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On the specification of behavioural constraints
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Source International Conference on Management of Data archive
Proceedings of the 1980 workshop on Data abstraction, databases and conceptual modeling table of contents
Pingree Park, Colorado, United States
Pages: 115 - 117  
Year of Publication: 1980
ISBN:0-89791-031-1
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Author
Flaviu Cristian  Computing Laboratory, University of Newcastle upon Tyne, Newcastle upon Tyne, NEI 7RU, England
Sponsors
NBS : National Bureau of Standards
SIGART: ACM Special Interest Group on Artificial Intelligence
SIGMOD: ACM Special Interest Group on Management of Data
SIGPLAN: ACM Special Interest Group on Programming Languages
Publisher
ACM  New York, NY, USA
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ABSTRACT

When designing information processing systems, the key problem is to find what symbols and constructs (available in some given language) should be used so as to be able to answer the questions that the users want to ask and to perform the state transitions that the users have to perform in order to keep in step with some reality that is being modelled. If the language that is being used cannot be interpreted directly by the software of a computer (e.g. set theory, algebra, semantic networks), the resulting model is called an abstract model (e.g. a specification, a data base schema). If all of the symbols and constructs used to express the model can be interpreted by a computer, the model is a concrete implementation (e.g. a data base system). Both the abstract and concrete models capture some aspects of the reality that is modelled. They differ with respect to the languages in which they are expressed. The choice of the languages which are appropriate for writing such models is a subject of intensive debate. The recent workshop on Data Abstraction, Data Bases and Conceptual Modelling has shown that this debate is not likely to diminish in the near future. In the context of this debate, however, a common opinion was expressed several times by data base participants: the data models used to specify data base schemas are lacking to support the specification of operations tailored to particular application environments. It is therefore expected that in the context of data base modelling, the integration of operations (behaviour) with data (structure) will be one of the most fertile research areas for the next few years.


REFERENCES

Note: OCR errors may be found in this Reference List extracted from the full text article. ACM has opted to expose the complete List rather than only correct and linked references.

 
1
C.A.R. Hoare: Proof of correctness of data representations. Acta Informatica 1,4,1972.
 
2
W. Wulf, R. London, M. Shaw: Abstraction and verification in Alphard, Introduction to language and methodology. TR, Carnegie-Mellon Univ. 1976.
 
3
J. Guttag, J. Horning: Formal specification as a design tool. TR, Xerox PARC, 1980.
 
4
F. Cristian: Specification and implementation of data types with exceptions. TR, Univ. of Newcastle upon Tyne, 1980.
 
5
J. McCarthy: A basis for a mathematical theory of computation. In Computer Programming and Formal Systems, P. Braffort and D. Hirschberg (Eds.) North Holland Pub. Co., 1963.
 
6
F. Cristian: Le traitement des exceptions dans les programmes modulaires. Doctoral Thesis, Univ. of Grenoble, 1979.
 
7
M. Hammer, D. McLeod: Semantic integrity in a relational data base system. Proc. of the Int. Conf. on Very Large Data Bases, U.S.A. 1975.
 
8
K. Eswaran, D. Chamberlin: Functional specification of a subsystem for data base integrity. Proc. of the Int. Conf. on Very Large Data Bases, U.S.A. 1975.
 
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J. Goguen: Abstract errors for abstract data types. In Formal Description of Programming Concepts. E. Neuhold (Ed.) North-Holland Pub. Co., 1978.
 
12
F. Cristian: Exception handling and software-fault tolerance. Proc. 10th Int. Symp. on Fault Tolerant Computing, Japan, 1980.


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