A relational model of data for large shared data banks
Communications of the ACM
Data base standardization: a status report
SIGMOD '75 Proceedings of the 1975 ACM SIGMOD international conference on Management of data
Computer Database Organization, 2nd Ed
Computer Database Organization, 2nd Ed
Programming with abstract data types
Proceedings of the ACM SIGPLAN symposium on Very high level languages
Modeling the storage architectures of commercial database systems
ACM Transactions on Database Systems (TODS)
An object-oriented approach to database system implementation
ACM Transactions on Database Systems (TODS)
A unifying logic-based formalism for semantic data models
CSC '91 Proceedings of the 19th annual conference on Computer Science
Data abstraction, views and updates in RIGEL
SIGMOD '79 Proceedings of the 1979 ACM SIGMOD international conference on Management of data
Conceptual-to-internal mappings in commercial database systems
PODS '84 Proceedings of the 3rd ACM SIGACT-SIGMOD symposium on Principles of database systems
On the Algebraic Specification of Databases
VLDB '82 Proceedings of the 8th International Conference on Very Large Data Bases
Proceedings of the 1980 workshop on Data abstraction, databases and conceptual modeling
An overview of recent data base research
ACM SIGMIS Database
| Hi-index | 0.00 |
The concept of abstract data types has emerged from programming language research as a device to encourage and facilitate structured and modular programming [1]. It separates the abstraction of a data object from its implementation. The user of an abstract data type only concerns himself with the behavioral semantics of the type: what meaningful operations can be applied to objects of the type; the internal representation and structure of the type is unknown to him. In this way, irrelevent detail is suppressed and meaningfulness of programs enhanced. What application does this concept have to the area of data bases? There are some obvious similarities between the principle of abstraction and the concept of data independence of data bases [2]. Data independence means that application programs that utilize a data base do not need to know either the physical or the structural organization of the data base, but can relate to it purely on a logical plane. As with data abstractions, the goal is clarity and modifiability of programs, resulting from concentration on semantics rather than representation.