This paper examines the ongoing debate over whether computing should be classified as a scientific discipline. Drawing on Tedre (2011), it traces computing's emergence as a distinct academic field following the development of stored-program paradigms in the mid-twentieth century, and explores how pioneers such as Donald Knuth helped separate it from mathematics and electrical engineering. The paper identifies three core reasons why these debates remain unresolved: the absence of a shared definition of science, the lack of consensus on computing as a discipline, and inconsistent use of scientific terminology. It also considers the various ways computer science can be understood — as a set of activities, a mode of thinking, or an institutional body of researchers — and reflects on computing's ongoing identity crisis.
Computing has been described as both a branch of science and an academic discipline, and its precise classification has been debated for a long time. The central concern in this discussion is the status of computing with regard to being scientific. Computing began developing in the mid-twentieth century as a distinct academic discipline following the emergence of several stored-program paradigms. Throughout the history of modern computing, different approaches to computing as a discipline have been proposed, and most debates revolve around the question of whether computing is, in fact, a scientific discipline.
In debates concerning the relationship between computing and other established disciplines, the scientific nature of computing — including its connections to mathematics, engineering, and the natural sciences — has been the most contested area. The central questions are typically whether computer science should be considered a science in the broad sense, or more narrowly as a natural science. Different researchers argue that computer scientists do primarily theoretical work similar to mathematics, and that, like mathematics, computing therefore does not qualify as a natural science.
After the emergence of stored-program structures, specialists in computing began to develop a disciplinary identity related to their field. However, separating computing from mathematics required the combined efforts of various computing pioneers. Donald Knuth is one prominent example: not only a pioneer in the field but also a specialist in theoretical computer science and a recognized mathematician, he was among those who helped establish computing's independent identity.
When computer science achieved independence from electrical engineering and mathematics, there began to be a push toward viewing computing as a scientific discipline in its own right. Many questions were raised about whether computer science involved the study of algorithms, automation, programming, or something else entirely.
Debates over whether computing should be classified as a science tend to circle back to the same three core issues. First, there is no agreed-upon view of science that participants in these debates can use as a shared foundation. Second, no definitive agreement exists on how to define computing as a discipline. Third, when debates about computing are conducted, scientific terminology is used inconsistently. These issues make such discussions ambiguous, largely because they end up being debates about science in general rather than about computing in particular.
Because debaters have no shared view of science, there is little consensus on how the term "science" should be applied across different fields. As a result, differing conceptions of science have a significant impact on arguments about the scientific nature of computing. Various characteristics of science have been proposed, including objectivity, simplicity, clarity, explanatory power, testability, consistency, and the ability to distinguish between relevant and irrelevant data.
"Scientific method and proposed characteristics of science"
"Various ways of understanding computer science as a field"
Throughout history, computing has faced a crisis of identity. The future of computing as a discipline remains a matter of great concern. Although there are differences between computers and instruments such as spectrometers and microscopes, computing will still be affected by the same fundamental questions that have shaped the science of microscopy and other instrument-based disciplines (Tedre, 2011).
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