Schema versioning is one of a number of related areas dealing with the same general problem- that of using multiple heterogeneous schemata for various database related tasks. In particular, schema versioning, and its weaker companion, schema evolution, deal with the need to retain current data and software system functionality in the face of changing database structure. Schema versioning and schema evolution offer a solution to the problem by enabling intelligent handling of any temporal mismatch between data and data structure. This survey discusses the modelling, architectural and query language issues relating to the support of evolving schemata in database systems. An indication of the future directions of schema versioning research are also given.

This paper describes the basic data model of an object-oriented database and the basic architecture of the system implementing it. In particular, a secondary storage segmentation scheme and a transaction-processing scheme are discussed. The segmentation scheme allows for arbitrary clustering of objects, including duplicates. The transaction scheme allows for many different sharing protocols ranging from those that enforce serializability to those that are nonserializable and require communication with the server only on demand. The interaction of these two features is described such that segment-level transfer and object-level locking is achieved.

E is an extension of C++ designed for writing software systems to support persistent applications. Originally designed as a language for implementing database systems, E has evolved into a general persistent programming language E was the first C++ extension to support transparent persistence, the first C++ implementation to support generic classes, and remains the only C++ extension to provide general-purpose lterators, In addition to its contributions to the C + + programming domain, work on E has made several contributions to the field of persmtent languages in general, including several distinct implementations of persistence. Thm paper describes the main features of E and shows through examples how E addresses many of the problems that arise in building persistent systems.

Achieving correct changes is the dominant activity in the application software industry. Modification of database schemata is one kind of change which may have severe consequences for database applications. The paper presents a method for measuring modifications to database schemata and their consequences, by using a thesaurus tool. Measurements of the evolution of a large-scale database application currently running in several hospitals in the UK are presented and interpreted. The kind of measurements provided by this in-depth study is useful input to the design of change management tools. Keywords: Schema evolution, change statistics, change management tools. * Published in: Information and Software Technology, Vol. 35, No. 1, pp. 35-44, January 1 1 Introduction One of the most challenging problems of building and maintaining large, long-lived application systems is to cope with all the changes that inevitably will be imposed on the systems over time. Many large application systems...

Current object database management systems support user-defined conversion functions to update the database once the schema has been modified. Two main strategies are possible when implementing such database conversion functions: immediate or lazy database updates. In this paper, we concentrate our attention to the definition of implementation strategies for conversion functions implemented as lazy database updates.

this paper, we propose a sound and complete axiomatic model for DSE in OBSs. The main benefit of the model is the formalization of DSE characteristics into a welldefined set of axioms. The axioms automatically maintain complex schema relationships and properties from two input sets associated with each type in a schema. The elements of these sets can be provided by the user, schema designer, system, or a combination of sources. One set is called the essential supertypes and contains the types that must be maintained as supertypes of a type for as long as it is consistently possible. The other set is called the essential properties and contains the properties that must be maintained in the type for as long as it is consistently possible. The correct properties and relationships within the schema are automatically derived by the axiomatic model using the essential supertypes and essential properties as a basis. The derivations performed by the axiomatic model have a proven soundness, completeness, and termination. The inclusion/exclusion of axioms in the model leads to a design space that categorizes OBSs into object-based, type-based, and object-oriented systems. The last category is further refined into several distinct subcategories that vary in functionality and expressiveness. To illustrate the power and practical usefulness of the model, the DSE operations of several existing OBSs are reduced to the axiomatic model and compared within this common framework. In recent years, researchers have addressed the problem of defining DSE policies for OBSs. These studies approach the issue from the perspective of individual systems. The axiomatic model is unique in this respect in that it captures and formalizes the salient features of DSE in OBSs and can be adopted as a commo...

In this paper we discuss extensions to the conventional relational algebra to support both aspects of transaction time, evolution of a database’s contents and evolution of a database’s schema. We define a relation’s schema to be the relation’s temporal signature, a function mapping the relation’s attribute names onto their value domains, and class, indicating the extent of support for time. We also introduce commands to change a relation, now defined as a triple consisting of a sequence of classes, a sequence of signatures, and a sequence of states. A semantic type system is required to identify semantically incorrect expressions and to enforce consistency constraints among a relation’s class, signature, and state following update. We show that these extensions are applicable, without change, to historical algebras that support valid time, yielding an algebraic language for the query and update of temporal databases. The additions preserve the useful properties of the conventional algebra. A database’s schema describes the structure of the database; the contents of the database must adhere to that structure [Date 1976, Ullman 1982]. Schema evolution refers to changes to the database’s schema over time. Conventional databases allow only one schema to be in force at a time, requiring restructuring (also termed logical reorganization [Sockut & Goldberg 1979]) when the schema is modified. With the advent of databases storing past states [McKenzie 1986], it becomes desirable to accommodate multiple schemas, each in effect for an interval in the past. Schema versioning refers to retention of past schemas resulting from schema evolution. In an earlier paper [McKenzie & Snodgrass 1987A] we proposed extensions to the conventional relational algebra [Codd 1970] that model the evolution of a database’s contents. We did not, however, consider the evolution of a database’s schema. In this paper, we provide further extensions to the conventional relational algebra that model the evolution of a database’s schema. The extensions that support evolution of a database’s contents are repeated here for completeness and because the extensions supporting schema evolution are best explained in concert with those earlier extensions

. In this paper, we address the problem of supporting more flexibility on the schema of object-oriented databases. We describe a general framework based on an object-oriented data model, where three levels of objects are distinguished: data objects, schema objects, and metaschema objects. We discuss the prerequisites for applying the query and update operations of an object algebra uniformly on all three levels. As a sample application of the framework, we focus on database evolution, that is, realizing incremental changes to the database schema and their propagation to data instances. We show, how each schema update of a given taxonomy is realized by direct updating of schema objects, and how this approach can be used to build a complete tool for database evolution. 1 Introduction There is an increasing need for database evolution facilities, offering more flexibility on the logical structure of object-oriented databases (OODBs). On the one hand, schema evolution is the basic prereq...

Abstract When the schema of an object-oriented database system is modified, the database needs to be changed in such a way that the schema and the database remain consistent with each other. This paper describes the algorithm implemented in the new forthcoming release of the O2 object database for automatically bringing the database to a consistent state after a schema update has been performed. The algorithm, which uses a deferred strategy to update the database, is a revised and extended version of the screening algorithm first sketched in [7].

The object-oriented data model TM is a language that is based on the formal theory of FM, a typed language with object-oriented features such as attributes and methods in the presence of subtyping. The general (typed) set constructs of FM allow one to deal with (database) constraints in TM. The paper describes the theory of FM, and discusses the role that set expressions may play in conceptual database schemas. Special attention is paid to the treatment of constraints, and a threestep specification approach is proposed. This approach results in the formal notion of database universe stated as an FM expression.