DATA CONSTRUCTORS: ON THE INTEGRATION OF RULES AND RELATIONS

Although the goals and means of rule-based and data-based systems are too different to be fully integrated at the present time, it seems appropriate to investigate a closer integration of language constructs and a better cooperation of execution models for both kinds of approaches. In this paper, we propose a new language construct called constructor that â when applied to a base relation â causes relation membership to become true for all tuples constructable through the predicates provided by the constructor definition. The approach is shown to provide expressive power at least equivalent to PROLOG's declarative semantics while blending well both with a strongly typed modular programming language and with a relational calculus query formalism. A three-step compilation, optimization, and evaluation methodology for expressions with constructed relations is described that integrates constructors with the surrounding database programming environment. In particular, many recursive queries can be evaluated more efficiently within the set-construction framework of database systems than with proof-oriented methods typical for a rule-based approach.Information Systems Working Papers Serie

COLAB : a hybrid knowledge representation and compilation laboratory

Knowledge bases for real-world domains such as mechanical engineering require expressive and efficient representation and processing tools. We pursue a declarative-compilative approach to knowledge engineering. While Horn logic (as implemented in PROLOG) is well-suited for representing relational clauses, other kinds of declarative knowledge call for hybrid extensions: functional dependencies and higher-order knowledge should be modeled directly. Forward (bottom-up) reasoning should be integrated with backward (top-down) reasoning. Constraint propagation should be used wherever possible instead of search-intensive resolution. Taxonomic knowledge should be classified into an intuitive subsumption hierarchy. Our LISP-based tools provide direct translators of these declarative representations into abstract machines such as an extended Warren Abstract Machine (WAM) and specialized inference engines that are interfaced to each other. More importantly, we provide source-to-source transformers between various knowledge types, both for user convenience and machine efficiency. These formalisms with their translators and transformers have been developed as part of COLAB, a compilation laboratory for studying what we call, respectively, "vertical\u27; and "horizontal\u27; compilation of knowledge, as well as for exploring the synergetic collaboration of the knowledge representation formalisms. A case study in the realm of mechanical engineering has been an important driving force behind the development of COLAB. It will be used as the source of examples throughout the paper when discussing the enhanced formalisms, the hybrid representation architecture, and the compilers

Query Evaluation in Deductive Databases

It is desirable to answer queries posed to deductive databases by computing fixpoints because such computations are directly amenable to set-oriented fact processing. However, the classical fixpoint procedures based on bottom-up processing — the naive and semi-naive methods — are rather primitive and often inefficient. In this article, we rely on bottom-up meta-interpretation for formalizing a new fixpoint procedure that performs a different kind of reasoning: We specify a top-down query answering method, which we call the Backward Fixpoint Procedure. Then, we reconsider query evaluation methods for recursive databases. First, we show that the methods based on rewriting on the one hand, and the methods based on resolution on the other hand, implement the Backward Fixpoint Procedure. Second, we interpret the rewritings of the Alexander and Magic Set methods as specializations of the Backward Fixpoint Procedure. Finally, we argue that such a rewriting is also needed in a database context for implementing efficiently the resolution-based methods. Thus, the methods based on rewriting and the methods based on resolution implement the same top-down evaluation of the original database rules by means of auxiliary rules processed bottom-up

MILO : a microarchitecture and logic optimizer

In this report we discuss strengths and weaknesses of logic synthesis systems and describe a system for microarchitectural and logic optimization. Our system uses a set of algorithms for synthesizing SSI/MSI macros from parameterized microarchitecture components. In addition, it uses rules for optimizing both at the microarchitecture and logic level. The system increases designer productivity and requires less design knowledge and experience from circuit engineers