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Opinion

Personal computing: personal computers and the world software market

It may be trite to say that “the world is shrinking,” but it is true nonetheless. Political and technological changes are edging us in the direction of the global village. We have the economic unification of Western Europe, the transition of Eastern Europe to market economies, and free trade agreements and negotiations in the Western hemisphere. Blue jeans and rock and roll music are found throughout the world, we can direct dial to Iceland, and your grandmother may have a FAX machine.
Opinion

Log on education: Quick, where do the computers go?

History has dealt computer and information science a special role in the inevitable restructuring of the educational system in the United States. In the coming decade computing and information technology will be the backbone of the most significant change in education in over 100 years. Rather than being an adjunct to learning and teaching, technology is facilitating a fundamental re-thinking of what should be learned and how. Such changes present the Communications readership with a unique opportunity and a serious responsibility. Toward meeting this challenge, in this column I will address some key issues in education and technology. For example, this first column examines how our basic notion of what needs to be learned is changing, and how this affects the ways in which technology is used. Subsequent columns will explore topics such as “programming's role in learning,” “multi-media, and nationwide, computer-based,” testing.
Research and Advances

The impact of information systems on organizations and markets

The adoption of information technology (IT) in organizations has been growing at a rapid pace. The use of the technology has evolved from the automation of structured processes to systems that are truly revolutionary in that they introduce change into fundamental business procedures. Indeed, it is believed that “More than being helped by computers, companies will live by them, shaping strategy and structure to fit new information technology [25].” While the importance of the relationship between information technology and organizational change is evidenced by the considerable literature on the subject,1 there is a lack of comprehensive analysis of these issues from the economic perspective. The aim of this article is to develop an economic understanding of how information systems affect some key measures of organization structure.
Research and Advances

Supply/demand of IS doctorates in the 1990s

The field of information systems (IS) has experienced a severe shortage of faculty throughout its 20-year history. This shortage now appears to be lessening. A survey of the supply of IS doctorates finds a steady stream of graduates from IS doctoral programs. In 1989, 61 universities in the U.S. offered Ph.D. or Doctor of Business Administration (D.B.A.) concentrations in information systems. A survey of these programs resulted in 51 responses, including all the programs producing significant numbers of graduates. The following are highlights from the survey: Recent increase in the number of IS doctoral students: In 1988-89 there were 807 doctoral students enrolled in 51 doctoral programs in information systems. The programs admitted 217 new students for 1989-90. In the 1988-89 time period, 36 programs produced 120 doctorates—a 24 percent increase in graduates from the previous year. In the 1989-90 time period, 41 programs expect to graduate a total of 140 students—a 2-year cumulative increase of 44 percent: Downsizing by some programs, but others—including new programs—adding to capacity. In 1988-89, there were 13 programs that produced three or more doctorates. Those 13 programs accounted for 70 percent of all the graduates in 1988-89. In 1989-90, those same 13 programs expect to account for only 39 percent of the total number of graduates. Of the 13 programs, 5 except to have a decrease in the number of students over the next five years. Of 51 schools, 9 offering doctorates in IS have yet to graduate a student. Another 9 schools had their first graduate in 1985 or later. Several additional doctoral programs are in the planning stages. Twenty-three programs expect a growth in the number of students over the next five years. In this article, we examine the supply and demand gap
Research and Advances

Profiling computer science master’s programs

Master's level computer science programs have experienced significant and sustained growth during the past two decades. According to the U.S. Department of Education's National Center for Education Statistics [4], a total of 1,588 master's degrees were conferred in computer and information sciences in 1971. This figure increased 508% to 8,070 in 1986—a larger percentage increase than any other major discipline. The 1970s and 1980s have also been an era in which computer science has experienced major theoretical and technological advances. The period has been marked by severe faculty shortages which are only now beginning to ease. Complicating matters further, the discipline is so young that it is still in the process of defining its intellectual framework [3]. Considering all of these factors, it is not surprising that there is a considerable amount of diversity and flux among computer science master's programs. What is surprising, however, is that little data is available pertaining to this degree.
Opinion

Inside risks: risks in computerized elections

Background: Errors and alleged fraud in computer-based elections have been recurring Risks Forum themes. The state of the computing art continues to be primitive. Punch-card systems are seriously flawed and easily tampered with, and still in widespread use. Direct recording equipment is also suspect, with no ballots, no guaranteed audit trails, and no real assurances that votes cast are properly recorded and processed.
Research and Advances

Women and computing

There is mounting evidence that many women opting for careers in computing either drop out of the academic pipeline or choose not to get advanced degrees and enter industry instead. Consequently, there are disproportionately low numbers of women in academic computer science and the computer industry. The situation may be perpetuated for several generations since studies show that girls from grade school to high school are losing interest in computing.Statistics, descriptions offered by women in academic and industrial computing, and the research findings reported later in this article indicate that much is amiss. But the point of what follows is not to place blame—rather it is to foster serious reflection and possibly instigate action. It behooves the computer community to consider whether the experiences of women in training are unique to computer science. We must ask why the computer science laboratory or classroom is “chilly” for women and girls. If it is demonstrated that the problems are particular to the field, it is crucial to understand their origins. The field is young and flexible enough to modify itself. These women are, of course, open to the charge that they describe the problems of professional women everywhere. But even if the juggling acts of female computer scientists in both academia and industry are not particular to computing, American society cannot afford to ignore or dismiss their experiences; there is an indisputable brain drain from this leading-edge discipline.A look at statistics reveals a disquieting situation. According to Betty M. Vetter, executive director of the Commission on Professionals in Science and Technology in Washington, DC, while the number of bachelor's and master's degrees in computer science are dropping steadily for both men and women, degrees awarded to women are dropping faster, so they are becoming a smaller proportion of the total. . Bachelor's degrees peaked at 35.7% in 1986, masters also peaked that year at 29.9%, and both are expected to continue to decline. “We have expected the numbers to drop for both, due to demographics such as fewer college students,” says Vetter, “but degrees awarded women are declining long before reaching parity.” (See Table I.) Vetter also would have expected computer science to be “a great field for women,” as undergraduate mathematics has been; female math majors have earned 45% of bachelor's degrees during the 1980s. On the other hand, math Ph.D.'s awarded to women have gone from only 15.5% to 18.1% in this decade, which is more in line with computer science Ph.D.'s earned by women. In 1987, 14.4% of all computer science Ph.D.'s went to women; this number declined to 10.9% the following year. Although the number almost doubled between 1988 and 1989 with women receiving 17.5% of Ph.D.'s, Vetter points out that the number remains very small, at 107. Since these figures include foreign students who are principally male, women constitute a smaller percentage of that total than they do of Ph.D.'s awarded to Americans. But while American women received 21.4% of Ph.D.'s awarded to Americans, that is not encouraging either, says Vetter. Again, the number of American women awarded computer science Ph.D.'s was miniscule, at 72. And taking a longer view, the awarding of significantly fewer bachelor's and master's degrees to women in the late 1980s will be felt in seven to eight years, when they would be expected to receive their Ph.D.'s.How do these figures compare with those of other sciences and engineering? In her 1989 report to the National Science Foundation, “Women and Computer Science,” Nancy Leveson, associate professor of information and computer science at the University of California at Irvine, reports that in 1986, women earned only 12% of computer science doctorates compared to 30% of all doctorates awarded to women in the sciences. Leveson notes, however, that this includes the social sciences and psychology, which have percentages as high as 32 to 50. But the breakout for other fields is as follows: physical sciences (16.4%), math (16.6%), electrical engineering (4.9%), and other engineering ranges from 0.8% for aeronautical to 13.9% for industrial.Those women who do get computer science degrees are not pursuing careers in academic computer science. Leveson says women are either not being offered or are not accepting faculty positions, or are dropping out of the faculty ranks. Looking at data taken from the 1988-89 Taulbee Survey, which appeared in Communications in September, Leveson points out that of the 158 computer science and computer engineering departments in that survey, 6.5 percent of the faculty are female. One third of the departments have no female faculty at all. (See Tables III and IV.)Regarding women in computing in the labor force, Vetter comments that the statistics are very soft. The Bureau of Labor Statistics asks companies for information on their workforce, and the NSF asks individuals for their professional identification; therefore estimates vary. Table II shows that this year, women comprise about 35% of computer scientists in industry. And according to a 1988 NSF report on women and minorities, although women represent 49% of all professionals, they make up only 30% of employed computer scientists. “There is no reason why women should not make up half the labor force in computing,” Betty Vetter says, “It's not as if computing involves lifting 125 pound weights.”The sense of isolation and need for a community was so keen among women in computing, that in 1987 several specialists in operating systems created their own private forum and electronic mailing list called “Systers.” Founded and operated by Anita Borg, member of the research staff at DEC's Western Research Lab, Systers consists of over 350 women representing many fields within computing. They represent 43 companies and 55 universities primarily in the United States, but with a few in Canada, the United Kingdom, and France. Industry members are senior level and come from every major research lab. University members range from computer science undergraduates to department chairs. Says Borg, “Systers' purpose is to be a forum for discussion of both the problems and joys of women in our field and to provide a medium for networking and mentoring.” The network prevents these women, who are few and dispersed, from feeling that they alone experience certain problems. Says Borg, “You can spit out what you want with this group and get women's perspectives back. You get a sense of community.” Is it sexist to have an all-women's forum? “Absolutely not,” says Borg, “It's absolutely necessary. We didn't want to include men because there is a different way that women talk when they're talking with other women, whether it be in person or over the net. Knowing that we are all women is very important.” (Professional women in computer science who are interested in the Systers mailing list may send email to systers-request@decwrl.dec.com)The burden from women in computing seems to be very heavy indeed. Investigators in gender-related research, and women themselves, say females experience cumulative disadvantages from grade school through graduate school and beyond. Because statistical studies frequently come under fire and do not always explain the entire picture, it is important to listen to how women themselves tell their story. In the Sidebar entitled “Graduate School in the Early 80s,” women describe experiences of invisibility, patronizing behavior, doubted qualifications, and so on. Given these experiences, it is not surprising that many women find the academic climate inclement. But while more women may choose to contribute to research in industry, is the computer business really a haven for women, or just the only alternative? In the Sidebar entitled “The Workplace in the late '80s,” women in industry also tell their story and describe dilemmas in a dialogue on academia versus industry; this discussion erupted freely last Spring on Systers. In addition, findings of scholars conducting gender-related research are presented in a report of a workshop on women and computing. Finally, Communications presents “Becoming a Computer Scientist: A Report by the ACM Committee on the Status of Women in Computer Science.” A draft was presented at the workshop and the report appears in its entirety in this issue.
Opinion

Legally speaking: how to interpret the Lotus decision (and how not to)

On June 28, 1990, a federal court judge in Boston made public his decision in favor of Lotus Development Corporation in its software copyright lawsuit against Paperback Software. People in the software industry had been waiting for this decision since the lawsuit was first filed in January 1987, certain that it would be a landmark case and would resolve many vexing questions about copyright protection for user interfaces.The trade press has abounded with varying interpretations of Judge Keeton's opinion in the Lotus case: Some have said the decision is a narrow one, making illegal only the direct copying of another firm's interface [9]; Some have seen it has a much broader ruling—one that will have a chilling effect on development of competitive software products [5]; Others have asserted the case draws a reasonable line, and will have a positive effect overall [4]; Several have argued the ruling will be harmful because it ignores the interests of users of software, and will make standardization of user interfaces impossible to achieve. [3] Still others perceive the opinion as only setting the stage for a new confrontation over the issues in the appellate courts. [1] Lotus has given some indication of how broadly it interprets the Paperback decision by filing a new round of user interface copyright lawsuits against two of its other spreadsheet competitors.his column, rather than just adding one more interpretation of the Lotus decision to the bin of those already expressed, will give the reader a glimpse of the nature of the legal process and of judicial opinions so he or she can see why people can interpret the Lotus opinion differently. The following three factors make it difficult to know what the Lotus decision means: 1) The legal process is not yet over, and the meaning of the case will depend in part on the outcome of this further process. 2) While Judge Keeton makes some statements that seem to suggest his ruling is a narrow one, some of his other statements could be interpreted much more broadly. 3) Even from unambiguous statements Judge Keeton makes, different people can draw reasonable but nonetheless differing inferences about what the judge would do in similar (though somewhat different) cases. For these reasons, it is impossible to know with any certainty what the law concerning copyright protection for user interfaces is in the aftermath of the Lotus decision.
Opinion

Personal computing: Windows, DOS and the MAC

Direct-manipulation or graphical user interfaces (GUIs) are nearly as old as command-line interfaces.1 At the ACM Conference on The History of Personal Workstations, Doug Ross told of drawing on an oscilloscope screen by using his finger to move a spot of light in 1954. Graphic software has been a bastion of direct manipulation since the 195Os, and Douglas Englebart demonstrated direct manipulation of text to large audiences in the 1960s. The style of contemporary direct-manipulation interfaces evolved largely from prototypes developed at the Xerox Palo Alto Research Center (PARC) in the 1970s. The Xerox Star offered a commercial GUI in 1981 (see Figure 1), and several early GUIs, like VisiOn, TopView, and Windows version 1, failed on underpowered PCs. The Macintosh, introduced in 1984, was a major commercial success. Although GUIs have been used for years, the hardware to support them is expensive, so the vast majority of personal computer users still control their software by typing commands. With the introduction of Windows Version 3, Microsoft hopes to move DOS users away from their command-line interface to a direct-manipulation interface. Let us take a quick look at Windows, then compare it to DOS and the Mac.
Research and Advances

Becoming a computer scientist

It is well known that women are significantly underrepresented in scientific fields in the United States, and computer science is no exception. As of 1987- 1988, women constituted slightly more than half of the U.S. population and 45% of employed workers in the U.S., but they made up only 30% of employed computer scientists. Moreover, they constituted only 10% of employed doctoral-level computer scientists. During the same time period, women made up 20% of physicians and, at the doctoral level, 35% of psychologists, 22% of life scientists, and 10% of mathematicians employed in the U.S. On the other hand, there are some disciplines in which women represent an even smaller proportion at the doctoral level: in 1987-88, 8% of physical scientists, and only 2.5% of engineers were women [21].1 The underrepresentation of women in computer science is alarming for at least two reasons. First, it raises the disturbing possibility that the field of computer science functions in ways that prevent or hinder women from becoming part of it. If this is so, those in the discipline need to evaluate their practices to ensure that fair and equal treatment is being provided to all potential and current computer scientists. Practices that exclude women are not only unethical, but they are likely to thwart the discipline's progress, as potential contributors to the field are discouraged from participation. The second reason for concern about the underrepresentation of women in computer science relates to demographic trends in the U.S., which suggest a significant decrease in the number of white males entering college during the next decade. At the same time, the number of jobs requiring scientific or engineering training will continue to increase. Because white males have traditionally constituted the vast majority of trained scientists and engineers in this country, experts have predicted that a critical labor shortage is likely early in the next century [4, 25]. To confront this possibility, the federal government has begun to expend resources to study the problem further. A notable example is the establishment of a National Task Force on Women, Minorities, and the Handicapped in Science and Technology. Their final report, issued in December of 1989, lists a number of government and industrial programs aimed at preventing a labor shortage by increasing the number of women and minorities trained as scientists and engineers [5]. In light of these facts, the Committee on the Status of Women in Computer Science, a subcommittee of the ACM's Committee on Scientific Freedom and Human Rights, was established with the goal of studying the causes of women's continued underrepresentation in the field, and developing proposed solutions to problems found. It is the committee's belief that the low number of women working as computer scientists is inextricably tied up with the particular difficulties that women face in becoming computer scientists. Studies show that women in computer science programs in U.S. universities terminate their training earlier than men do. Between 1983 and 1986 (the latest year for which we have such figures) the percentage of bachelor's degrees in computer science awarded to women was in the range of 36-37%, while the percentage of master's degrees was in the range of 28-30s. During the same time span, the percentage of doctoral degrees awarded to women has only been in the range of 10-12%, and it has remained at that level, with the exception of a slight increase in 1989 [16, 21]. Moreover, the discrepancy between the numbers of men and women continues to increase when we look at the people who are training the future computer scientists: women currently hold only 6.5% of the faculty positions in the computer science and computer engineering departments in the 158 Ph.D.-granting institutions included in the 1988- 1989 Taulbee Survey (See Communications September 1990). In fact, a third of these departments have no female faculty members at all [16]. This pattern of decreasing representation is generally consistent with that of other scientific and engineering fields [4, 25]. It is often described as “pipeline shrinkage”: as women move along the academic pipeline, their percentages continue to shrink. The focus of this report is pipeline shrinkage for women in computer science. We describe the situation for women at all stages of training in computer science, from the precollege level through graduate school. Because many of the problems discussed are related to the lack of role models for women who are in the process of becoming computer scientists, we also concern ourselves with the status of women faculty members. We not only describe the problems, but also make specific recommendations for change and encourage further study of those problems whose solutions are not yet well understood. Of course, our focus on computer science in the university by no means exhausts the set of issues that are relevant to an investigation of women in computer science. Most notably, we do not directly address issues that are of concern exclusively or primarily to women in industry. Although some of the problems we discuss are common to all women computer scientists, there are, without doubt, other problems that are unique to one group or the other. Nonetheless, the committee felt that an examination of the process of becoming a computer scientist provided a good starting point for a wider investigation of women in the field. Clearly, to increase the number of women in industrial computer science, one must first increase the number of women trained in the discipline. Thus, we need to consider why women stop their training earlier than men: too few women with bachelor's degrees in computer science translates into too few women in both industry and academia. Moreover, because of the documented positive effects of same-sex role models [12], it is also important to consider why women drop out in higher numbers than do men even later in their academic training: too few women with doctorate degrees results in too few women faculty members. This in turn means inadequate numbers of role models for younger women in the process of becoming computer scientists.
Opinion

Practical programmer: Software teams

I have often heard the phrase, “We see what we know.” As technicians, we concentrate on technical ways to manage complexity: abstraction, design techniques, high-level languages, and so on. That is what we know best. But when the tale is told of a project that failed, the blame is often laid not on technical difficulties, but on management and interpersonal problems.In the last six months, I have seen firsthand how attention to the social organization of a software team can make a big difference in the success of a development project. I work in a “Research and Development” group. “Research” means that some aspects of the project are experimental—we do not know for sure what is going to work. “Development” means we are expected to produce high-quality software for real users. So while we want to encourage creative thought, we must pay heed to the lessons of commercial software developers in quality assurance, testing, documentation, and project control.Our all-wise project leader decided we also needed to pay heed to the lessons of sociology. In particular, we began to apply the ideas found in Larry Constantine's work on the organization of software teams. Our efforts have resulted in a team that is productive, flexible, and comfortable. I thought these qualities are unusual enough to merit a column on the subject.
Research and Advances

Expert simulation for on-line scheduling

The state-of-the-art in manufacturing has moved toward flexibility, automation and integration. The efforts spent on bringing computer-integrated manufacturing (CIM) to plant floors have been motivated by the overall thrust to increase the speed of new products to market. One of the links in CIM is plant floor scheduling, which is concerned with efficiently orchestrating the plant floor to meet the customer demand and responding quickly to changes on the plant floor and changes in customer demand. The Expert System Scheduler (ESS) has been developed to address this link in CIM. The scheduler utilizes real-time plant information to generate plant floor schedules which honor the factory resource constraints while taking advantage of the flexibility of its components. The scheduler uses heuristics developed by an experienced human factory scheduler for most of the decisions involved in scheduling. The expertise of the human scheduler has been built into the computerized version using the expert system approach of the discipline of artificial intelligence (AI). Deterministic simulation concepts have been used to develop the schedule and determine the decision points. As such, simulation modeling and AI techniques share many concepts, and the two disciplines can be used synergistically. Examples of some common concepts are the ability of entities to carry attributes and change dynamically (simulation—entities/attributes or transaction/parameters versus AI—frames/slots); the ability to control the flow of entities through a model of the system (simulation—conditional probabilities versus AI—production rules); and the ability to change the model based upon state variables (simulation—language constructs based on variables versus AI—pattern-invoked programs). Shannon [6] highlights similarities and differences between conventional simulation and an AI approach. Kusiak and Chen [3] report increasing use of simulation in development of expert systems. ESS uses the synergy between AI techniques and simulation modeling to generate schedules for plant floors. Advanced concepts from each of the two areas are used in this endeavor. The expert system has been developed using frames and object-oriented coding which provides knowledge representation flexibility. The concept of “backward” simulation, similar to the AI concept of backward chaining, is used to construct the events in the schedule. Some portions of the schedule are constructed using forward or conventional simulation. The implementation of expert systems and simulation concepts is intertwined in ESS. However, the application of the concepts from these two areas will be treated separately for ease of presentation. We will first discuss the expert system approach and provide a flavor of the heuristics. The concept of backward simulation and the motive behind it will then be explored along with some details of the implementation and the plant floor where the scheduler is currently being used. We will then highlight some advantages and disadvantages of using the expert simulation approach for scheduling, and, finally, the synergetic relationship between expert systems and simulation.

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