Database Schema Evolution and Meta-Modeling
Preface
Program Committee
Table of Contents
Schema Evolution in SQL-99 and Commercial (Object-)Relational DBMS
Introduction
Schema Evolution in SQL-99
Basic Schema Elements
Creating, Altering, and Removing a Domain
Creating, Altering, and Removing a User-Defined Type
Creating, Altering, and Removing a Table
Creating and Removing a View
Creating and Removing an Assertion
Creating, Altering, and Removing a Routine
Creating and Removing a Trigger
Creating and Removing Roles
Granting and Revoking Privileges
Comparison of Schema Evolution Constructs in SQL-99 and Commercial DBMS
Domains and Assertions
User-Defined Types
Tables
Views
Procedures, Functions, and Triggers
Roles and Privileges
Constraints
Renaming Schema Elements
Some Final Remarks
References
Consistency Management in Runtime Evolving Concurrent Information Systems: A CO-NETS-Based Approach
Introduction
{sc Co-nets} with Runtime Evolution: An Overview
{sc Co-nets}: Specification of Simple Components
The Runtime Behaviour Modification in {sc Co-nets}
Consistency Management in {sc Co-nets}
Integrity Constraints as a {sc Co-nets} Class
Meta-level for a Flexible Consistency Management
More Complex Integrity Constraints
Conclusions
References
Adaptive Specifications of Technical Information Systems
Motivation
Case Study
Adaptive Specifications
Conclusions
References
Evolving the Software of a Schema Evolution System
Introduction
SERF: Providing Basic Schema Evolution Operations
Updating Existing Evolution Primitives - The Problem
Contracts: De-coupling the Constraints
An Example - Creating New Primitives with Contracts
Classification of Software Evolution Support
Related Work
Conclusion
References
Schema Evolution and Versioning: A Logical and Computational Characterisation
Introduction
The Data Model
Syntax and Semantics
Using the Data Model
Computational Properties of Reasoning
Comparison with Other Approaches
Conclusions and Future Developments
References
Temporal Branching as a Conflict Management Technique
Introduction
The Problem
Background Review
Distributed Data Management and Replication
Conflict and Conflict Resolutions
The `Log File'' Approach
Temporal Databases
Temporal Versioning
The Temporal Branching Method
Additional Dimensions: Resolutions and Versions
The Model's Components
The Model's Behavior
Version Management and Administration
Discussion and Conclusions
References
Evolving Relations
Introduction
Requirements for Evolving Relation Schemas
Conditional Schema Changes and Tuple Versioning
Evolving Relations
Conditional Schema Change
Querying Evolving Relations
Logical Query Answering
Physical Query Answering
Related Work
Conclusions and Future Research
References
QFD Matrix for Incremental Construction of a Warehouse via Data Marts
Introduction
The Matrix
Quality Function Deployment
The DWQFD Matrix
Summary
References
Change Propagation in an Axiomatic Model of Schema Evolution for Objectbase Management Systems
Introduction
Axiomatic Model Overview
Change Propagation Model
Related Work
Conclusion
References
Evolving Objects: Conceptual Description of Adaptive Information Systems
Introduction
Programs versus Information SystemsProgram-as-House' Metaphor
`Information-System-as-City' Metaphor
Adaptation in Database Applications
Example of Adaptive Applications
Evolution in SQL
Our Approach: Explicit Handling of Evolution
Objects as Building Blocks
Towards Evolving Objects
Conclusions and Future Work
References
Extending the Object Query Language for Transparent Metadata Access
Introduction
MetaOQL Syntax Extension to OQL
OQL Reviewed
Syntax of MetaOQL
Portability and Usability Improved by MetaOQL
The MetaOQL Translator
Overview of the ODMG Schema Access Class Hierarchy
System Requirements
Translation Strategy
Related Work
Conclusions and Future Work
References
A Metamodeling Approach to Evolution
Introduction
Metamodeling and Evolution
Our Approach to Metamodeling with UML
Meta-metamodel Layer
Metamodel Layer
Metamodel-Level Evolution
Classification of Evolution
Bases for Distance between Formal Metamodels
Conclusion
References
Defining Metrics for Conceptual Schema Evolution
Introduction
The Framework
Metrics for Conceptual Schema Evolution
Justified Change
Proportional Change
Proportional Rate of Change
Compatibility
Extensibility
Complexity Hampers Change
Abstraction Reduces the Need for Change
Susceptibility to Change
Preservation of Entity Identity
Change Is Local
Change Is Restricted to a Single Module
Modules Are Stable
Soundness of the Metrics
Field Study Setup
Related Work
Conclusions
References
Author Index