The article of record as published may be found at http://doi.org/10.1093/comjnl/bxs065

Computer science emerged as a discipline about 70 years ago, some 2,000 years after the Greeks created mathematics, physics and philosophy. However, the questions “What is Mathematics?” and “What is Physics?” remain unanswered, and it is not surprising that the specification of computation likewise remains unresolved, in spite of the increasing centrality of the computing discipline.

This paper examines the limitations of Turing Machines as a complete model of computation, and presents several models that extend Turing Machines. Dynamic interaction of clients and servers on the Internet, an infinite adaptation from evolutionary computation, and robots sensing and acting are some examples of areas that cannot be properly described using Turing Machines and algorithms. They require new models of computation going beyond Turing Machines. We refer to such new models as superTuring models of computation. Three superTuring models of computation, namely Interaction Machines, the π calculus and the $-calculus are presented and explained, focussing on why they are better for the solution of computational problems. We expect that superTuring computation will become the central programming paradigm in the future.

This panel will discuss major issues and challenges in computer science education across a wide range of institutions. It originates from a report developed by the Education Working Group of the Strategic Directions in Computing Research (SDCR) Workshop. That report appears in its entirety in the ACM Computing Surveys issue [Wegner96] which is distributed to all attendees to this SIGCSE 97 conference.) In this panel, we will discuss the general aims and accomplishments of the SDCR conference, highlighting the specific recommendations of the Education Working Group. We will outline ideas for improving the quality and effectiveness of computer science programs at the undergraduate, graduate, and K-12 levels. We will also argue for the creation of a Resource Center for developing and distributing computer science and engineering curricular materials, including the idea of developing a "Virtual Computing University."

Our goals are to review the evolution of curriculum develop-men~examine alternative curricular approaches, and explore new trends in the design of introductory computer science courses.We review the historical evolution of introductory computer science curricula, including Curriculum 68 and 78, the Liberrd Arts Model Curriculum of 1986, the Deming committee's comprehensive (broad) approach in 1989, and the implementation of this approach in the recent report Computing Curricula 1991.Alternative approaches to introductory curriculum development are presented in terms of dichotomies such as depth versus breadth, single vemus multiple paradigm, conceptual versus pmctical, and active versus passive learning.The role of programming, mathematics, laboratories, and visualization in the curriculum is examined, We then focus more specifically on the goals and scope of specitlc approaches to the introductory courses, examining the role of introductory computer science within the technical and social context of the discipline as a whole.

article Free Access Share on Object-oriented megaprogramming (panel) Authors: Peter Wegner View Profile , William Scherlis View Profile , James Purtilo View Profile , David Luckham View Profile , Ralph Johnson View Profile Authors Info & Claims ACM SIGPLAN NoticesVolume 27Issue 10Oct. 1992 pp 392–396https://doi.org/10.1145/141937.141968Published:31 October 1992Publication History 1citation258DownloadsMetricsTotal Citations1Total Downloads258Last 12 Months9Last 6 weeks1 Get Citation AlertsNew Citation Alert added!This alert has been successfully added and will be sent to:You will be notified whenever a record that you have chosen has been cited.To manage your alert preferences, click on the button below.Manage my AlertsNew Citation Alert!Please log in to your account Save to BinderSave to BinderCreate a New BinderNameCancelCreateExport CitationPublisher SiteeReaderPDF

The design space of object-based languages is characterized in terms of objects, classes, inheritance, data abstraction, strong typing, concurrency, and persistence. Language classes (paradigms) associated with interesting subsets of these features are identified and language design issues for selected paradigms are examined. Orthogonal dimensions that span the object-oriented design space are related to non-orthogonal features of real languages. The self-referential application of object-oriented methodology to the development of object-based language paradigms is demonstrated.

Ada is rich in the variety of its abstraction mechanisms. It has both a data abstraction mechanism (packages with private data types) that supports a functional programming style and a program abstraction mechanism (generic program units) that supports an object-oriented program style. Tradeoffs between data and program abstraction are examined and it is pointed out that Ada discourages program abstraction because program units are not first-class objects. It is shown how program units could be made into first-class objects by introducing closures as values for functions and records with function components as values for packages. Further unification by allowing types to be first-class objects conflicts with the requirement of compile-time type invariance. The relaxation of this requirement in a manner that preserves type consistency is examined and leads to a notion of value for types as tuples of operations. It is suggested in the conclusion that our understanding of abstraction for object-oriented languages and of other language design, implementation, and environment issues will have progressed sufficiently by 1985 to warrant the design of a successor to Ada by the late 1980s.

Three notations for concurrent programming are compared, namely CSP, Ada, and monitors. CSP is an experimental language for exploring structuring concepts in concurrent programming. Ada is a general-purpose language with concurrent programming facilities. Monitors are a construct for managing access by concurrent processes to shared resources. We start by comparing "lower-level" communication, synchronization, and nondeterminism in CSP and Ada and then examine "higher-level" module interface properties of Ada tasks and monitors.

Sponsored by the Department of Defense, Ada is a programming language that embodies and enforces many modern software methodologies. Thus, the introduction of the language gives the opportunity for improvements in software reliability, maintainability, and clarity. Ada also offers some unique educational challenges and opportunities, so this panel will focus on some of the requirements for industrial, graduate, and undergraduate Ada education. In particular, the panel will explore different teaching methodologies, and will share their experiences in teaching the language.

The programming language field is certainly one of the most important subfields of computer science. It is rich in concepts, theories, and practical developments. The present paper attempts to trace the 25 year development of programming languages by means of a sequence of 30 milestones (languages and concepts) listed in more or less historical order. The first 13 milestones (M1–M13) are largely concerned with specific programming languages of the 1950's and 1960's such as Fortran, Algol 60, Cobol, Lisp, and Snobol 4. The next ten milestones (M14–M23) relate to concepts and theories in the programming language field such as formal language theory, language definition, program verification, semantics and abstraction. The remaining milestones (M24–M30) relate to the software engineering methodology of the 1970's and include a discussion of structured programming and the life cycle concept. This discussion of programming language development is far from complete and there are both practical developments such as special purpose languages and theoretical topics such as the lambda calculus which are not adequately covered. However, it is hoped that the discussion covers the principal concepts and languages in a reasonably nontrivial way and that it captures the sense of excitement and the enormous variety of activity that was characteristic of the programming language field during its first 25 years.

A notation for specifying translation networks is analyzed and shown to be a special case of a notation for specifying functions. Cancellation of domains and ranges and associativity is derived more simply than in a previous paper by Sklansky, Finkelstein, and Russell.