Didier Parigot

Design, implementation and evaluation of the FNC-2 attribute grammar system

FNC-2 is a new attribute grammar processing system aiming at expressive power, efficiency, ease of use and versatility. Its development at INRIA started in 1986, and a first running prototype is available since early 1989. Its most important features are: efficient exhaustive and incremental visit-sequence-based evaluation of strongly (absolutely) non-circular AGs; extensive space optimizations; a specially-designed AG-description language, with provisions for true modularity; portability and versatility of the generated evaluators; complete environment for application development. This paper briefly describes the design and implementation of FNC-2 and its peripherals. Then preliminary experience with the system is reported.

Declarative Program Transformation: A Deforestation Case-Study

Software engineering has to reconcile modularity with efficiency. One way to grapple with this dilemma is to automatically transform a modular-specified program into an efficient-implementable one. This is the aim of deforestation transformations which get rid of intermediate data structure constructions that occur when two functions are composed. Beyond classical compile time optimization, these transformations are undeniable tools for generic programming and software component specialization.

SmartTools: A Generator of Interactive Environments Tools

SmartTools is a development environment generator that provides a structure editor and semantic tools as main features. The well-known visitor pattern technique is commonly used for designing semantic analysis, it has been automated and extended. SmartTools is easy to use thanks to its graphical user interface designed with the Java Swing APIs. It is built with an open architecture convinient for a partial or total integration of SmartTools in other environments. It makes the addition of new software components in SmartTools easy. As a result of the modular architecture, we built a distributed instance of SmartTools which required minimal effort. Being open to the XML technologies offers all the features of SmartTools to any language defined with those technologies. But most of all, with its open architecture, SmartTools takes advantage of all the developments made around those technologies, like DOM, through the XML APIs. The fast development of SmartTools (which is a young project, one year old) validates our choices of being open and generic.The main goal of this tool is to provide help and support for designing software development environments for programming languages as well as application languages defined with XML technologies.

Aspect and XML-oriented Semantic Framework Generator: SmartTools

SmartTools is a semantic framework generator, based on XML and object technologies. Thanks to a process of automatic generation from specifications, SmartTools makes it possible to quickly develop environments dedicated to domain-specific and programming languages. Some of these specifications (XML, DTD, Schemas, XSLT) are issued from the W3C which is an important source of varied emerging domain-specific languages. SmartTools uses object technologies such as visitor patterns and aspect-oriented programming. It provides code generation adapted to the usage of those technologies to support the development of semantic analyses. In this way, we obtain at minimal cost the design and implementation of a modular development platform which is open, interactive, uniform, and most important prone to evolution.

Internals and Externals of the FNC-2 Attribute Grammar System

Fnc-2 is a modern attribute grammar processing system aiming at expressive power, efficiency, ease of use and versatility. This paper provides the reader with a brief tour inside Fnc-2, presenting the most important features of its “engine”: efficient sequential exhaustive, parallel exhaustive and sequential incremental evaluation of strongly non-circular AGs. These methods are based on the visit-sequence paradigm; the first one makes use of extensive space optimizations. Then we describe the external features of the system—attribute coupled grammar view of an AG, specially-designed AG-description language, with provisions for true modularity, and complete environment—that make it really usable for developing large-scale applications. Experience with the system is briefly reported.

P2Prec: a social-based P2P recommendation system

P2Prec is a social-based P2P recommendation system for large-scale content sharing that leverages content-based and social-based recommendation. The main idea is to recommend high quality documents related to query topics and contents held by useful friends (of friends) of the users, by exploiting friendship networks. We have implemented a prototype of P2Prec using the Shared-Data Overlay Network (SON), an open source development platform for P2P networks using web services, JXTA and OSGi. In this paper, we describe the demo of P2Precs main services (installing P2Prec peers, initializing peers, gossiping topics of interest among friends, key-word querying for contents) using our prototype implemented as an application of SON.

Techniques for Improving Grammar Flow Analysis

Grammar Flow Analysis (GFA) is a computation framework that can be applied to a large number of problems expressed on context-free grammars. In this framework, as was done on programs with Data Flow Analysis, those problems are split into a general resolution procedure and a set of specific propagation functions. This paper presents a number of improvement techniques that act on the resolution procedure, and hence apply to every GFA problem: grammar partitioning, non-terminals static ordering, weak stability and semantic stability. Practical experiments using circularity tests for attribute grammars will show the benefit of these improvements. This paper is a shortened version of [JoP90].

InfraPhenoGrid: A scientific workflow infrastructure for Plant Phenomics on the Grid

Plant phenotyping consists in the observation of physical and biochemical traits of plant genotypes in response to environmental conditions. Challenges , in particular in context of climate change and food security, are numerous. High-throughput platforms have been introduced to observe the dynamic growth of a large number of plants in different environmental conditions. Instead of considering a few genotypes at a time (as it is the case when phenomic traits are measured manually), such platforms make it possible to use completely new kinds of approaches. However, the data sets produced by such widely instrumented platforms are huge, constantly augmenting and produced by increasingly complex experiments, reaching a point where distributed computation is mandatory to extract knowledge from data. In this paper, we introduce InfraPhenoGrid, the infrastructure we designed and deploy to efficiently manage data sets produced by the PhenoArch plant phenomics platform in the context of the French Phenome Project. Our solution consists in deploying scientific workflows on a Grid using a middle-ware to pilot workflow executions. Our approach is user-friendly in the sense that despite the intrinsic complexity of the infrastructure, running scientific workflows and understanding results obtained (using provenance information) is kept as simple as possible for end-users.

The OLGA Attribute Grammar Description Language: Design, Implementation and Evaluation

Olga is the input language of the FNC-2 attribute grammar processing system, currently under development at INRIA. As such, it is designed for the specification of attribute grammars and is specialized for this purpose. The features of Olga can be classified into those which make it a powerful general-purpose applicative language and those which make it a specialized AG-description language. A remarkable feature of Olga is its strong support for modularity. The paper discusses the design goals for Olga and presents the most important aspects of the language. It also includes comparisons with other existing languages, an overview of the implementation of Olga, namely the FNC-2 system, and an account of the experience gained in using Olga.

Space optimization in the FNC-2 attribute grammar system

Evaluating attribute grammars (AGs) is an extremely memory space consuming problem. Optimizing the memory space management procedures is therefore an highly rewarding challenge. We consider this problem for evaluators of the simple multi-visit class, also called l-ordered, because it is the largest possible AG class for which we can find, at construction time, a method for memory space optimization. We present a new algorithm which decides, at generation time, whether it is possible to store attribute instances into global stacks or global variables. The purpose of this approach is to reduce not only memory space, but also the number of attributes to be stored in the nodes of the tree. This method is implemented in the FNC-2 attribute grammar processing system. Preliminary experimental results demonstrate its efficiency.