We propose a novel approach to the view update problem for tree-structured data: a domainspecific programming language in which all expressions denote bi-directional transformations on trees. In one direction, these transformations—dubbed lenses—map a “concrete ” tree into a simplified “abstract view”; in the other, they map a modified abstract view, together with the original concrete tree, to a correspondingly modified concrete tree. Our design emphasizes both robustness and ease of use, guaranteeing strong well-behavedness and totality properties for welltyped lenses. We identify a natural mathematical space of well-behaved bi-directional transformations over arbitrary structures, study definedness and continuity in this setting, and state a precise connection with the classical theory of “update translation under a constant complement ” from databases. We then instantiate this semantic framework in the form of a collection of lens combinators that can be assembled to describe transformations on trees. These combinators include familiar constructs from functional programming (composition, mapping, projection, conditionals, recursion) together with some novel primitives for manipulating trees (splitting, pruning, copying, merging, etc.). We illustrate the expressiveness of these combinators by developing a number of bi-directional listprocessing transformations as derived forms. An extended example shows how our combinators can be used to define a lens that translates between a native HTML representation of browser bookmarks and a generic abstract bookmark format.

Abstract. When updating a knowledge base, several problems may arise. One of the most important problems is that of integrity constraints satisfaction. The classic approach to this problem has been to develop methods for checking whether a given update violates an integrity constraint. An alternative approach consists of trying to repair integrity constraints violations by performing additional updates that maintain knowledge base consistency. Another major problem in knowledge base updating is that of view updating; which determines how an update request should be translated into an update of the underlying base facts. We propose a new method for updating knowledge bases while maintaining their consistency. Our method can be used for both integrity constraints maintenance and view updating. It can also be combined with any integrity checking method for view updating and integrity checking. The kind of updates handled by our method are: updates of base facts, view updates, updates of deductive rules, and updates of integrity constraints. Our method is based on events and transition rules, which explicitly define the insertions and deletions induced by a knowledge base update. Using these rules, an extension of the SLDNF procedure allows us to obtain all possible minimal ways of updating a knowledge base without violating any integrity constraint. Key Words. View updating, integrity checking, integrity maintenance. 1.

A closed view of a database schema is one which is totally encapsulated. Insofar as the user is concerned, the view is the database schema. The rest of the database system is not visible through the view, and is is not required for complete use of the view. Similarly, the updates which may be effected through the view have their scope limited entirely to that view. In this paper, we lay the mathematical foundations for the systematic support of such views. The proper context is shown to be that of update translation under constant meet complement, a refinement of the constant complement strategy of Bancilhon and Spyratos. The central complexity result for relational schemata is that checking the legality of updates is “infinitely ” simpler than blindly checking that the new state is legal for the view schema, and in the particular case that the base schema is constrained by functional dependencies, may always be performed in constant time, even if the view schema is not finitely axiomatizable. We further establish that, under very natural assumptions, update strategies for closed views are unique.

Abstract not found

View update is the problem of translating update requests against a view into update requests against the base data. In this paper, we present a novel approach to this problem in relational databases. Using conditional tables to represent relational views, we translate a view update problem into a disjunction of a number of constraint satisfaction problems (CSPs). Solutions to the CSPs correspond to possible translations of the view update. Semantic information to resolve ambiguity can be handled as additional constraints in the CSPs. This approach enables us to apply the rich results of the CSP research to analyze and solve an important problem in database management.

We develop a semantic foundation and a core programming language for bi-directional transformations on treestuctured data. In one direction, these transformations, called lenses, map a complex "concrete" tree into a simplified "abstract" one; in the other, they map a modified abstract tree, together with the original concrete tree, to a correspondingly modified concrete tree.

Given an intensional database (IDB) and an extension database (EDB), the view update problem translates updates on the IDB into updates on the EDB. One approach to the view update problem uses a translation langauge to specify the meaning of a view update. In this paper we prove properties of a translation language. This approach to the view update problem studies the expressive power of the translation language and the computational cost of demonstrating properties of a translation. We use an active rule based database language for specifying translations of view updates. This paper uses the containment of one datalog program (or conjunctive query) by another to demonstrate that a translation is semantically correct. We show that the complexity of correctness is lower for insertion than deletion. Finally, we discuss extensions to the translation language. 1 Introduction A deductive database consists of an intensional (IDB) and extensional database (EDB). In the case of datalog, the m...

System evolution most often implies the integration of legacy components, such as databases, with newly developed ones, leading to mixed architectures that suffer from severe heterogeneity problems. For instance, incorporating a new program in a legacy database application can create an integrity mismatch, since the database model and the program data view can be quite different (e.g. standard file model versus OO model). In addition, neither the legacy DBMS (too weak to address integrity issues correctly) nor the new program (that relies on data server responsibility) correctly cope with data integrity management. The component that can reconciliate these mismatched subsystems is the R/W wrapper, which allows any client program to read, but also to update the legacy data, while controlling the integrity constraints that are ignored by the legacy DBMS. This article describes a generic, technology-independent, R/W wrapper architecture, a methodology for specifying them in a disciplined way, and a CASE tool for generating most of the corresponding code. The key concept is that of implicit construct, which is a structure or a constraint that has not been declared in the database, but which is controlled by the legacy application code. The implicit constructs are elicited through reverse engineering techniques, and then translated into validation

One approach to the view update problem for deductive databases proves properties of translations - that is, a language specifies the meaning of an update to the intensional database (IDB) in terms of updates to the extensional database (EDB). We argue that the view update problem should be viewed as a question of the expressive power of the translation language and the computational cost of demonstrating properties of a translation. We use an active rule based database language as a means of specifying translations of updates on the IDB into updates on the EDB. This paper uses the containment of one datalog program (or conjunctive query) by another to demonstrate that a translation is semantically correct. We show that the complexity of correctness is lower for insertion than deletion. Finally, we discuss extension to the translation language. 1 Introduction A deductive database consists of an intensional (IDB) and extensional database (EDB). In the case of datalog, the meaning of a d...