Computing as a discipline: preliminary report of the ACM task force on the core of computer science
Authors: Denning Peter , Comer Douglas E. , Gries David , Mulder Michael C. , Tucker Allen B. , Turner A. Joe , Young Paul R. 
Published: July 2004

It is ACM's 40th year and an old debate continues. Is computer science a science? An engineering discipline? Or merely a technology, an inventor and purveyor of computing commodities? What is the intellectual substance of the discipline? Is it lasting, or will it fade within a generation? Do core curricula in computer science and engineering accurately reflect the field? How can theory and lab work be integrated in a computing curriculum?
We project an image of a technology-oriented discipline whose fundamentals are in mathematics and engineering — for example, we represent algorithms as the most basic objects of concern and programming and hardware design as the primary activities. The view that “computer science equals programming” is especially strong in our curricula: the introductory course is programming, the technology is in our core courses, and the science is in our electives. This view blocks progress in reorganizing the curriculum and turns away the best students, who want a greater challenge. It denies a coherent approach to making experimental and theoretical computer science integral and harmonious parts of a curriculum.
Those in the discipline know that computer science encompasses far more than programming. The emphasis on programming arises from our long-standing belief that programming languages are excellent vehicles for gaining access to the rest of the field — but this belief limits out ability to speak about the discipline in terms that reveal its full breadth and richness.
The field has matured enough that it is now possible to describe its intellectual substance in a new and compelling way. In the spring of 1986, ACM President Adele Goldberg and ACM Education Board Chairman Robert Aiken appointed this task force with the enthusiastic cooperation of the IEEE Computer Society. At the same time, the Computer Society formed a task force on computing laboratories with the enthusiastic cooperation of the ACM.

The charter of the task force has three components:

Present a description of computer science that emphasizes fundamental questions and significant accomplishments.

Propose a new teaching paradigm for computer science that conforms to traditional scientific standards and harmoniously integrates theory and experimentation.

Give at least one detailed example of a three-semester introductory course sequence in computer science based on the curriculum model and the disciplinary description.

We immediately extended our task to encompass computer science and computer engineering, for we came to the conclusion that in the core material there is no fundamental difference between the two fields. We use the phrase “discipline of computing” to embrace all of computer science and engineering. The rest of this paper is a summary of the recommendation.
The description of the discipline is presented in a series of passes, starting from a short definition and culminating with a matrix as shown in the figure. The short definition:

Computer science and engineering is the systematic study of algorithmic processes that describe and transform information: their theory, analysis, design, efficiency, implementation, and application. The fundamental question underlying all of computing is, “What can be (efficiently) automated?”

The detailed description of the field fills in each of the 27 cells in the matrix with significant issues and accomplishments. (That description occupies about 16 pages of the report.)
For the curriculum model, we recommend that the introductory course consist of regular lectures and a closely coordinated weekly laboratory. The lectures emphasize fundamentals; the laboratories emphasize technology and know-how. The pattern of closely coordinated lectures and labs can be repeated where appropriate in other courses. The recommended model is traditional in the physical sciences and in engineering: lectures emphasize enduring principles and concepts while laboratories emphasize the transient material and skills relating to the current technology.