Using rewriting techniques to produce code generators and proving them correct

AbstractA major problem in deriving a compiler from a formal definition is the production of correct and efficient object code. In this context, we propose a solution to the problem of code-generator generation.Our approach is based on a target machine description where the basic concepts used (storage classes, access modes, access classes and instructions) are hierarchically described by tree patterns. These tree patterns are terms of an abstract data type. The program intermediate representation (input to the code generator) is a term of the same abstract data type.The code generation process is based on access modes and instruction template-driven rewritings. The result is that each program instruction is reduced to a sequence of elementary machine instructions, each of them representing an instance of an instruction template.The axioms of the abstract data type are used to prove that the rewritings preserve the semantics of the intermediate representation

Model Transformations with Tom

International audienceModel Driven Engineering (MDE) advocates the use of Model Transformations (MT) in order to automate repetitive development tasks. Many different model transformation languages have been proposed with a significant tool development cost as common language elements like expressions, statements, ... must be built from scratch for each new language development tools. The Tom language is a shallow extension of Java tailored to describe and implement transformations of tree based data-structures. A key feature of Tom allows to map any Java data-structure to tree based data abstractions that can then be accessed by powerful non-linear, associative, commutative pattern matching. In this paper, we present how this approach can be used in order to develop model transformations, in particular relying on Eclipse Modeling Framework (EMF) based metamodeling facilities. This allows to provide a transformation language at a low cost both for the development of its tools and the training of its users

An illumination of the template enigma : software code generation with templates

Creating software is a process of refining a concept to an implementation. This process consists of several stages represented by documents, models and plans at several levels of abstraction. Mostly, the refinement process requires creativity of the programmers, but sometimes the task is boring and repetitive. This repetitive work is an indication that the program is not written at the most suitable level of abstraction. The level of abstraction offered by the used programming language might be too low to remove the recurring code. Code generators can be used to raise the level of abstraction of program specifications and to automate the repetitive work. This thesis focuses on code generators based on templates. Templates are one of the techniques to implement a code generator. Templates allow extension of the syntax of a programming language, enabling generative programming without modifying the underlying compiler. Four artifacts are involved in a template based generator: templates, input data, a template evaluator and output code. The templates we consider are a concrete (incomplete) representation of the output document, i.e. object code, that contains holes, i.e. the meta code. These holes are filled by the template evaluator using information from the input data to obtain the output code. Templates are widely used to generate HTML code in web applications. They can be used for generating all kinds of text, like e-mails or (source) code. In this thesis we limit the scope to the generation of source code. The central research question is how the quality of template based code generators can be improved. Quality, in general, is a broad notion and our scope is limited to the technical quality of templates and generated code. We focused on improving the maintainability of template based code generators and the correctness of the generated code. This is facilitated by the three main contributions provided by this thesis. First, the maintainability of template based code generators is increased by specifying the following requirement for our metalanguage. Our metalanguage should not be rich enough to allow programming in templates, without being too restrictive to express some code generators. We used the theory of formal languages to specify our metalanguage. Second, we ensure correctness of the templates and generated code. Third, the presented theory and techniques are validated by case studies. These case studies show application of templates in real world applications, increased maintainability and syntactical correctness of generated code. Our metalanguage should not be rich enough to allow programming in templates, without being too restrictive to express some code generators. The theory of formal languages is used to specify the requirements for our metalanguage. As we only consider to generate programming languages, it is sufficient to support the generation of languages defined by context-free grammars. This assumption is used to derive a metalanguage, that is rich enough to specify code generators that are able to instantiate all possible sentences of a context-free language. A specific case of a code generator, the unparser, is a program that can instantiate all sentences of a context-free language. We proved that an unparser can be implemented using a linear deterministic topdown tree-to-string transducer. We call this property unparser-completeness. Our metalanguage is based on a linear deterministic top-down tree-to-string transducer. Recall that the goal of specifying the requirements of the metalanguage is to increase the maintainability of template based code generators, without being too restrictive. To validate that our metalanguage is not too restrictive and leads to better maintainable templates, we compared it with four off-the-shelf text template systems by implementing an unparser. We have observed that the industrial template evaluators provide a Turing complete metalanguage, but they do not contain a block scoping mechanism for the meta-variables. This results in undesired additional boilerplate meta code in their templates. The second contribution is guaranteeing the correctness of the generated code. Correctness of the generated code can be divided in two concerns: syntactical correctness and semantical correctness. We start with syntactical correctness of the generated code. The use of text templates implies that syntactical correctness of the generated code can only be detected at compilation time. This means that errors detected during the compilation are reported on the level of the generated code. The developer is required to trace back manually the errors to their origin in the template or input data. We believe that programs manipulating source code should not consider the object code as text to detect errors as early as possible. We present an approach where the grammars of the object language and metalanguage can be combined in a modular way. Combining both grammars allows parsing both languages simultaneously. Syntax errors in both languages of the template will be found while parsing it. Moreover, only parsing a template is not sufficient to ensure that the generated code will be free of syntax errors. The template evaluator must be equipped with a mechanism to guarantee its output will be syntactically correct. We discuss our mechanism in short. A parse tree is constructed during the parsing of the template. This tree contains subtrees for the object code and subtrees for the meta code. While evaluating the template, subtrees of the meta code are substituted by object code subtrees. The template evaluator checks whether the root nonterminal of the object code subtree is equal to the root nonterminal of the meta code subtree. When both are equal, it is allowed to substitute the meta code. When the root nonterminals are distinct an accurate error message is generated. The template evaluator terminates when all meta code subtrees are substituted. The result is a parse tree of the object language and thus syntactically correct. We call this process syntax safe code generation. In order to validate that the presented techniques increase maintainability and ensure syntactical correctness, we implemented our ideas in a syntax safe template evaluator called Repleo. Repleo has been applied in four case studies. The first case is a real world situation, where it is required to generate a three tier web application from a data model. This case showed that multiple layers of an applications defined in different programming languages can be generated from a single model. The second case and third case are used to show that our metalanguage results in a better maintainable code generator. Our metalanguage forces to use a two layer code generator with separation of concerns between the two layers, where the original implementations are less modular. The last case study shows that ensuring syntactical correctness results in the prevention of cross-site scripting attacks in dynamic generation of web pages. Recall that one of our goals was ensuring the correctness of the generated code. We also showed that is possible to check static semantic properties of templates. Static semantic checks are defined for the metalanguage, for the object language and checks for the situations where the object language is dependent on the metalanguage. We implemented a prototype of a static semantic checker for PicoJava templates using attribute grammars. The use of attribute grammars leads to re-use of the original PicoJava checker. Summarizing, in this thesis we have formulated the requirements for a metalanguage and discussed how to implement a syntax safe template evaluator. This results in better maintainable template based code generators and more reliable generated code

Rascal: From Algebraic Specification to Meta-Programming

Algebraic specification has a long tradition in bridging the gap between specification and programming by making specifications executable. Building on extensive experience in designing, implementing and using specification formalisms that are based on algebraic specification and term rewriting (namely Asf and Asf+Sdf), we are now focusing on using the best concepts from algebraic specification and integrating these into a new programming language: Rascal. This language is easy to learn by non-experts but is also scalable to very large meta-programming applications. We explain the algebraic roots of Rascal and its main application areas: software analysis, software transformation, and design and implementation of domain-specific languages. Some example applications in the domain of Model-Driven Engineering (MDE) are described to illustrate this.Comment: In Proceedings AMMSE 2011, arXiv:1106.596

Survey on Instruction Selection: An Extensive and Modern Literature Review

Instruction selection is one of three optimisation problems involved in the code generator backend of a compiler. The instruction selector is responsible of transforming an input program from its target-independent representation into a target-specific form by making best use of the available machine instructions. Hence instruction selection is a crucial part of efficient code generation. Despite on-going research since the late 1960s, the last, comprehensive survey on the field was written more than 30 years ago. As new approaches and techniques have appeared since its publication, this brings forth a need for a new, up-to-date review of the current body of literature. This report addresses that need by performing an extensive review and categorisation of existing research. The report therefore supersedes and extends the previous surveys, and also attempts to identify where future research should be directed.Comment: Major changes: - Merged simulation chapter with macro expansion chapter - Addressed misunderstandings of several approaches - Completely rewrote many parts of the chapters; strengthened the discussion of many approaches - Revised the drawing of all trees and graphs to put the root at the top instead of at the bottom - Added appendix for listing the approaches in a table See doc for more inf

Deep Learning for Text Style Transfer: A Survey

Text style transfer is an important task in natural language generation, which aims to control certain attributes in the generated text, such as politeness, emotion, humor, and many others. It has a long history in the field of natural language processing, and recently has re-gained significant attention thanks to the promising performance brought by deep neural models. In this paper, we present a systematic survey of the research on neural text style transfer, spanning over 100 representative articles since the first neural text style transfer work in 2017. We discuss the task formulation, existing datasets and subtasks, evaluation, as well as the rich methodologies in the presence of parallel and non-parallel data. We also provide discussions on a variety of important topics regarding the future development of this task. Our curated paper list is at https://github.com/zhijing-jin/Text_Style_Transfer_SurveyComment: Computational Linguistics Journal 202

Stream Fusion, to Completeness

Stream processing is mainstream (again): Widely-used stream libraries are now available for virtually all modern OO and functional languages, from Java to C# to Scala to OCaml to Haskell. Yet expressivity and performance are still lacking. For instance, the popular, well-optimized Java 8 streams do not support the zip operator and are still an order of magnitude slower than hand-written loops. We present the first approach that represents the full generality of stream processing and eliminates overheads, via the use of staging. It is based on an unusually rich semantic model of stream interaction. We support any combination of zipping, nesting (or flat-mapping), sub-ranging, filtering, mapping-of finite or infinite streams. Our model captures idiosyncrasies that a programmer uses in optimizing stream pipelines, such as rate differences and the choice of a "for" vs. "while" loops. Our approach delivers hand-written-like code, but automatically. It explicitly avoids the reliance on black-box optimizers and sufficiently-smart compilers, offering highest, guaranteed and portable performance. Our approach relies on high-level concepts that are then readily mapped into an implementation. Accordingly, we have two distinct implementations: an OCaml stream library, staged via MetaOCaml, and a Scala library for the JVM, staged via LMS. In both cases, we derive libraries richer and simultaneously many tens of times faster than past work. We greatly exceed in performance the standard stream libraries available in Java, Scala and OCaml, including the well-optimized Java 8 streams