NDLI: Computing as a discipline: preliminary report of the ACM task force on the core of computer science

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The trouble with for-loop invariants

File processing—a correctness approach

A phased programming paradigm

Requiring CS1 students to write requirements specifications: a rationale, implementation suggestions, and a case study

Development and documentation of computer programs in undergraduate computer science programs

The effective use of undergraduates to staff large introductory CS courses

Understanding concurrent programming through program animation

The multiuser calculator: an operating system project

Robots in the laboratory

Computing as a discipline: preliminary report of the ACM task force on the core of computer science

Concurrency in the undergraduate curriculum

Introductory computer science: the case for a unified view

The case for Modula-2 in CS1 and CS2

Integrating software engineering into an intermediate programming class

An introduction to the parallel distributed processing model of cognition and some examples of how it is changing the teaching of artificial intelligence

Introducing parallel processing at the undergraduate level

An undergraduate parallel processing laboratory

Program complexity: a tutorial

Undergraduate theory of computation: an approach using simulation tools

Algorithmic paradigms: examples in computational geometry

Proposed criteria for accreditation of computer information systems programs

Computer science education in China

A major in computer applications for small liberal arts colleges

Assembly language courses in transition

The role of mathematics in the computer science curriculum

A student system development diagrammer

Choosing group projects for advanced systems courses

Introducing knowledge-based projects in a systems development course

Requirement methods: a graduate level course that integrates software engineering principles with information systems theory

A design tool used to quantitatively evaluate student projects

Anatomy of a software engineering project

The role of supercomputers in higher education

Computer science undergraduate capstone course

Interactive graphics: a tool for beginning programming students in discovering solutions to novel problems

Application frameworks: experience with MacApp

Automatic generation of graphic displays of data structures through a preprocessor

A simple technique to motivate structured programming

Using assembly language to teach concepts in the introductory course

Introducing finite automata in the first course

Planning and implementing an internship program for undergraduate computer science students

An industry/academic partnership experiment: a course in artificial intelligence

“Cactus Systems”: a computer science practicum that is more than a capstone

Recruiting more computer science students—what to do after the “glamour” has gone away?

Computing resources in small colleges

A transition from bubble to shell sort

Should short, relatively complex algorithms be taught using both graphical and verbal methods? Six replications

Textbook errors in binary searching

Teaching database using a real DBMS: experience with INGRES

A “course” for data modelling

An intelligent tutor for normal form determination

The computer background of incoming freshman: looking for emerging trends

Retraining pre-college teachers: a survey of state computing coordinators

IBM 3270 full screen interactive programming without CICS

The increasing role of computer theory in undergraduate curricula

Program plagiarism revisited: current issues and approaches

A microcomputer oriented computer literacy course

The impact of menus and command-level feedback on learners' acquisition of data base language skills

A profile of today's computer literacy students: an update

A study of an advance organizer as a technique for teaching computer programming concepts

Using concept expansion and level integration in an introductory computer science course

Teaching programming: a new approach based on analysis skills

Pascal's emulation of a Prolog program

Modeling in Prolog

Teaching recursion using fractals in Prolog

Goal-oriented laboratory development in CS/EE

Continuing education activities of the ACM

An amazing exercise in recursion for CS1 and CS2

Learning recursion as a concept and as a programming technique

Spin-out: the Chinese rings in the classroom

A content analysis of ten introduction to programming textbooks

Should computer science examinations contain “programming” problems?

The reliability of analytic and holistic methods in rating students' computer programs

Computing trends in small liberal arts colleges

Using a model railroad to teach digital process control

Microprogramming a watch: tools for a course in computer organization

Varieties of computer graphics courses in computer science

Computing as a discipline: preliminary report of the ACM task force on the core of computer science

Content Provider	ACM Digital Library
Author	Denning, Peter Gries, David Mulder, Michael C. Comer, Douglas E. Turner, A. Joe Young, Paul R. Tucker, Allen B.
Abstract	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.
Starting Page	41
Ending Page	41
Page Count	1
File Format	PDF
ISSN	00978418
DOI	10.1145/52965.52975
Journal	ACM SIGCSE Bulletin (SGCS)
Volume Number	20
Issue Number	1
Language	English
Publisher	Association for Computing Machinery (ACM)
Publisher Date	1978-02-01
Publisher Place	New York
Access Restriction	One Nation One Subscription (ONOS)
Content Type	Text
Resource Type	Article

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