Schema Evolution publication categorizer

Context
UML and XML are two of the most commonly used languages in software engineering processes. One of the most critical of these processes is that of model evolution and maintenance. More specifically, when an XML schema is modified, the changes should be propagated to the corresponding XML documents, which must conform with the new, modified schema.
Objective

Nowadays, one of the most important problems of software engineering continues to be the maintenance of both databases and applications. It is clear that any method that can reduce the impact that database modifications produce on application programs is valuable for software engineering processes. We have proposed such a method, by means of a database evolution architecture (MeDEA) that makes use of database views. By using views, changes in the structure of the database schema can be delayed until absolutely necessary. However, some conditions oblige modifications to be made.

Among other issues, database evolution includes the necessity of propagating the changes inside and between abstraction levels. There exist several mechanisms in order to carry out propagations from one level to another, that are distinguished on the basis of when and how the changes are performed. The strict mechanism, which implies the immediate realization of modifications, is a time–consuming process. In this paper we propose a solution that is closer to the lazy and logical mechanisms, in which changes are delayed or not finally realized, respectively.

One of the most important challenges that software engineers (designers, developers) still have to face in their everyday work is the evolution of working database systems. As a step for the solution of this problem in this paper we propose MeDEA, which stands for Metamodel-based Database Evolution Architecture. MeDEA is a generic evolution architecture that allows us to maintain the traceability between the different artifacts involved in any database development process. MeDEA is generic in the sense that it is independent of the particular modeling techniques being used.

Abstract. One of the most severe problems related to database evolution
is how to reflect in the data level the changes that have occurred
in the conceptual schema of a database. This is specially relevant when
evolution operations affect ISA relationships. In this paper we present
our view of the evolution of ISA relationships, focusing on the artifacts
that generate the sentences for changing the data in a consistent way.

Many engineering approaches exist that are widely accepted as `good design practices' for their ability to deliver high-quality conceptual schemas. Such schemas are supposed to be stable enough for subsequent system exploitation, and flexible enough to accommodate future changes. This paper presents a comparative review of a dozen current engineering approaches as to which mechanisms they employ to enhance flexibility of the CS. No single best strategy emerges from the analysis. It is found that most engineering approaches employ only a limited number of mechanisms to enhance flexibility.

An approach for evolutionary database design is presented which tries to remedy some of the shortcomings of previous design methods. The approach distinguishes clearly between a conceptual and a logical database design. A conceptual schema models the relevant aspects of reality. A logical schema describes the structure of the database as generic tables, and it reflects the design decisions taken to map the objects of the conceptual schema into the generic tables.

It is generally believed that a well-designed Conceptual Schema will remain stable over time. However, current literature rarely addresses how such stability should be observed and measured in the operational business environment with evolving information needs and database structures. This paper sets up a framework for stability of conceptual schemas and proceeds to develop a set of metrics from it. The metrics are based on straightforward measurements of conceptual features.

Recently there has been increasing interest in both the problems and the potential of
accommodating evolving schema in databases, especially in systems which necessitate a
high volume of structural changes or where structural change is difficult. This paper
presents a taxonomy of changes applicable to the Entity-Relationship Model together with
their effects on the underlying relational model expressed in terms of a second taxonomy
relevant to the relational model.