Discusses a paradigm and prototype system for the design-time expression, checking and automatic implementation of the semantics of database updates. Enforcement rules are viewed as the implementation of constraints and are specified, checked for consistency, and then finally mapped to object-oriented code during database design. A classification of enforcement rule types is provided as a basis for these design activities, and the general strategy for specification, analysis and implementation of these rules within a semantic modeling paradigm is discussed. SORAC (Semantics, Objects, Relationships And Constraints), a prototype database design system of the University of Rhode Island, is also described.

A metamodel for describing the semantics of object-oriented data models is presented. This metamodel supports the automatic generation of conceptual database design tool software for a variety of data models. Data modeling is viewed as having three levels of abstraction. The physical database, at the lowest level, stores objects and relationships. Specific data models reside at the middle level. A data model consists of object types and relationship types. The metamodel resides at the highest level and is composed of metaobject types and metarelationship types. To illustrate the utility of the metamodel, the representation of the ORION data model is presented.>

A description is given of WharfRat, a knowledge base of data type implementations which employs case-based reasoning as its primary retrieval mechanism. Given a description of an abstract data type, it retrieves the most similar data type implementation in the knowledge base. The focus of the study is the process by which two case descriptions are compared. Similarity between data types is modeled by a fuzzy relation. A set of similarity matching rules has been developed and implemented. The system employs a general, graph-based data model in which object types are organized in a specialization network. Abstract data representations are built using the constructs of the general data model. This system is the first step toward developing a complete programming-by-similarity system.>

Describes the Data Model Compiler (DMC) project. The goal of the DMC is to generate automatically data-model and application-specific database system software. A component of the DMC, called SeaWeed, automatically generates conceptual database design tool software for specific data models using the software reusability approach. The technique of design reuse is used to derive the requirement specification of the software being generated, and the mechanism of code reuse is adopted to produce the necessary reusable software components. The authors present SeaWeed's software generation paradigm including the derivation of requirement specifications, the formal representation of design reuse, and the implementation and organization of the reusable software component library.>

The development of a knowledge-aided engineering environment, an emerging concept that aims to exploit the commonality and the adaptability of the knowledge underlying design and manufacturing, is presented. The following objectives are critical for achieving this end: (1) the definition of an integrated set of conceptual and physical data models that can support the unique requirements of the engineering and manufacturing environments and also promote the sharing of common knowledge; (2) the production of a mechanism for the automatic generation of such models and their accompanying software for specific application domains; (3) the creation of a strategy for knowledge-driven dialogue management; and (4) the specification of a rule base that supports the integration of the dialogue manager and the data model generator into a functional prototype. An example illustrating the KAD/KAM (knowledge-aided design/knowledge-aided manufacturing) environment is presented.>

The authors consider data reorganization in a dynamically reconfigurable distributed database system. The network environment they study is a dynamic system prototype called Driftwood. They present reallocation strategies corresponding to different network reconfiguration and then address the nonblocking reorganization approach. They cover the implementation strategies, impact on user transaction processing, and efficiency. The authors present an algorithm to construct a parallel reorganization scheduler that is expected to minimize the system recovery time.>

The authors address the data allocation problem in a dynamically reconfigurable distributed database system. Following the description of the system model and the consequences of node movement, several dynamic allocation strategies are presented. A distributed candidate-selection algorithm using the data from the accounting system in the database servers is proposed to reduce the number of files and nodes considered in reallocation. The allocation algorithms choose the optimal assignment using heuristic benefit functions and greedy search strategy. The experimental results demonstrate the accuracy and efficiency of the allocation algorithms.>

A discussion is presented of the integration of analogical reasoning into a knowledge base system. Such a system would retrieve stored examples on the basis of similarity to a current problem. A data model that permits a case-oriented representation is developed. The cases are organized in memory using an indexing scheme that permits directed search. The search strategy is based on the goal of the problem. Incorporating this type of reasoning into a database will provide a powerful search strategy which does not require users to be familiar with the organization of the database.>

The D-OBE (Distributed Office By Example) language for distributed office information systems is introduced. D-OBE is an extension of the OBE (Office By Example) and QBE (Query By Example) languages. A major problem was the design of a language simple enough for office workers and yet sufficiently powerful to handle the many facilities of a distributed office system. It is suggested that D-OBE achieves these goals by employing the proven user friendly QBE interface. Surprisingly few extensions to QBE were needed. The states of the servers are presented to the user as QBE tables that are manipulated by the familiar QBE operations. Another problem was to design D-OBE such that it would fit ‘any’ office. D-OBE is based on the observation that large offices divide their tasks among departments. Each department is made responsible for accomplishing its tasks, and is given control over the facilities to do it. A department will thus control its ‘D-OBE cluster’, which is a number of workstations connected to a database, mail, hardcopy and name server. Such a cluster may cooperate with other clusters. The use of logical ports help to reconfigure the network as the structure and goals of the office evolve. A naming server provides the ‘yellow pages’ of the network services. D-OBE identifies for each data object, workstation and server the person responsible for its proper handling.

An information systems major is presented as a second offering by a computer science department. The rationale for the degree program is based upon the demands of industry for graduates skilled in database and information systems. Courses in COBOL, business data processing, database management, and systems analysis are included in the information systems curriculum to prepare the student for employment in the business systems area. The contents of the courses in the information systems core curriculum at Kansas State University are presented as an example of an implemented degree program. In addition, the information systems curriculum is analyzed in terms of its differences with the Curriculum 78 computer science curriculum and of the resources required for its implementation.

This research deals with the methodology of integrating a data base management system (DBMS) into a distributed network system. The focus of concern is upon the interfaces and communications among a DBMS, an operating system with associated network interface features, and other such components at distributed nodes. The environment of a generalized data base management system is extended to a distributed generalized data base management system. The definition of this system by the authors allows the DBMS, schema, subschema, and application program to be distributed individually throughout nodes in the network and for the data base itself to be distributed.

The authors would like to thank B. R. Gaines for his careful reading of both the paper1and the thesis [1]. Dr. Gaines is correct in pointing out that for application to the grammatical inference problem We have found, as Gaines has stated, that making this correction to the program does in fact yield more accurate models. We also concur with Dr. Gaines as to the two typographical errors pointed out in test grammar 1.

Mediator: An Integrated Approach to Information Retrieval

The problem of the inference of finite-state probabilistic grammars is studied from two points of view. First, the theoretical aspects of grammatical inference are considered. Among the topics investigated are the structural and statistical properties of probabilistic grammars, methods for assigning probability measures to rewrite rules of probabilistic grammars, and statistical measures for determining how well an inferred probabilistic grammar approximates a sample set. The second concern of the study is the development and implementation of an algorithm for the inference of finite-state probabilistic grammars. This finite-state inference procedure produces a deterministic finite-state probabilistic grammar whose language approximates the sample set within a user-supplied acceptance region under the chi-square test. This procedure is enumerative. Heuristic tree-searching techniques are used to improve efficiency. The convergence of the procedure to an acceptable grammar is demonstrated and the steps of the procedure are theoretically justified. Test results of a PL/I implementation are presented. The inference procedure developed provides a means of synthesizing a probabilistic model of both physical and abstract systems from samples of their behavior.