Michael S. Mahoney

The histories of computing(s)

Abstract The first electronic digital computers were variations on the protean design of a limited Turing machine, which described not a single device but a schema, and which could assume many forms and could develop in many directions. It became what various groups of people made of it. The computer thus has little or no history of its own. Rather, it has histories derived from the histories of the groups of practitioners who saw in it, or in some yet to be envisioned form of it, the potential to realise their agendas and aspirations. What kinds of computers we have designed since 1945, and what kinds of programs we have written for them, reflect not so much the nature of the computer as the purposes and aspirations of the communities who guided those designs and wrote those programs. Their work reflects not the history of the computer but the histories of those groups, even as the use of computers in many cases fundamentally redirected the course of those histories. Separating the histories of computing, or perhaps even of computings, shifts attention to the major communities, or bodies of shared disciplinary practices, who embraced the new device and helped to shape it by adapting it to their needs and aspirations.

Finding a History for Software Engineering

Historians and software engineers are both looking for a history for software engineering. For historians, it is a matter of finding a point of perspective from which to view an enterprise that is still in the process of defining itself. For software engineers, it is the question of finding a usable past, as they have sought to ground their vision of the enterprise on historical models taken from science, engineering, industry, and the professions. The article examines some of those models and their application to software engineering.

What Makes the History of Software Hard

Creating software for work in the world has meant translating into computational models the knowledge and practices of the people who have been doing that work without computers. What people know and do reflects their particular historical experience, which also shapes decisions about what can be automated and how. Software thus involves many histories and a variety of sources to be read in new ways.

Software as science: science as software

Software should be of great interest to historians of science. That may seem strange, given that it is of such recent origin. Software is no older than the modern electronic computer and the activity of writing programs for it. It is still experiencing growing pains. Yet, over the past fifty years, it has become the subject of its own thriving science and a ubiquitous medium for pursuing other sciences. In both instances software represents a new kind of science. It is what Herbert Simon calls a “science of the artificial.”2 There is nothing natural about software or any science of software. Programs exist only because we write them, we write them only because we have built computers on which to run them, and the programs we write ultimately reflect the structures of those computers. Computers are artifacts, programs are artifacts, and models of the world created by programs are artifacts. Hence, any science about any of these must be a science of a world of our own making rather than of a world presented to us by nature.3 What makes it both challenging and intriguing is that those two worlds meet in the physical computer, which enacts a program in the world. Their encounter has posed new and difficult epistemological questions concerning what we can know both about the workings of the models and about the relation of the models to the phenomena they purport to represent or simulate. Answers to those questions would seem to depend, at least in part, on understanding programs as dynamic systems.

Changing canons of mathematical and physical intelligibility in the later 17th century

Abstract Learning to use the new calculus in the late 17th century meant looking at quantities and configurations, and the relationships among them, in fundamentally new ways. In part, as Leibniz argued implicitly in his articles, the new concepts lay along lines established by Viete, Fermat, Descartes, and other “analysts” in their development of algebraic geometry and the theory of equations. But in part too, those concepts drew intuitive support from the new mechanics that they were being used to explicate and that was rapidly becoming the primary area of their application. So it was that the world machine that emerged from the Scientific Revolution could be both mechanically intelligible and mathematically transcendental.

A study and critique of the teaching of the history of science and technology. Interim report by the committee on undergraduate education of the history of science society (U.S.A.)

Summary The history of science and technology has been a scholarly discipline with little attention given to the special needs of undergraduate teaching. What needs to be done to transform a discipline to an undergraduate subject? Suggestions include using the relation between science and technology as well as the role of interpreters in formulation of the popular world view. Relations with science and history departments are considered. Curriculum materials are surveyed with some recommendations for correcting deficiencies.

In Our Own Image: Creating the Computer

In the years following World War II, the world appeared to be entering a new age, the Atomic Age, portrayed as an era of prosperity fueled by energy “too cheap to meter”. Automobiles, trains, planes, homes, industry would all draw their power from nuclear reactors of various sizes and formats, and society would assume new forms around the possibilities of ubiquitous, unlimited energy. Some of those visions became reality, some turned into nightmares. Fifty years later we draw on atomic power, but the phrase “atomic age” is more likely than not to evoke images of a nuclear winter of desolation.

What Makes Computer Science a Science

From the beginning computer science has been a contentious subject, with practitioners disagreeing on whether computers and computing could (or indeed should) be the subject of a science and, if so, what kind of science it should be. As the subject has developed, it has grounded computing in a body of profound and elegant mathematical knowledge relating abstract machines to computational processes, thereby creating the field of “applied abstract algebra” and bringing the most advanced mathematics of the twentieth century to b ear on the defining technology of our age. That theory has led the development of powerful tools for programming and for monitoring the operations of computers, thus placing the power of the computer in the hands of professional and non -professional users alike. Software engineering has generally followed suit, taking as its (as yet unfulfilled) goal the automation of the processes of designing and producing the software systems that automate processes in the world. Indeed, much of its literature is redolent with the language of machine-based production. Alongside this mainstream of development has flowed a current critical of its focus on the computer and aimed at a broader view of the subject and of humans both as agents and subjects of automation. These critics argue that, properly construed, informatics (informatique, Informatik, informatica) extends beyond the computer and its operations to include its social context and that a commensurate theory of informatics would reach beyond mathematics to encompass social and political theory. Despite the failure so far to create a viable alternative to computer science as currently construed, recent trends in software engineering suggest how these two streams of thought may be converging.

Technikleitbilder auf dem prufstand: Leitbild-assessment aus sicht der informatik und computer-geschichte (Visions of technology on the test-bed: Assessment of guiding visions from the perspective of the history of computing and informatics) [Book Review]

reorganization, long believed impossible, as the successors to the Bureaus of Ordnance and Ships—which had long impeded innovation and progress with their idiotic internal warfare—were merged into the Naval Sea Systems Command. The story ends with a magnificent table, which on one page summarizes 40 years of Navy tactical computers, from 1956 to 1996. I found only two major omissions. First, almost nothing is said about the interaction between the Navy and Congress about NTDS. This omission is understandable, because although Congressional maneuvering is always important, it usually is conducted out of the sight and hearing of the actual workers like Boslaugh. Second, the precise nature of the command and control systems are never presented in detail. This is undoubtedly because of security considerations. However, the Navy is surely aware today that although these details are supposed to be secret, the intelligence services of our friends and enemies will have certainly bought any computing secrets that are more than a year old. Boslaugh provides a valuable eight-page appendix of acronyms and abbreviations; a four-page appendix showing the organization chart of the 1959 NTDS Organization of Univac, the principal contractor; a bibliography of 275 items; and a splendid index. The author hopes that others may learn from his story and to that end lists the six factors that he believes contributed to the project’s success:

Probing the elephant: how do the parts fit together?

In keeping with the themes and objectives of the conference, the authors of the five main papers attempted to approach software as a whole, each viewing it from a different perspective. The result may seem at first a bit like the proverbial report of a team of blind persons on their tactile investigation of an elephant: depending on the part they touched, it resembled a tree, a snake, a rope, and so on. At least they had an elephant to touch. Here, the authors and their commentators are grappling with a seemingly amorphous object, appropriately called software, which is invisible and intangible, yet produces visible and tangible effects in the world. To have those effects, it must run on hardware, and at a fundamental level it must fit that hardware so precisely as to become indistinguishable from it. Yet, at higher levels of abstraction software has an existence independent of hardware, which indeed has all but disappeared from the view of a large majority of people engaged in computing. Users and producers program virtual machines defined in terms of concepts rather than circuits and reflecting human purposes rather than computer architecture. Software encompasses both the product and the means of that process. That is, one may think in terms of virtual machines because software exists to translate the virtual into the real. Software is thus multilayered, and complexity makes it hard to see through the layers. Depending on where one stands and how one tries to grab hold of it, software assumes a variety of appearances.