Keisuke Nakano

Bidirectionalization transformation based on automatic derivation of view complement functions

Bidirectional transformation is a pair of transformations: a view function and a backward transformation. A view function maps one data structure called source onto another called view. The corresponding backward transformation reflects changes in the view to the source. Its practically useful applications include replicated data synchronization, presentation-oriented editor development, tracing software development, and view updating in the database community. However, developing a bidirectional transformation is hard, because one has to give two mappings that satisfy the bidirectional properties for system consistency. In this paper, we propose a new framework for bidirectionalization that can automatically generate a useful backward transformation from a view function while guaranteeing that the two transformations satisfy the bidirectional properties. Our framework is based on two known approaches to bidirectionalization, namely the constant complement approach from the database community and the combinator approach from the programming language community, but it has three new features: (1) unlike the constant complement approach, it can deal with transformations between algebraic data structures rather than just tables; (2) unlike the combinator approach, in which primitive bidirectional transformations have to be explicitly given, it can derive them automatically; (3) it generates a view update checker to validate updates on views, which has not been well addressed so far. The new framework has been implemented and the experimental results show that our framework has promise.

Bidirectionalizing graph transformations

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, these have been limited to the context of relational or XML (tree-like) databases. We challenge the problem of bidirectional transformations within the context of graphs, by proposing a formal definition of a well-behaved bidirectional semantics for UnCAL, i.e., a graph algebra for the known UnQL graph query language. The key to our successful formalization is full utilization of both the recursive and bulk semantics of 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. We use the trace information for backward evaluation to reflect in-place updates and deletions on the view to the source, and adopt the universal resolving algorithm for inverse computation and the narrowing technique to tackle the difficult problem with insertion. We prove our bidirectional evaluation is well-behaved. Our current implementation is available online and confirms the usefulness of our approach with nontrivial applications.

A compositional approach to bidirectional model transformation

Bidirectional model transformation plays an important role in maintaining consistency between two models, and has many potential applications in software development, including model synchronization, round-trip engineering, software evolution, multiple-view software development, and reverse engineering. However, unclear bidirectional semantics, domain-specific bidirectionalization method, and lack of systematic development framework are known problems that prevent it from being practically used. In this paper, we propose a novel compositional framework for bidirectional model transformation based on an existing graph querying language UnQL, so that one can develop various useful bidirectional model transformation by combination of a fixed number of primitive bidirectional model transformations. We have implemented a prototype system, and the experimental results show promise of the new approach.

Toward bidirectionalization of ATL with GRoundTram

ATL is a language for describing model transformations currently in uni-direction. In our previous work we have shown that transformations of graph structures given in some form can be bidirectionalized and have implemented a system called GRoundTram system for bidirectional graph transformations. We say a transformation t is bidirectionalized when we obtain a backward transformation t′ so that the pair (t, t′) of transformations satisfies certain well-behavedness properties. Bidirectional model transformation is used to reflect the changes in the target model back to the source model, and vice versa. In this paper, as a first step toward realizing practical bidirectional model transformations, we present bidirectionalization of core part of the ATL by encoding it in the UnQL language, which is used as a transformation language in the GRound-Tram system. We give the algorithm for the encoding, based on which we have implemented the system for bidirectionalizing the core ATL in OCaml language.

Deriving Event-Based Document Transformers from Tree-Based Specifications

Abstract Structured documents are usually processed by tree-based document transformers, which transform the document tree representing the structure of the input document into another tree structure. Event-based document transformers , by contrast, recognize the input as a stream of parsing events, i.e., lexical tokens, and process the events one by one in an event-driven manner. Event-based document transformers have advantages that they need less memory space and that they are more tolerant of large inputs, compared to tree-based transformers, which construct the intermediate tree representation. This paper proposes an algorithm which derives an event-based transformer from a given specification of a document transformation over a tree structure. The derivation of an event-based transformer is carried out in the framework of attribute grammars. We first obtain an attribute grammar which processes a stream of parsing events, by applying a deforestation method; We then derive an attribute evaluation scheme relevant to the event-based transformation. Using this algorithm, one can develop event-based document transformers in a more declarative style than directly programming over the stream of parsing events.

XQuery streaming by Forest Transducers

Streaming of XML transformations is a challenging task and only a few existing systems support streaming. Research approaches generally define custom fragments of XQuery and XPath that are amenable to streaming, and then design custom algorithms for each fragment. These languages have several shortcomings. Here we take a more principled approach to the problem of streaming XQuery-based transformations. We start with an elegant transducer model for which many static analysis problems are well-understood: the Macro Forest Transducer (MFT). We show that a large fragment of XQuery can be translated into MFTs - indeed, a fragment of XQuery, that can express important features that are missing from other XQuery stream engines, such as GCX: our fragment of XQuery supports XPath predicates and let-statements. We then use an existing streaming engine for MFTs and apply a well-founded set of optimizations from functional programming such as strictness analysis and deforestation. Our prototype achieves time and memory efficiency comparable to the fastest known engine for XQuery streaming, GCX. This is surprising because our engine relies on the OCaml built in garbage collector and does not use any specialized buffer management, while GCXs efficiency is due to clever and explicit buffer management.

Graph-transformation verification using monadic second-order logic

This paper presents a new approach to solving the problem of verification of graph transformation, by proposing a new static verification algorithm for the Core UnCAL, the query algebra for graph-structured databases proposed by Bunemann et al. Given a graph transformation annotated with schema information, our algorithm statically verifies that any graph satisfying the input schema is converted by the transformation to a graph satisfying the output schema. We tackle the problem by first reformulating the semantics of UnCAL into monadic second-order logic (MSO). The logic-based foundation allows to express the schema satisfaction of transformations as the validity of MSO formulas over graph structures. Then by exploiting the two established properties of UnCAL called bisimulation-genericity and compactness, we reduce the problem to the validity of MSO over trees, which has a sound and complete decision procedure. The algorithm has been efficiently implemented; all the graph transformations in this paper and the system web page can be verified within several seconds.

An Implementation Scheme for XML Transformation Languages Through Derivation of Stream Processors

We propose a new implementation scheme for XML transformation languages through derivation of stream processors. Most of XML transformation languages are implemented as tree manipulation, where input XML trees are completely stored in memory. It leads to inefficient memory usage in particular when we apply a facile transformation to large-sized inputs. In contrast, XML stream processing can minimize memory usage and execution time since it begins to output the transformation result before reading the whole input. However, it is much harder to program XML stream processors than to specify tree manipulations because stream processing frequently requires ‘stateful programming’. This paper proposes an implementation scheme for XML transformation languages, in which we can define an XML transformation as tree manipulation and also we can obtain an XML stream processor automatically. The implementation scheme employs a framework of a composition of attribute grammars.

Composing Stack-Attributed Tree Transducers

Stack-attributed tree transducers extend attributed tree transducers with a pushdown stack device for attribute values, which make them strictly more powerful. This paper presents an algorithm for the composition of stack-attributed tree transducers with attributed tree transducers. The algorithm is an extension of the existing method to compose attributed tree transducers. It leads to some natural closure properties of the corresponding classes of tree transformations.

Structural recursion for querying ordered graphs

Structural recursion, in the form of, for example, folds on lists and catamorphisms on algebraic data structures including trees, plays an important role in functional programming, by providing a systematic way for constructing and manipulating functional programs. It is, however, a challenge to define structural recursions for graph data structures, the most ubiquitous sort of data in computing. This is because unlike lists and trees, graphs are essentially not inductive and cannot be formalized as an initial algebra in general. In this paper, we borrow from the database community the idea of structural recursion on how to restrict recursions on infinite unordered regular trees so that they preserve the finiteness property and become terminating, which are desirable properties for query languages. We propose a new graph transformation language called lambdaFG for transforming and querying ordered graphs, based on the well-defined bisimulation relation on ordered graphs with special epsilon-edges. The language lambdaFG is a higher order graph transformation language that extends the simply typed lambda calculus with graph constructors and more powerful structural recursions, which is extended for transformations on the sibling dimension. It not only gives a general framework for manipulating graphs and reasoning about them, but also provides a solution to the open problem of how to define a structural recursion on ordered graphs, with the help of the bisimilarity for ordered graphs with epsilon-edges.