The paper proposes a comprehensive framework for representing and using non-functional requirements during the development process. The framework consists of five basic components which provide for the representation of non-functional requirements in terms of interrelated goals. Such goals can be refined through refinement methods and can be evaluated in order to determine the degree to which a set of non-functional requirements is supported by a particular design. Evidence for the power of the framework is provided through the study of accuracy and performance requirements for information systems. 1

Most common database management systems represent information in a simple record-based format. Semantic modeling provides richer data structuring capabilities for database applications. In particular, research in this area has articulated a number of constructs that provide mechanisms for representing structurally complex interrelations among data typically arising in commercial applications. In general terms, semantic modeling complements work on knowledge representation (in artificial intelligence) and on the new generation of database models based on the object-oriented paradigm of programming languages. This paper presents an in-depth discussion of semantic data modeling. It reviews the philosophical motivations of semantic models, including the need for high-level modeling abstractions and the reduction of semantic overloading of data type constructors. It then provides a tutorial introduction to the primary components of semantic models, which are the explicit representation of objects, attributes of and relationships among objects, type constructors for building complex types, ISA relationships, and derived schema components. Next, a survey of the prominent semantic models in the literature is presented. Further, since a broad area of research has developed around semantic modeling, a number of related topics based on these models are discussed, including data languages, graphical interfaces, theoretical investigations, and physical implementation strategies.

We present an exception handling facility suitable for languages used to implement database-intensive Information Systems. Such a mechanism facilitates the development and maintenance of more flexible software systems by supporting the abstraction of details concerning special or abnormal occurrences. We consider the type constraints imposed by the schema as well as various semantic integrity assertions to be normalcy conditions, and the key contribution of this work is to allow exceptions to these constraints to persist. To achieve this, we propose solutions to a range of problems, including sharing and computing with exceptional information, exception handling by users, the logic of constraints with exceptions, and implementation issues. We also illustrate the use of exception handling in dealing with null values, estimates, and measurements. Keywords and phrases: semantic integrity, violations of type constraints, exception handling, accommodating exceptions, conceptual models CR ...

We present a functional DBPL in the style of FP that facilitates the definition of precise semantics and opens up opportunities for far-reaching optimizations. The language is integrated into a functional data model, which is extended by arbitrary type hierarchies and complex objects. Thus we are able to provide the clarity of FP-like programs together with the full power of semantic data modelling. To give an impression of the special facilities for optimizing functional database languages, we point out some laws not presented before which enable access path selection already on the algebraic level of optimization. The algebraic way of access path optimization also gives new insights into optimization strategies. 1 Introduction The design of new database programming languages is still a challenging task, for on the one hand it has to meet the conceptual requirements of programming languages and database systems at the same time, and on the other hand it has to present a suita...

Secondary memory storage plays a major role in making large knowledge bases usable. This paper presents such a storage architecture for knowledge bases. In particular, the Controlled Decomposition Model, a flexible storage model which takes into account the numerous and expressive features of the knowledge representation model is defined. Second, the indexing problem for the knowledge base context is examined and the Temporal Join Index is proposed. An implementation technique for temporal indices, based on a spatial access method, is presented. Finally, an analytical and experimental performance study is conducted to account the performance limits of the proposed methods. 1 Introduction The performance of knowledge base systems slows down significantly as the size of the employed knowledge base increases, if the knowledge base is stored in primary memory. Performance deterioration is even worse when the size of the knowledge base grows much beyond the size of the available main memo...

This paper presents a highly efficient file structure for the storage of semantic databases. A low-level access language is presented, such that an arbitrary query can be performed as one or several elementary queries of the language. Most elementary queries, including such nontrivial queries as range queries and others, can be performed in just one single access to the disk.

Object --- a non-value object in the real world. An abstract object can be, for example, a tangible item (such as a person, a table, a country), or an event (such as an offering of a course by an instructor), or an idea (such as a course). Abstract objects cannot be represented directly in the computer. This term is also used for a user-transparent representation of such an object in the Semantic Binary Model. Category (also called Entity# Type# or Entity# Set# in some semantic models) --- any concept of the application's real world which is used for classification of objects. At every moment in time such a concept is descriptive of a set of objects. Unlike the mathematical notion of a set, the category itself does not depend on its objects: the objects are added and removed while the meaning of the category is preserved in time. Conversely, a set does depend on its members: the meaning of a set changes with the ebb and flow of its members. Categories are usually named by singular ...