During the last three or four years several investigators have been exploring “semantic models” for formatted databases. The intent is to capture (in a more or less formal way) more of the meaning of the data so that database design can become more systematic and the database system itself can behave more intelligently. Two major thrusts are clear. In this paper we propose extensions to the relational model to support certain atomic and molecular semantics. These extensions represent a synthesis of many ideas from the published work in semantic modeling plus the introduction of new rules for insertion, update, and deletion, as well as new algebraic operators.

A "majority consensus" algorithm which represents a new solution to the update synchronization problem for multiple copy databases is presented. The algorithm embodies distributed control and can function effectively in the presence of communication and database site outages. The correctness of the algorithm is demonstrated and the cost of using it is analyzed. Several examples that illustrate aspects of the algorithm operation are included in the Appendix. patterns used by the DBMP set as it cooperates to arrive at a consensus on update requests. Possible communication patterns include daisy chaining, daisy chaining with timeouts and retransmission (see below), and broadcasting.Voting Rule. This is the rule followed by each DBMP when it considers an update request. Details of the voting rule are sensitive to the DBMP/DBMP communication rule.Request Resolution Rule. After DBMP voting this rule is applied to determine the outcome of the voting. Its details depend upon the particular DBMP/DBMP communication rule used.

Extendible hashing is a new access technique, in which the user is guaranteed no more than two page faults to locate the data associated with a given unique identifier, or key. Unlike conventional hashing, extendible hashing has a dynamic structure that grows and shrinks gracefully as the database grows and shrinks. This approach simultaneously solves the problem of making hash tables that are extendible and of making radix search trees that are balanced. We study, by analysis and simulation, the performance of extendible hashing. The results indicate that extendible hashing provides an attractive alternative to other access methods, such as balanced trees.

Presented is a computation method-the chase-for testing implication of data dependencies by a set of data dependencies. The chase operates on tableaux similar to those of Aho, Sagiv, and Ullman. The chase includes previous tableau computation methods as special cases. By interpreting tableaux alternately as mappings or as templates for relations, it is possible to test implication of join dependencies (including multivalued dependencies) and functional dependencies by a set of dependencies.

1Various approaches to interpreting queries in a database with incomplete information are discussed. A simple model of a database is described, based on attributes which can take values in specified attribute domains. Information incompleteness means that instead of having a single value of an attribute, we have a subset of the attribute domain, which represents our knowledge that the actual value, though unknown, is one of the values in this subset. This extends the idea of Codd's null value, corresponding to the case when thii subset is the whole attribute domain. A simple query language to communicate with such a system is described and its various semantics are precisely defined. We emphasize the distinction between two different interpretations of the query language-the external one, which refers the queries directly to the real world modeled in an incomplete way by the system, and the internal one, under which the queries refer to the system's information about this world, rather than to the world itself. Both external and internal interpretations are provided with the corresponding sets of axioms which serve as a basis for equivalent transformations of queries. The technique of equivalent transformations of queries is then extensively exploited for evaluating the interpretation of (i.e. the response to) a query.