Article Free Access Share on Knowledge discovery in reaction databases Authors: J. Royce Rose Department of Computer Science, State University of N. Y. at Stony Brook, Stony Brook, New York Department of Computer Science, State University of N. Y. at Stony Brook, Stony Brook, New YorkView Profile , Herbert Gelernter Department of Computer Science, State University of N. Y. at Stony Brook, Stony Brook, New York Department of Computer Science, State University of N. Y. at Stony Brook, Stony Brook, New YorkView Profile Authors Info & Claims CIKM '93: Proceedings of the second international conference on Information and knowledge managementDecember 1993 Pages 714–716https://doi.org/10.1145/170088.170464Published:01 December 1993Publication History 0citation184DownloadsMetricsTotal Citations0Total Downloads184Last 12 Months2Last 6 weeks2 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

Abstract When implementing large programs, it sometimes happens that the sheer size of the problem makes it difficult to apply recommended techniques for program designs. One example of this occurs when the size and complexity of a single data structure become great. It is naturally desirable that the details of the structure remain hidden from those modules which access it. For simple data structures this poses no problem since the data structure can be maintained by a separate data structure executive (effectively a cluster or class) which is the only module concerned with the physical details of the structure. However, for data structures which require very large executive procedures for maintenance and complex data declarations, it is necessary to partition the structure into substructures, each maintained by a separate module. If this is done in a straightforward manner, it will not be possible for other program modules to access properly parts of the structure unless that module can ‘see’ the various relationships of the substructures. Data metastructures are devices which, when properly employed, allow access to all parts of a partitioned data structure without the accessing module being aware of the partition.

The technique of programming within the framework of the so-called Newell-Shaw-Simon (NSS) associative list memory is currently the subject of much interest among workers in the area of advanced programming research. Unfortunately, committing a given program to list memory generally entails accepting a significant loss of speed and efficiency in information processing, so that the advantages accruing from the use of list memory must be carefully balanced against its weaknesses. This paper is concermed with the system requirements of a digital computer for which the use of list techniques is to be competitive with standard programming, so that the particular memory organization for a given problem may be chosen on the basis of suitability and ease of programming alone. A description of a list-processing 7090-type computer is appended in order to make our discussion concrete, although engineering and economic feasibility is not implied.

A compiled computer language for the manipulation of symbolic expressions organized in storage as Newell-Shaw-Simon lists has been developed as a tool to make more convenient the task of programming the simulation of a geometry theorem-proving machine on the IBM 704 high-speed electronic digital computer. Statements in the language are written in usual Fortran notation, but with a large set of special list-processing functions appended to the standard Fortran library. The algebraic structure of certain statements in this language corresponds closely to the structure of an NSS list, making possible the generation and manipulation of complex list expressions with a single statement. The many programming advantages accruing from the use of Fortran, and in particular, the ease with which massive and complex programs may be revised, combined with the flexibility offered by an NSS list organization of storage make the language particularly useful where, as in the case of our theorem-proving program, intermediate data of unpredictable form, complexity, and length may be generated.