Schema evolution is a problem that is faced by long-lived data. When
a schema changes, existing persistent data can become inaccessible
unless the database system provides mechanisms to access data created
with previous versions of the schema. Most existing systems that
support schema evolution focus on changes local to individual types
within the schema, thereby limiting the changes that the database
maintainer can perform. We have developed a model of type changes
involving multiple types. The model describes both type changes
and their impact on data by defining derivation rules to initialize
new data based on the existing data. The derivation rules can describe
local and nonlocal changes to types to capture the intent of a large
class of type change operations. We have built a system called Tess
(Type Evolution Software System) that uses this model to recognize
type changes by comparing schemas and then produces a transformer
that can update data in a database to correspond to a newer version
of the schema.
%0 Journal Article
%1 lerner00
%A Lerner, Barbara S.
%C New York, NY, USA
%D 2000
%I ACM Press
%J ACM Trans. Database Syst.
%K evolution schema
%N 1
%P 83--127
%R 10.1145/352958.352983
%T A model for compound type changes encountered in schema evolution
%U http://dx.doi.org/10.1145/352958.352983
%V 25
%X Schema evolution is a problem that is faced by long-lived data. When
a schema changes, existing persistent data can become inaccessible
unless the database system provides mechanisms to access data created
with previous versions of the schema. Most existing systems that
support schema evolution focus on changes local to individual types
within the schema, thereby limiting the changes that the database
maintainer can perform. We have developed a model of type changes
involving multiple types. The model describes both type changes
and their impact on data by defining derivation rules to initialize
new data based on the existing data. The derivation rules can describe
local and nonlocal changes to types to capture the intent of a large
class of type change operations. We have built a system called Tess
(Type Evolution Software System) that uses this model to recognize
type changes by comparing schemas and then produces a transformer
that can update data in a database to correspond to a newer version
of the schema.
@article{lerner00,
abstract = {Schema evolution is a problem that is faced by long-lived data. When
a schema changes, existing persistent data can become inaccessible
unless the database system provides mechanisms to access data created
with previous versions of the schema. Most existing systems that
support schema evolution focus on changes local to individual types
within the schema, thereby limiting the changes that the database
maintainer can perform. We have developed a model of type changes
involving multiple types. The model describes both type changes
and their impact on data by defining derivation rules to initialize
new data based on the existing data. The derivation rules can describe
local and nonlocal changes to types to capture the intent of a large
class of type change operations. We have built a system called Tess
(Type Evolution Software System) that uses this model to recognize
type changes by comparing schemas and then produces a transformer
that can update data in a database to correspond to a newer version
of the schema.},
added-at = {2006-09-18T06:26:07.000+0200},
address = {New York, NY, USA},
author = {Lerner, Barbara S.},
biburl = {https://www.bibsonomy.org/bibtex/2a0aaf460b312ce3c692d1d16f0a05e4d/neilernst},
citeulike-article-id = {666446},
description = {Not previously uploaded},
doi = {10.1145/352958.352983},
interhash = {b86d2b8654f2fe0a483cc339981c1d56},
intrahash = {a0aaf460b312ce3c692d1d16f0a05e4d},
issn = {0362-5915},
journal = {ACM Trans. Database Syst.},
keywords = {evolution schema},
month = {March},
number = 1,
pages = {83--127},
priority = {3},
publisher = {ACM Press},
timestamp = {2006-09-18T06:26:07.000+0200},
title = {A model for compound type changes encountered in schema evolution},
url = {http://dx.doi.org/10.1145/352958.352983},
volume = 25,
year = 2000
}