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.

(QVT) standard as applied to the specification of bidirectional transformations between models. We discuss what is meant by bidirectional transformations, and the model-driven development scenarios in which they are needed. We analyse the fundamental requirements on tools which support such transformations, and discuss some semantic issues which arise. We argue that a considerable amount of basic research is needed before suitable tools will be fully realisable, and suggest directions for this future research.

Translating data and data access operations between applications and databases is a longstanding data management problem. We present a novel approach to this problem, in which the relationship between the application data and the persistent storage is specified using a declarative mapping, which is compiled into bidirectional views that drive the data transformation engine. Expressing the application model as a view on the database is used to answer queries, while viewing the database in terms of the application model allows us to leverage view maintenance algorithms for update translation. This approach has been implemented in a commercial product. It enables developers to interact with a relational database via a conceptual schema and an object-oriented programming surface. We outline the implemented system and focus on the challenges of mapping compilation, which include rewriting queries under constraints and supporting non-relational constructs. Categories and Subject Descriptors: H.2 [Database Management], D.3 [Programming Languages]

was held in December 2008 near Tokyo, Japan. The meeting brought together researchers and practitioners from a variety of subdisciplines of computer science to share research efforts and help create a new community. In this report, we survey the state of the art and summarize the technical presentations delivered at the meeting. We also describe some insights gathered from our discussions and introduce a new effort to establish a benchmark for bidirectional transformations. 1

There are now a number of bidirectional programming languages, where every program can be read both as a forward transformation mapping one data structure to another and as a reverse transformation mapping an edited output back to a correspondingly edited input. Besides parsimony—the two related transformations are described by just one expression—such languages are attractive because they promise strong behavioral laws about how the two transformations fit together—e.g., their composition is the identity function. It has repeatedly been observed, however, that such laws are actually a bit too strong: in practice, we do not want them “on the nose, ” but only up to some equivalence, allowing inessential details, such as whitespace, to be modified after a round trip. Some bidirectional languages loosen their laws in this way, but only for specific, baked-in equivalences. In this work, we propose a general theory of quotient lenses— bidirectional transformations that are well behaved modulo equivalence relations controlled by the programmer. Semantically, quotient lenses are a natural refinement of lenses, which we have studied in previous work. At the level of syntax, we present a rich set of constructs for programming with canonizers and for quotienting lenses by canonizers. We track equivalences explicitly, with the type of every quotient lens specifying the equivalences it respects. We have implemented quotient lenses as a refinement of the bidirectional string processing language Boomerang. We present a number of useful primitive canonizers for strings, and give a simple extension of Boomerang’s regular-expression-based type system to statically typecheck quotient lenses. The resulting language is an expressive tool for transforming real-world, ad-hoc data formats. We demonstrate the power of our notation by developing an extended example based on the UniProt genome database format and illustrate the generality of our approach by showing how uses of quotienting in other bidirectional languages can be translated into our notation.

Security views are a flexible and effective means of controlling access to confidential information. Rather than allowing untrusted users to access the source data directly, they can instead be provided with a restricted view, from which all confidential information has been removed. The program that generates the view effectively embodies a confidentiality policy for the underlying source data. However, this approach has a significant drawback: it prevents users from updating the data in the view. To address the “view update problem ” in general, a number of bidirectional languages have been proposed. Programs in these languages—often called lenses—can be run in two directions: read from left to right, they map sources to views; read from right to left, they map updated views back to updated sources. However, existing bidirectional languages do not deal adequately with security issues. In particular, they do not provide a way to ensure the integrity of data in the source as it is manipulated by untrusted users of the view. We propose a novel framework of secure lenses that addresses these shortcomings. We first enrich the types of basic lenses with equivalence relations capturing notions of confidentiality and integrity and formulate the essential security conditions on source data as non-interference properties. We then offer a concrete instantiation of our framework in the domain of string transformations, developing concrete syntax for security-annotated regular expressions as well as a collection of bidirectional string combinators with annotated expressions as their types.

Bidirectional transformations provide a novel mechanism for synchronizing and maintaining the consistency of information between input and output. Despite many promising results on bidirectional transformations, they are limited to the context of relational or XML (tree-like) databases. In this paper, we challenge the problem of bidirectional transformations in the context of graphs, by proposing a formal definition of a well-behaved bidirectional semantics for UnCAL, a graph algebra for the known UnQL graph query language. The key to our successful formalization is full utilization of both recursive and bulk semantics of the structural recursion on graphs. We carefully refine the existing forward evaluation of structural recursion so that it can produce sufficient trace information for later backward evaluation. For the backward evaluation, we use the trace information to reflect in-place update and deletion on the view to the source, and adopt the universal resolving algorithm for inverse computation and the narrowing technique to tackle the difficult insertion problem. We prove the well-behavedness of our bidirectional evaluation. Our current implementation, being available online, confirms usefulness of our approach with nontrivial applications.

Bidirectional programming languages have been proposed as a practical approach to the view update problem. Programs in these languages, often called lenses, can be read in two ways— from left to right as functions mapping sources to views, and from right to left as functions mapping updated views back to updated sources. Lenses address the view update problem by making it possible to define a view and its associated update policy together. One issue that has not received sufficient attention in the design of bidirectional languages is alignment. In general, to correctly propagate an update to a view, a lens needs to match up the pieces of the edited view with corresponding pieces of the underlying source. Unfortunately, existing bidirectional languages are extremely limited in their treatment of alignment—they only support simple strategies that do not suffice for many examples of practical interest. In this paper, we propose a novel framework of matching lenses that extends basic lenses with new mechanisms for calculating and using alignments. We enrich the types of lenses with “chunks ” that identify the locations of data that should be re-aligned after updates, and we formulate refined behavioral laws that capture essential constraints on the handling of chunks. To demonstrate the utility of our approach, we develop a core language of matching lenses for string data, and we extend it with primitives for describing a number of useful alignment heuristics.

Traditional client-server applications relegate query and persistence operations on their data to database systems. The database system operates on data in the form of rows and tables, while the application operates on data in terms of higher-level programming language constructs (classes, structures etc.). The impedance mismatch in the data manipulation services between the application and the database tier was problematic even in traditional systems. With the advent of service-oriented architectures (SOA), application servers and multi-tier applications, the need for data access and manipulation services that are well-integrated with programming environments and can operate in any tier has increased tremendously. Microsoft’s ADO.NET Entity Framework is a platform for programming against data that raises the level of abstraction from the relational level to the conceptual (entity) level, and thereby significantly reduces the impedance mismatch for applications and data-centric services. This paper describes the key aspects of the Entity Framework, the overall system architecture, and the underlying technologies. Categories and Subject Descriptors: H.2 [Database Management], D.3 [Programming Languages]

A key challenge in supporting information interchange is not only supporting queries over integrated data, but also updates. Previous work on update exchange has enabled update propagation over schema mappings in a unidirectional way — conceptually similar to view maintenance, in that a derived instance gets updated based on changes to a source instance. In this paper, we consider how to support data and update propagation across bidirectional mappings that enable different sites to mirror each other’s data. We describe how data and update exchange can be extended to support bidirectional updates, implement an algorithm to perform side effect-free update propagation in this model, and show preliminary results suggesting our approach is feasible.