Scrap your boilerplate with object algebras

htmlabstractTraversing complex Abstract Syntax Trees (ASTs) typically requires large amounts of tedious boilerplate code. For many operations most of the code simply walks the structure, and only a small portion of the code implements the functional- ity that motivated the traversal in the first place. This paper presents a type-safe Java framework called Shy that removes much of this boilerplate code. In Shy Object Algebras are used to describe complex and extensible AST structures. Using Java annotations Shy generates generic boilerplate code for various types of traversals. For a concrete traversal, users of Shy can then inherit from the generated code and over- ride only the interesting cases. Consequently, the amount of code that users need to write is significantly smaller. Moreover, traversals using the Shy framework are also much more structure shy, becoming more adaptive to future changes or extensions to the AST structure. To prove the effectiveness of the approach, we applied Shy in the implementation of a domain-specific questionnaire language. Our results show that for a large number of traversals there was a significant reduction in the amount of user-defined code

Type-safe two-level data transformation

A two-level data transformation consists of a type-level transformation of a data format coupled with value-level transformations of data instances corresponding to that format. Examples of two-level data transformations include XML schema evolution coupled with document migration, and data mappings used for interoperability and persistence. We provide a formal treatment of two-level data transformations that is type-safe in the sense that the well-formedness of the value-level transformations with respect to the type-level transformation is guarded by a strong type system. We rely on various techniques for generic functional programming to implement the formalization in Haskell. The formalization addresses various two-level transformation scenarios, covering fully automated as well as user-driven transformations, and allowing transformations that are information-preserving or not. In each case, two-level transformations are disciplined by one-step transformation rules and type-level transformations induce value-level transformations. We demonstrate an example hierarchical-relational mapping and subsequent migration of relational data induced by hierarchical format evolution.Fundação para a Ciência e a Tecnologia (FCT

Adding superimposition to a language semantics

Given the denotational semantics of a programming language, we describe a general method to extend the language in a way that it supports a form of emph{superimposition}~---~just in the sense of aspect-oriented programming. In the extended language, the programmer can superimpose additional or alternative functionality (aka advice) onto points along the execution of a program. Adding superimposition to a language semantics comes down to three steps: (i) the semantic functions are elaborated to carry advice; (ii) the semantic equations are turned into `reflective' style so that they can be altered at will; (iii) a construct for binding advice is integrated. We illustrate the approach by representing semantics definitions as interpreters in Haskell

Recovering Grammar Relationships for the Java Language Specification

Grammar convergence is a method that helps discovering relationships between different grammars of the same language or different language versions. The key element of the method is the operational, transformation-based representation of those relationships. Given input grammars for convergence, they are transformed until they are structurally equal. The transformations are composed from primitive operators; properties of these operators and the composed chains provide quantitative and qualitative insight into the relationships between the grammars at hand. We describe a refined method for grammar convergence, and we use it in a major study, where we recover the relationships between all the grammars that occur in the different versions of the Java Language Specification (JLS). The relationships are represented as grammar transformation chains that capture all accidental or intended differences between the JLS grammars. This method is mechanized and driven by nominal and structural differences between pairs of grammars that are subject to asymmetric, binary convergence steps. We present the underlying operator suite for grammar transformation in detail, and we illustrate the suite with many examples of transformations on the JLS grammars. We also describe the extraction effort, which was needed to make the JLS grammars amenable to automated processing. We include substantial metadata about the convergence process for the JLS so that the effort becomes reproducible and transparent

Semantics-directed implementation of method-call interception

We describe a form of method-call interception (MCI) that allows the programmer to superimpose extra functionality onto method calls at run-time. We provide a reference semantics and a reference implementation for corresponding language constructs. The setup applies to class-based, statically typed, compiled languages such as Java. The semantics of MCI is used to direct a language implementation with a number of valuable properties: simplicity of the implementational model and run-time adaptation capabilities and static type safety and separate compilation and reasonable performance. Our implementational development employs sourcecode instrumentation. We start from a naive implementational model, which is subsequently refined to optimise program execution. The implementation is assessed via benchmarks

Parse-tree annotations meet re-engineering concerns

We characterise a computational model for processing annotated parse trees. The model is basically rewriting-based with specific provisions for dealing with annotations along the ordinary rewrite steps. Most notably, there are progression methods, which define a default for annotating the results of rewriting. There are also access methods, which can be used in the rewrite rules in order to retrieve annotations from the input and to establish annotations in the output. Our approach extends the basic rewriting paradigm with support for the separation of concerns that involve annotations. This is motivated in the context of transformations for software re-engineering where annotations can be used to implement concerns such as layout preservation and reversible preprocessing

Scrap your boilerplate with object algebras

International audienceTraversing complex Abstract Syntax Trees (ASTs) typically requires large amounts of tedious boilerplate code. For many operations most of the code simply walks the structure, and only a small portion of the code implements the functional- ity that motivated the traversal in the first place. This paper presents a type-safe Java framework called Shy that removes much of this boilerplate code. In Shy Object Algebras are used to describe complex and extensible AST structures. Using Java annotations Shy generates generic boilerplate code for various types of traversals. For a concrete traversal, users of Shy can then inherit from the generated code and over- ride only the interesting cases. Consequently, the amount of code that users need to write is significantly smaller. Moreover, traversals using the Shy framework are also much more structure shy, becoming more adaptive to future changes or extensions to the AST structure. To prove the effectiveness of the approach, we applied Shy in the implementation of a domain-specific questionnaire language. Our results show that for a large number of traversals there was a significant reduction in the amount of user-defined code

Synthesis of Recursive ADT Transformations from Reusable Templates

Recent work has proposed a promising approach to improving scalability of program synthesis by allowing the user to supply a syntactic template that constrains the space of potential programs. Unfortunately, creating templates often requires nontrivial effort from the user, which impedes the usability of the synthesizer. We present a solution to this problem in the context of recursive transformations on algebraic data-types. Our approach relies on polymorphic synthesis constructs: a small but powerful extension to the language of syntactic templates, which makes it possible to define a program space in a concise and highly reusable manner, while at the same time retains the scalability benefits of conventional templates. This approach enables end-users to reuse predefined templates from a library for a wide variety of problems with little effort. The paper also describes a novel optimization that further improves the performance and scalability of the system. We evaluated the approach on a set of benchmarks that most notably includes desugaring functions for lambda calculus, which force the synthesizer to discover Church encodings for pairs and boolean operations

Language Support for Megamodel Renarration

Megamodels may be difficult to understand because they reside at a high level of abstraction and they are graph-like structures that do not immediately provide means of order and decomposition as needed for successive examination and comprehension. To improve megamodel comprehension, we introduce modeling features for the recreation, in fact, renarration of megamodels. Our approach relies on certain operators for extending, instantiating, and otherwise modifying megamodels. We illustrate the approach in the context of megamodeling for Object/XML mapping (also known as XML data binding)

Deriving tolerant grammars from a base-line grammar

A grammar-based approach to tool development in re- and reverse engineering promises precise structure awareness, but it is problematic in two respects. Firstly, it is a considerable up-front investment to obtain a grammar for a relevant language or cocktail of languages. Existing work on grammar recovery addresses this concern to some extent. Secondly, it is often not feasible to insist on a precise grammar, e.g., when different dialects need to be covered. This calls for tolerant grammars. In this paper, we provide a well-engineered approach to the derivation of tolerant grammars, which is based on previous work on error recovery, fuzzy parsing, and island grammars. The technology of this paper has been used in a complex Cobol restructuring project on several millions of lines of code in different Cobol dialects. Our approach is founded on an approximation relation between a tolerant grammar and a base-line grammar which serves as a point of reference. Thereby, we avoid false positives and false negatives when parsing constructs of interest in a tolerant mode. Our approach accomplishes the effective derivation of a tolerant grammar from the syntactical structure that is relevant for a certain re- or reverse engineering tool. To this end, the productions for the constructs of interest are reused from the base-line grammar together with further productions that are needed for completion