed by customers cannot be antici- pated years in advance, industry will have to place greater emphasis on reducing the time to market for new products; thus tools, technol- ogy, and approaches to design (e.g., rapid prototyping) to facilitate shorter response times will be necessary, especially for the now la- bor-intensive software sector. Finally, greater concerns about competitiveness will increase fi- nancial pressures on the computer industry, just as they affect all other industry. In an environment of cost cutting, activities that can- not demonstrate an impact on the bottom line will be highly suspect and subject to reduction or elimination. Thus it would not be sur- prising to see industrial research laboratories shift their focus to ef- forts with a more "applied" flavor in the quest of their parent compa- nies for competitive advantage.35 Such a shift may already be starting to occur: the strong connection between CS&E and computing prac

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COMPUTING SIGNIFICANCE, STATUS, CHALLENGES 47 lice has led to strong demand from the computer industry for indi- viduals who are "system builders," making it more difficult for aca- demia to compete effectively for such individuals. Cost-cutting pres- sures may also be reflected in the willingness of the industry to continue unchanged its practices of donating equipment to academic CS&E departments. These donations (or reduced-price sales) account for a substantial amount of the equipment that these departments use for research and educational purposes.36 Structural Changes in Academic CS&E From a personnel standpoint, the CS&E field has undergone tre- mendous growth in the last decade. For example, according to the Office of Scientific and Engineering Personnel of the National Re- search Council, U.S. Ph.D. production in CS&E grew from its 1979 level of 235 graduates per year to 531 in 1989.37 The number of undergraduate degrees awarded per year grew by more than a factor of three and may be rising again. The number of academic doctoral- level researchers working in CS&E grew from 1052 to 3860 over the same time period, and the number of individuals who have doctor- ates and are teaching CS&E increased from 1613 to 5239.38 The me- dian age of doctoral faculty who teach CS&E grew from 38.4 in 1977 to 43.4 years in 1989, which was about the median age of all doctoral scientists and engineers regardless of field in 1981. (Chapter 8 dis- cusses these and other human resources trends in academic CS&E.) Tremendous growth characterizes the intellectual side of CS&E as well. While it is of course difficult to document in quantitative terms the intellectual maturity of a field, it is nevertheless the judg- ment of the committee that CS&E as an intellectual endeavor has indeed come of age. Although as an organized and independent intellectual discipline it is less than 30 years old, CS&E has estab- lished a unique paradigm of scientific inquiry-a computational par- adigm that is applicable to a wide variety of problems and has be- come the base on which a critical enabling technology of the next century will be built. The opening pages of Chapter 3 and the sec- tion "Selected Accomplishments" in Chapter 5 discuss the accom- plishments and the research paradigm in greater detail. Changes in the University Environment Academic CS&E will be affected by the university environment, an environment that is itself in the midst of remarkable changes.

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48 COMPUTING THE FUTURE One major issue is the fact that the compact between the federal government and university research developed in the 1940s and 1950s is under increasing pressure. Implicit in this compact was the under- standing that placing decisions regarding the course of basic research in the hands of the investigating scientist would lead to substantial social and economic benefits as the result of government support for such research.39 However, recent events such as congressional inter- est in alleged abuses in government funding of university research40 suggest that pressures for accountability will increase in the future, and it is entirely plausible that accountability for research will re- quire concrete demonstrations of positive benefit to the nation. Financial considerations also loom large. Universities everywhere are suffering from ever tighter budgets, and it does not appear that these exigencies will abate in the foreseeable future. Apart from the difficulties that all academic disciplines will face in matters such as faculty hiring, academic CS&E departments will face particular prob- lems in maintaining infrastructure to meet the field's research needs. As noted earlier, many research problems in CS&E are driven and motivated by the upper bounds of performance at the cutting edge of computing technology (whether these edges result from so- phisticated new components or novel arrangements of older compo- nents). The availability of state-of-the-art systems to address these problems is therefore critical if CS&E departments are to stay at the cutting edge of research, whether in software or hardware. Howe~r- er, state-of-the-art systems are always expensive, and acquisition of such equipment does not benefit from the downward cost trend that characterizes computing equipment of a given sophistication or per- formance. Compounding the problem is the fact that a system that is state of the art today may not remain so for very long.4i Large and often recurring replacement costs will be necessary for departments to remain at the hardware state of the art. Capitalization for educational purposes is also an important as- pect of acquisition budgets. CS&E students (especially undergradu- ate students) may not need access to computing equipment that is absolutely at the cutting edge, but all too often undergraduate CS&E students must make do with personal computers that were acquired in the mid-1980s and that often cannot run modern software. When they must use hardware whose capabilities are so limited, students are forced to struggle with machine limitations rather than focusing on central concepts that could be more clearly illustrated with more powerful machines. For the teaching of some topics, hardware that is so limited in performance is not effective as a pedagogical tool.

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COMPUTING SIGNIFICANCE, STATUS, CHALLENGES SUMMARY AND CONCLUSIONS 49 Computing has become indispensable to modern life, and every computer in use today is based on concepts and techniques devel- oped by research in CS&E. Future advances in CS&E research will have a similar impact: they will increase the use of computing and the effectiveness of computing. But after several decades of vigor and growth, the CS&E field is facing a very different environment. Academic computer scientists and engineers the primary group ad- dressed in this report will have to cope with a host of new challeng- es, some arising from the remarkable successes of the discipline (e.g., the spread of computing to virtually all walks of life) and others from factors er~tirely outside the discipline (e.g., pressures on federal research support). How should the community respond? As Chapter 2 describes at length, the committee believes that academic CS&E must begin to look outward, embracing rather than eschewing other problem do- mains as presenting rich arid challenging topics for CS&E research. NOTES 1. Business Week, October 28, 1991, p. 120. 2. Written testimony of Jack L. Brock, Information Management and Technology Division of the General Accounting Office, to the Subcommittee on Science, Technolo- gy and Space of the Senate Commerce Committee, March 5, 1991, p. 6. 3. Written testimony of Jack L. Brock to the Subcommittee on Science, Technology and Space of the Senate Commerce Committee, March 5, 1991, p. 4. 4. The Bossiness Week 1000, 1991 Special Issue, pp. 174-175. 5. For example, a floppy disk with a word-processing program on it and one with- out the program on it have identical weights, but the first disk is much more useful and valuable. 6. The Business Week 1000, 1991 Special Issue, p. 167. The "Entertainment" catego- ry lists five major corporations. 7. U.S. Department of Commerce, U.S. Industrial Outlook 1991, U.S. Government Printing Office, Washington, D.C., 1991, p. 39-6. 8. The Business Week 1000, 1991 Special Issue, p. 178. 9. The GNP of the United States was $5465.1 billion in 1990 (U.S. Department of Commerce, Survey of Current Business, Volume 71(7), July 1991, p. 5). For 1990, the Computer and Business Equipment Manufacturers Association (CBEMA) estimated revenues derived from computer equipment at $153.7 billion (p. 26), from computer software at $92.4 billion (p. 24), and from telecommunications equipment at $61.7 billion (p. 26); in total, these categories accounted for about 5.6 percent of the GNP. (Page references are for CBEMA Industry Marketing Statistics Committee, The I~forma- tion Technology Industry Data Book: 1960-2000, Computer and Business Equipment Manufacturers Association, Washington, D.C., 1990.) A different set of estimates is provided by the U.S. Department of Commerce (U.S. Industrial Outlook 1991, U.S. Gov- ernment Printing Office, Washington, D.C., 1991): computers and peripherals, $71 bil

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50 COMPUTING THE FUTURE lion (p. 28-1); software, $29 billion (p. 28-15); telephone and telegraph equipment, $18.5 billion (p. 30-1); radio and TV communication equipment, more than $55.8 bil- lion (p. 31-1); electronic information services, $9 billion (p. 27-2); data processing and network services, $31 billion (p. 27-3); and computer professional services, $44 billion (p. 27-4). Taken together, these categories totaled 4.7 percent of the GNP. 10. In this report, the term "computing" denotes both the electronic activity taking place when computers are being used and the problem-solving activities to which computers are directed. "Computing practice" or "the practice of computing" denotes computers used as tools for solving problems in domains not intrinsically related to computers themselves. "Computer science and engineering" (CS&E) is used more narrowly to denote a field whose research and development activities are related to computers per se. 11. The notion of CS&E as a discipline based on theory, abstraction, and design is described in Peter Denning, Douglas E. Comer, David Gries, Michael C. Mulder, Allen Tucker, Joe Turner, and Paul R. Young, "Computing as a Discipline," Communications of the ACM, Volume 32(1), January 1989, pp. 9-23. 12. Personal communication, Donald Knuth, March 10,1992 letter. 13. Frederick Brooks, The Mythical Man-Month, Addison-Wesley, Reading, Mass., 1975, pp. 7-8. 14. Ivan Sutherland, "Computer Displays," Scientific American, June 1970, p. 57. 15. A point-of-sale network is a network of electronically linked cash-register/ter- minals that can capture purchasing information at the moment and place a sale is made (i.e., at the "point of sale") for such purposes as tracking inventory, debiting and crediting funds between customer and store bank accounts through electronic funds transfer, or automatically generating purchase orders for new merchandise. Or, it can perform some combination of these tasks. 16. In 1990, 53 percent of the American public disagreed with the statement that "computers and factory automation will create more jobs than they will eliminate." See National Science Foundation, Science and Engineering Indicators, 1991, NSF, Wash- ington, D.C., 1991, p. 455. 17. Gary Hart and Barry Goldwater, Recent False Alerts from the Nation's Missile Attack Warning System, Report to the Senate Armed Services Committee, U.S. Govern- ment Printing Office, Washington, D.C., October 10, 1980. In 1979, a test tape was mistakenly entered into the missile early warning system of the Strategic Air Com- mand. In 1980, the failure of a computer chip generated two erroneous warnings of . . . .. Incoming missiles. 18. Funding figures have been drawn from various sources of the NSF Division of Science Resources Studies (SRS) series. The NSF SRS Division compiles these figures on the basis of questionnaires completed by the various federal agencies. Thus it identifies what the various agencies believe should be counted under the label "com- puter science." Such self-identification of funds, in the absence of a standard and consistent definition, may easily lead to errors and omissions, especially in the case of projects that contain important CS&E elements but that are not themselves obviously CS&E. For example, the National Institutes of Health does not fund much research that it reports as "computer science" research ($300,000 in FY 1990). Nevertheless, according to an NIH briefing received by the committee, NIH funds some $150 million per year in medical imaging research, research that has a strong CS&E aspect and may even be performed in CS&E departments. Similarly, research funded under electrical engi- neering may be computer design. However, agencies may also label as "computer science" work that may more properly be classified under "applied mathematics."

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COMPUTING SIGNIFICANCE, STATUS, CHALLENGES 51 SRS figures have been used because they come from a single source that attempts to ensure that trend comparisons can be made. The alternative would have been to dig into the data in detail (i.e., at the individual grant and contract level) for the years in question, an undertaking well beyond the scope of this project. In addition, since individual agencies tend to use the same identification process year in and year out, the SRS figures are likely to reflect trends over time for individual agencies. However, note that when funding figures for FY 1990 and FY 1991 are presented, they are pre- liminary and subject to later revision. Figures presented in the funding charts of this chapter and in Chapter 7 are the sum of line items labeled "computer science" and "mathematics and computer science, not otherwise classified," are in FY 1992 (constant) dollars, and are assumed to include computer engineering. 19. Bob Brewin, "IT Dollars to Inch Up Next Year," Federal Computer Week, April 25, 1992, p. 1. 20. Office of Science and Technology Policy, The Federal High Performance Comput- ing Program, Executive Office of the President, Washington, D.C., September 1989. 21. The Federal Coordinating Council on Science, Engineering, and Technology consists of the heads of all agencies that have responsibilities for issues with signifi- cant scientific or technical aspects. Chartered in the early 1970s and revitalized in 1989 under Science Advisor D. Allan Bromley, its purpose is to provide interagency coordi- nation for activities related to such issues. 22. The 1989 OSTP report articulated specific goals: increasing Ph.D. production in computer science to 1000 per year by 1995, upgrading 25 additional university com- puter science departments to nationally competitive quality, and improving connec- tions between computer science and other disciplines, including the creation of at least ten computational science and engineering departments (p. 40). But neither the legis- lation nor its legislative history mention these specific goals, except to specify that the Congress expects the HPCC Program to be similar to that presented in the 1989 report (Senate Commerce Committee, High-Performance Computing Act of 1991: Report of the Senate Committee on Commerce, Science, and Transportation, Report 102-57, U.S. Govern- ment Printing Office, Washington, D.C., 1991, p. 16). 23. Since the HPCC Program is a multiagency program, authorizations are con- trolled by different committees of the Congress. Five-year authorizations for the NSF, Departments of Energy and Commerce, NASA, and the Environmental Protection Agency were specified by the High-Performance Computing Act of 1991. A one-year authori- zation for the DARPA portion was passed by the National Defense Authorization Act for Fiscal Years 1992 and 1993, and will be revisited in FY 1993. The National Insti- tutes of Health has been operating under the "rolled-over" authorizing legislation of FY 1990 since that year, although a multiyear authorization bill for FY 1993 and be- yond is pending in Congress as this report goes to press. 24. The budget process typically involves four major steps. The first is that the administration proposes a budget, called "the administration's request." The second step is usually that the Congress passes "authorizing" legislation that provides what amounts to an upper bound on the amounts that the Congress may appropriate in later years. Authorizing legislation also generally determines the broad policy out- lines that the administration must follow in implementing the program. Authorizing legislation is often (though not always) based on the broad outlines of the administra- tion's request; for major programs, authorizing legislation nearly always makes some budget or policy changes in the request. In the event that authorizing legislation is not specifically passed for any given fiscal year, Congress often resorts to stop-gap legisla- tion that simply rolls over authorizations from previous years. The third step is that

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52 COMPUTING THE FUTURE the Congress passes "appropriating" legislation that provides the administration with the authority to obligate money (i.e., write checks for specific purposes); appropriating legislation is passed yearly. There is no legal requirement that the amounts appropri- ated match the amounts authorized, though in practice amounts appropriated above the authorized figures are rare and amounts appropriated under the authorized figure are somewhat more common. The fourth step is that the administration responds to the congressional appropriation. For example, if the appropriation for the National Science Foundation is lower than that proposed in the president's budget, the admin- istration must decide how to parcel out that cut among the various directorates of the NSF; it has complete freedom to make these decisions, as long as they are consistent with congressional intent on the matter. 25. The difference between the 1991 amount in Table 1.3 ($489 million) and the amount in Table 1.1 for FY 1991 ($680 million) reflects the fact that not all federally funded CS&E research is part of the HPCC Program. Similarly, not all HPCC Program funding is intended for the CS&E community; researchers in other "grand challenge" disciplines will also benefit from the HPCC Program. 26. During congressional debate on the HPCC Program, the administration cited a study that estimated a payback of $10.4 billion in supercomputer revenues from the pursuit (at full funding levels of $1.9 billion over the next five years) of the HPCC Program (p. 119). This study also forecast a cumulative increase in GNP of $172 billion to $502 billion over the next decade (p. 143). See the Gartner Group, High Performance Computing and Communications: Investment in American Competitiveness, Stamford, Con- necticut, March 15,1991. 27. The ending of the Cold War was thought by many to herald an era in which military spending would be sharply curtailed and the savings made available for other purposes. But the budget agreement for FY 1991 between the president and the Con- gress stipulated that military spending and nondefense, discretionary spending would constitute two entirely separate categories and that cuts in one category could not be used to increase spending in another category. This agreement was originally sched- uled to expire in FY 1993, so that the FY 1994 budget will not be subject to this rule. Whether this agreement will continue to remain in effect is not clear as this report goes to press. A very good survey of the pressures on federal funding of the research enterprise is contained.in Office of Technology Assessment, Federally Funded Research: Decisions for a Decade, U.S. Government Printing Office, Washington, D.C., May 1991. 28. David Sanchez, "The Growing, Caring and Feeding of a Budget," NSF Direc- tions Newsletter, STIS DIR-916, Office of Legislative and Public Affairs, National Sci- ence Foundation, Washington, D.C., Volume 4(2), March-April 1991. 29. Office of Science and Technology Policy, The Federal High Performance Comput- ing Program, Executive Office of the President, Washington, D.C., September 8, 1989, p. 8. Some of the grand challenges listed on pp. 49-50 of this document are the predic- tion of weather, climate, and global change; semiconductor design; drug design; the human genome project; and quantum chromodynamics. 30. The committee's estimate is based on an assumption that the half-dozen or so major firms in the computer and communications industry (e.g., AT&T, IBM) employ a few thousand full-time CS&E Ph.D. researchers and hire hundreds of new CS&E Ph.D.s every year (as indicated by the various Taulbee surveys). Assuming that each re- searcher costs an average of $200,000 per year in salary, benefits, and equipment, industrial researchers represent an annual investment of several hundred million dol- lars per year. (This estimate does not take into account the fact that a substantial

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COMPUTING SIGNIFICANCE, STATUS, CHALLENGES 53 portion of industrial research is conducted by holders of master's degrees or Ph.D.s from other fields.) This figure can only be estimated due to the fact that reports of corporate R&D spending generally do not disaggregate research and development, let alone research in different fields. However, according to common rules of thumb, research costs tend to be perhaps a tenth of development costs, which are themselves perhaps several percent of gross revenues. Thus the figure of "several hundred million" per year spent on CS&E research is not grossly inconsistent with the $153 billion per year in sales of the computer industry reported by CBEMA in Note 9 above. (One data point on the relative size of research vs. development is that IBM's R&D budget in 1991 was about $6.5 billion, of which 90 percent went to development. See John Markoff, "Abe Peled's Secret Start-Up at IBM," New York Times, December 8, 1991, Section 3, p. 6.) 31. This understanding is echoed in Government-University-Industry Research Round- table/Academy Industry Program, New Alliances and Partnerships in American Science and Engineering, National Academy Press, Washington, D.C., 1986, p. 36. 32. Computer Science and Technology Board, National Research Council, Keeping the U.S. Computer Industry Competitive: Defining the Agenda, National Academy Press, Washington, D.C., 1989, p. 59. The report notes that many successful ideas in software have had their origin in large research investments by big companies and that these ideas have been commercialized by small start-up firms. Though the report refers to research originating in industry, the same is likely true for academic research as well, since the difficulties of commercializing research tend to arise regardless of the re- search's origin. 33. The flow of venture capital to small business had dropped by nearly a factor of two in 1990 compared to its peak in 1987. See "Agenda for Business," U.S. News and World Report, June 3, 1991, p. 62. 34. See also Government-University-Industry Research Roundtable/Academy In- dustry Program, New Alliances and Partnerships in American Science and Engineering, National Academy Press, Washington, D.C., 1986, p. 29. 35. For example, Kumar Patel, a research director at AT&T Bell Laboratories, says that "we have a narrow view of what's important to us in the long run. What we call basic research is what fits the general needs of the company." See "Physics losing the corporate struggle," Nature, Volume 356, March 19, 1992, p. 184. While this article emphasizes shifts at Bell Labs, Bellcore, and IBM away from basic research in physics, the reasons for such shifts are closely related to the business interests of the respective companies. 36. According to an NSF survey, private and industrial sources accounted for about 29 percent of research equipment acquisition budgets for academic CS&E in 1988. See National Science Foundation, Academic Research Equipment in Computer Science, Central Computer Facilities, arid Engineering: 1989, NSF 91-304, NSF, Washington, D.C., January 1991, Table 4, p. 5. 37. Throughout this report, figures related to Ph.D. production are taken from the Office of Scientific and Engineering Personnel (OSEP) of the National Research Coun- cil. As Chapter 8 indicates, these numbers at times differ considerably from figures commonly available to the field, such as those of the Taulbee surveys; these figures also lag the Taulbee survey by a couple of years. However, these figures have been used because the OSEP is also responsible for collecting such data for other fields, making the data usable for comparative purposes. Reasons for the discrepancies in data from the various sources are discussed in Chapter 8. 38. The number of academic CS&E researchers over time is presented in Table 8.13.

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54 COMPUTING THE FUTURE The number of those teaching CS&E in these years is taken from data provided by the Office of Scientific and Engineering Personnel of the National Research Council and includes those teaching computer science, computer engineering, and information sci- ences. 39. This compact is best described in Vannevar Bush, Science the Endless Frontier, NSF-90-8, National Science Foundation, Washington, D.C., 1945/1990: "Scientific progress on a broad front results from the free play of free intellects, working on subjects of their own choice, in the manner dictated by their curiosity for exploration of the unknown" (p. 12) and "Support of basic research in the public and private colleges, universities, and research institutes must leave the internal control of policy, person- nel, and the method and scope of the research to the institutions themselves" (p. 33), as well as the text of Note 1 in Chapter 2. 40. Colleen Cordes, "Audits Indicate 14 Universities Improperly Charged Govern- ment for $1.9 to $2.4 Million in Overhead," Chronicle of Higher Education, Volume 38(10), October 30, 1991, pp. A26-A29; Daniel E. Koshland, Jr., "The Overhead Ques- tion," Science, Volume 249, July 6, 1990, pp. 10-13. 41. In one NSF survey conducted in 1985-1986, administrators from computer sci- ence departments regarded research instrumentation and equipment that was more than one year old (on average) as not "state-of-the-art." See National Science Founda- tion, Academic Research Equipment in Selected Science/Engineering Fields: 1982-1983 to 1985-1986, SRS 88-D1, NSF, Washington, D.C., June 1988, Table B-5, p. B-14.