Alain Pirotte

Constraints for improving the generation of intentional answers in a deductive database

It is shown how intentional answers can be generated as logical consequences of the query and of deduction rules and how integrity constraints can filter out inadequate answers and produce simpler and more informative answers. An efficient organization for the combination of answers and constraints is presented. The authors focus on the design of mechanisms for controlling the generation of intentional answers using integrity constraints. The assertions specified by constraints bear not only on the database but also on queries and intentional answers, since the latter specify sets of values from the database.<<ETX>>

Data Structures for CAD Object Description

Designing databases allowing the inter-application communication of designs in integrated CAD systems is a very complex task. A way of breaking this complexity consists in clearly separating the logical and physical concerns in database design. A data model well-suited to the logical description of elaborate objects such as those handled in CAD in electronics is presented. It is argued to be more adapted to the CAD needs than the hierarchic, network and relational data models.

A precise definition of basic relational notions and of the relational algebra

This paper presents a precise definition of basic relational notions as well as a precise and general definition of the relational algebra. The paper also illustrates a method for developing semi-formal definitions of data models. A nearly formal definition of relations with unordered attributes is given, and algebraic operations are described as operating on and producing relations thus defined. The definition of algebric operations contains, as a special case, the classical definition of the algebra (see e.g. [CODD72]). But, in addition, several operations are generalized. The closure of the algebra is characterized precisely, with the help of an operation for renaming relation attributes.

CQLF---a query language for CODASYL-type databases

This paper describes CQLF (CODASYL Query Language, Flat) [MAN081]. CQLF is a high level language for accessing and manipulating data in databases described using the 1981 ANSI dpANS version of the CODASYL Data Description Language [ANSI81]. CQLF has similarities to typical relational languages, such as SQL [ASTR76, CHAM76] and QUEL [STON76]. CQLF provides capabilities for querying and operating on databases described both in a relational style (having no CODASYL sets, using only values to represent interrecord relationships, and having records with no arrays), and in a network style (using CODASYL sets to represent interrecord relationships, and having records containing arrays).

Comparison of database interfaces for application programming

Abstract The historical evolution of interfaces to databases at the application programming level is analyzed. Emphasis is put on aspects of the data manipulation operations rather than on the data model that they address. Four phases are distinguished in this evolution: “call” interfaces, simple language extensions, non-procedural languages embedded in general purpose languages, and integrated languages. The evolution is explained in terms of the growing needs for more reliable programs written in high level languages, for which programmer efficiency is more important than machine efficiency.

Fundamental And Secondary Issues In The Design Of Non-Procedural Relational Languages

A number of high-level data manipulation languages have been proposed for the relational model. This paper summarizes results of an analysis of languages and attempts to evaluate various criteria as to their capability of accounting for differences among languages. The distinction between fundamental and secondary characteristics of languages is not the result of a speculative exploration of which features should be made available in a relational language. Instead, this distinction is based on a comparison of existing languages as they are described in the literature.

ILL: an English structured query language for relational data bases

A retrieval language for relational data bases is presented and its similarity, both syntactic and semantic, with a particular form of queries in English is shown. A definition of the essential features of the language is given and it is illustrated with examples. Queries in ILL always have a straightforward paraphrase in English.

Integrating two descriptions of taxonomies with materialization

This paper presents a precise correspondence between two views of taxonomic hierarchies: an intensional view based on concepts and an extensional view based on categories, i.e., subsets of the population of individuals analyzed in terms of these concepts. The correspondence is described with materialization, a generic relationship defined for object-oriented and entity-relationship information models. The paper introduces materialization and shows how it provides a systematic bridge between both views of taxonomies.

Associating types with domains of relational data bases

In the DB field, there are two interpretations (or perceptions or schools of thought) concerning the relational model:n (a) one interpretation considers that the relational model contribution to the DB field essentially consists in the presentation of a clear and simple notion of (flat) file, and that many users will be very satisfied to describe their data structures as tables;n (b) another interpretation considers the relational model as a (reasonable) support for a (weak) entity relationship model.

Controlled generation of intensional answers

Intensional answers are conditions that tuples of values must satisfy to belong to the usual extensional answer of a query addressed to a deductive database. This paper motivates the concept of intensional answers and introduces a general method for generating them as logical consequences of the query and of deduction rules. It then shows how integrity constraints can filter out inadequate answers and produce simpler and more informative answers. An efficient organization for the combination of answers and constraints is described. Beyond the mechanics of answer generation, the interest of the approach also depends on a strategy for selecting answers to a user submitting a query. This requires techniques for user modeling and dialogue management similar to those required for expert systems.