No description available.

Computational reflection is a fundamental mechanism in object oriented languages. Reflection has proved useful in many contexts, such as in the design of development environments, language extension, and the dynamic, unanticipated adaptation of running systems We identify three problems with the current approach to reflection in object oriented languages: partial behavioral reflection needs to be anticipated, structural reflection is limited to the granularity of a method, and behavioral reflection cannot be applied to the whole system. To address these problems, we extend structural reflection to cover sub-method elements and present how sub-method structural reflection supports unanticipated partial behavioral reflection. We add the concept of context to represent meta-level execution and show how this allows behavioral reflection to be applied even to system classes. We describe an implementation in Smalltalk. Benchmarks validate the practicability of our approach. In addition, we present an experimental evaluation in which we show how the system is used for dynamic analysis. We realize dynamic feature analysis by annotating the sub-method structure of the system directly to denote features instead of recording full execution traces.

This dissertation provides the motivation for and evidence in favour of an approach to language extension via dynamic loading of plug-ins. There is a growing realisation that language features are often a superior choice to software libraries for implementing applications. Among the benefits are increased usability, safety and efficiency. Unfortunately, designing and implementing new languages is difficult and time consuming. Thus, reuse of language infrastructure is an attractive implementation avenue. The central question then becomes, what is the best method to extend languages? Much research has focussed on methods of extension based on using features of the language itself such as macros or reflection. This dissertation focuses on a complementary solution: plug-in compilers. In this approach languages are extended at run-time via dynamic extensions to compilers, called plug-ins. Plug-ins can be used to extend the expressiveness, safety and efficiency of languages. However, a plug-in compiler provides other benefits. Plug-in compilers encourage modularity, lower the barrier of entry to development, and facilitate the distribution and use of experimental language extensions. This dissertation describes how plug-in support is added, to both the front and back-end of a compiler, and demonstrates their application through a pair of case studies.

Vykstant nuolatiniam programų sistemų atnaujinimui, nuolatos reikia prižiūrėti, kad jos būtų kokybiškai projektuojamos ir programuojamos. Tačiau neišvengiamai atsiranda nekokybiško išeities teksto, arba atsiranda projektavimo trūkumų. Todėl yra svarbu mokėti ieškoti tokias problemas, ir jas ištaisyti. Šio darbo tikslas yra sukurti automatinio – universalaus įrankio modelį, kuris savarankiškai aptiktų pertvarkas, bei būtų nepriklausomas nuo konkrečios programavimo kalbos. Šiam tikslui pasiekti yra nagrinėjami mokslininkų siūlomi automatiškai aptinkantys pertvarkas metodai. Taip pat yra nagrinėjamos tokio įrankio realizavimo galimybės, pateikti realizaciniai sprendimai ir pavyzdžiai. Taip pat tikslas yra sukurti praktiškai naudingas automatines pertvarkas, kurios būtų realizuotos pasiūlytu įrankiu, ir pademonstruotas jų veikimas. Šis įrankis naudoja loginį programavimą, kurio faktais yra aprašomos pertvarkomos programos, o taisyklėmis – pačios pertvarkų programos. Sėkmingai sukurti automatiniai pertvarkų radimo pavyzdžiai, leidžia daryti išvadą, kad šiame darbe rastas būdas automatiškai aptikti nekokybišką išeities tekstą, bei realizuoti tokias pertvarkas nepriklausomai nuo programavimo kalbos. / In the continual evolution of software systems, should be continuous to ensure that they are high quality designed and programmed. But inevitably the defective code, that call “bad small” or the design deficiencies. It is therefore important to be able to find such problems, and to correct them. The aim of this thesis is to create automatic - universal refactoring tool, which is detected in self-refactoring, and is independent of specific programming languages. To achieve this objective are scientists considered the proposed automatic detection of refactoring methods. It is also considered the possibility of the realization of such a tool, to provide examples and realizable solutions. It also aims to create a practical benefit of the automatic adjustments to the proposed tool is to be realized, and a demonstration of their operation. This tool uses a logic programming, which is a factual description of the conversion, and the rules - the refactoring of the program. The successful creation of automatic detection for refactoring, it can be concluded that this work is found way to automatically detect poor quality of source code, and the realization of the restructuring, regardless of programming language.

Abstraction mechanisms in programming languages aim to allow orthogonal pieces of functionality to be developed separately; complex software can then be constructed through the composition of these pieces. The effectiveness of such mechanisms lies in their support for modularity and reusability: The behavior of a piece of code should be reasoned about modularly---independently of the specific compositions it may participate in; the computation of a piece of code should allow specialization, so that it is reusable for different compositions. This dissertation introduces structural abstraction: a mechanism that advances the state of the art by allowing the writing of highly reusable code---code whose structure can be specialized per composition, while maintaining a high level of modularity. Structural abstraction provides a disciplined way for code to inspect the structure of its clients in composition, and declare its own structure accordingly. The hallmark feature of structural abstraction is that, despite its emphasis on greater reusability, it still allows modular type checking: A piece of structurally abstract code can be type-checked independently of its uses in compositions---an invaluable feature for highly reusable components that will be statically composed by other programmers. This dissertation introduces two structural abstraction techniques: static type conditions, and morphing. Static type conditions allow code to be conditionally declared based on subtyping constraints. A client of a piece of code can configure a desirable set of features by composing the code with types that satisfy the appropriate subtyping conditions. Morphing allows code to be iteratively declared, by statically reflecting over the structural members of code that it would be composed with. A morphing piece of code can mimic the structure of its clients in composition, or change its shape according to its clients in a pattern-based manner. Using either static type conditions or morphing, the structure of a piece of code is not statically determined, but can be automatically specialized by clients. Static type conditions and morphing both guarantee the modular type-safety of code: regardless of specific client configurations, code is guaranteed to be well-typed.

Multi-stage programming is a valuable technique for improving the performance of computer programs through run-time optimization. Current implementations of multi-stage programming do not support run-time type introspection, which is a significant feature of modern object-oriented platforms such as Java and C#. This is unfortunate because many programs that use type introspection in these languages could be improved with multi-staging programming. The aim of this research is to investigate the interaction between multi-stage programming and object-oriented type introspection. This is done by the invention of a new programming language that is a multi-stage extension to C#. The language is capable of expressing traditional multi-stage programs as well as a new style of multi-stage programs that incorporate type introspection, most notably polytypic algorithms such as object serialization. A compiler for the language is implemented and freely available. The language is significant because it is the first object-oriented, multi-stage language; the first attempt to combine type introspection with multi-stage programming; and the first exploration of polytypic programming in a multi-stage context.

Les architectures parallèles sont aujourd'hui présentes dans tous les systèmes informatiques, allant des smartphones aux supercalculateurs en passant par les ordinateurs de bureau. Programmer efficacement ces architectures en fonction des applications requiert un effort pluridisciplinaire portant sur les langages dédiés (Domain Specific Languages - DSL), les techniques de génération de code et d'optimisation, et les algorithmes numériques propres aux applications. Dans cette thèse, nous présentons une méthode de programmation haut niveau prenant en compte les caractéristiques des architectures hétérogènes et les propriétés existantes des matrices pour produire un solveur générique d'algèbre linéaire dense. Notre modèle de programmation supporte les transferts explicites et implicites entre un processeur (CPU) et un processeur graphique qui peut être généraliste (GPU) ou intégré (IGP). Dans la mesure où les GPU sont devenus un outil important pour le calcul haute performance, il est essentiel d'intégrer leur usage dans les plateformes de calcul. Une architecture récente telle que l'IGP requiert des connaissances supplémentaires pour pouvoir être programmée efficacement. Notre méthodologie a pour but de simplifier le développement sur ces architectures parallèles en utilisant des outils de programmation haut niveau. À titre d'exemple, nous avons développé un solveur de moindres carrés en précision mixte basé sur les équations semi-normales qui n'existait pas dans les bibliothèques actuelles. Nous avons par la suite étendu nos travaux à un modèle de programmation multi-étape ("multi-stage") pour résoudre les problèmes d'interopérabilité entre les modèles de programmation CPU et GPU. Nous utilisons cette technique pour générer automatiquement du code pour accélérateur à partir d'un code effectuant des opérations point par point ou utilisant des squelettes algorithmiques. L'approche multi-étape nous assure que le typage du code généré est valide. Nous avons ensuite montré que notre méthode est applicable à d'autres architectures et algorithmes. Les routines développées ont été intégrées dans une bibliothèque de calcul appelée NT2.Enfin, nous montrons comment la programmation haut niveau peut être appliquée à des calculs groupés et des contractions de tenseurs. Tout d'abord, nous expliquons comment concevoir un modèle de container en utilisant des techniques de programmation basées sur le C++ moderne (C++-14). Ensuite, nous avons implémenté un produit de matrices optimisé pour des matrices de petites tailles en utilisant des instructions SIMD. Pour ce faire, nous avons pris en compte les multiples problèmes liés au calcul groupé ainsi que les problèmes de localité mémoire et de vectorisation. En combinant la programmation haut niveau avec des techniques avancées de programmation parallèle, nous montrons qu'il est possible d'obtenir de meilleures performances que celles des bibliothèques numériques actuelles. / Parallelism in today's computer architectures is ubiquitous whether it be in supercomputers, workstations or on portable devices such as smartphones. Exploiting efficiently these systems for a specific application requires a multidisciplinary effort that concerns Domain Specific Languages (DSL), code generation and optimization techniques and application-specific numerical algorithms. In this PhD thesis, we present a method of high level programming that takes into account the features of heterogenous architectures and the properties of matrices to build a generic dense linear algebra solver. Our programming model supports both implicit or explicit data transfers to and from General-Purpose Graphics Processing Units (GPGPU) and Integrated Graphic Processors (IGPs). As GPUs have become an asset in high performance computing, incorporating their use in general solvers is an important issue. Recent architectures such as IGPs also require further knowledge to program them efficiently. Our methodology aims at simplifying the development on parallel architectures through the use of high level programming techniques. As an example, we developed a least-squares solver based on semi-normal equations in mixed precision that cannot be found in current libraries. This solver achieves similar performance as other mixed-precision algorithms. We extend our approach to a new multistage programming model that alleviates the interoperability problems between the CPU and GPU programming models. Our multistage approach is used to automatically generate GPU code for CPU-based element-wise expressions and parallel skeletons while allowing for type-safe program generation. We illustrate that this work can be applied to recent architectures and algorithms. The resulting code has been incorporated into a C++ library called NT2. Finally, we investigate how to apply high level programming techniques to batched computations and tensor contractions. We start by explaining how to design a simple data container using modern C++14 programming techniques. Then, we study the issues around batched computations, memory locality and code vectorization to implement a highly optimized matrix-matrix product for small sizes using SIMD instructions. By combining a high level programming approach and advanced parallel programming techniques, we show that we can outperform state of the art numerical libraries.

Cyber-physical systems are dynamic physical systems that are controlled by computers for their safe and sound operations (e.g., cars, satellites, robots, elevators, and many others). Consequently, the programs running cyber-physical systems have real-time requirements, which require the programs to compute not only correctly but also timely because dynamic physical systems need to move to correct positions within certain duration to ensure safe and sound operations. To satisfy real-time requirements in better ways, many real-time languages have been proposed in the literature. Nevertheless, the general-purpose non-real-time languages C and C++ have remained the de facto languages to program cyber-physical systems, including Mars rovers and F-35 jet fighters. Given this reality, the better ways to satisfy real-time requirements have been the use of model-based tools (e.g., MATLAB/Simulink) that allow cyber-physical systems to be designed by modeling and simulating them and the resulting models to be translated automatically to C programs. Model-based tools, however, leave the resulting C programs for manual integration with other C/C++ programs, such as legacy/third-party device drivers and libraries. Since manual integration could slip in some inconsistencies, which proved fatal in the maiden flight of Ariane-5 rocket, this work shows how the standard features of C++, which support active libraries, can be used to embed a model-based real-time language, called Tice, as a C++ active library that can be used to declaratively express models of real-time systems that are processable by off-the-shelf standard C++ compilers (e.g., GCC and Clang) that automatically not only translate the models into C/C++ programs but also check both the validity of the models and the consistency of the models with other C/C++ programs. Furthermore, being compilable by off-the-shelf standard C++ compilers also sets Tice apart from other real-time languages already proposed in the literature because the other languages require either their own special compilers/interpreters or non-standard C/C++ compilers. Consequently, while Tice itself either uses no C++ features that are unsuitable for cyber-physical systems (e.g., exception) or uses some in judicious manner (e.g., template instantiations to generate programs), Tice prevents no usage that is permitted by standard C++ compilers. Beside that, as C++ active libraries are indeed ordinary C++ libraries, C++ active libraries are seamlessly composable as ordinary C++ libraries, and therefore, as models play an increasingly important role in software engineering, this work shows the potential of C++ as a platform for language-oriented programming where different languages that express different kinds of models and are embedded as C++ active libraries could be composed seamlessly.

Cette thèse vise à définir une méthodologie de mise en œuvre d’applications performantes sur les processeurs embarqués du futur. Ces architectures nécessitent notamment d’exploiter au mieux les différents niveaux de parallélisme (grain fin, gros grain) et de gérer les communications et les accès à la mémoire. Pour étudier cette méthodologie, nous avons utilisé un processeur cible représentatif de ces architectures émergentes, le processeur CELL. Le détecteurde points d’intérêt de Harris est un exemple de traitement régulier nécessitant des unités de calcul intensif. En étudiant plusieurs schémas de mise en oeuvre sur le processeur CELL, nous avons ainsi pu mettre en évidence des méthodes d’optimisation des calculs en adaptant les programmes aux unités spécifiques de traitement SIMD du processeur CELL. L’utilisation efficace de la mémoire nécessite par ailleurs, à la fois une bonne exploitation des transferts et un arrangement optimal des données en mémoire. Nous avons développé un outil d’abstraction permettant de simplifier et d’automatiser les transferts et la synchronisation, CELL MPI. Cette expertise nous a permis de développer une méthodologie permettant de simplifier la mise en oeuvre parallèle optimisée de ces algorithmes. Nous avons ainsi conçu un outil de programmation parallèle à base de squelettes algorithmiques : SKELL BE. Ce modèle de programmation propose une solution originale de génération d’applications à base de métaprogrammation. Il permet, de manière automatisée, d’obtenir de très bonnes performances et de permettre une utilisation efficace de l’architecture, comme le montre la comparaison pour un ensemble de programmes test avec plusieurs autres outils dédiés à ce processeur. / This thesis aims to define a design methodology for high performance applications on future embedded processors. These architectures require an efficient usage of their different level of parallelism (fine-grain, coarse-grain), and a good handling of the inter-processor communications and memory accesses. In order to study this methodology, we have used a target processor which represents this type of emerging architectures, the Cell BE processor.We have also chosen a low level image processing application, the Harris points of interest detector, which is representative of a typical low level image processing application that is highly parallel. We have studied several parallelisation schemes of this application and we could establish different optimisation techniques by adapting the software to the specific SIMD units of the Cell processor. We have also developped a library named CELL MPI that allows efficient communication and synchronisation over the processing elements, using a simplified and implicit programming interface. This work allowed us to develop a methodology that simplifies the design of a parallel algorithm on the Cell processor.We have designed a parallel programming tool named SKELL BE which is based on algorithmic skeletons. This programming model providesan original solution of a meta-programming based code generator. Using SKELL BE, we can obtain very high performances applications that uses the Cell architecture efficiently when compared to other tools that exist on the market.

Ce mémoire décrit mes travaux de thèse de doctorat menés au sein de l’équipe ComSee (Computers that See) rattachée à l’axe ISPR (Image, Systèmes de Perception et Robotique) de l’Institut Pascal. Celle-ci a été financée par la Région Auvergne et le Fonds Européen de Développement Régional. Les travaux présentés s’inscrivent dans le cadre d’applications de localisation pour la robotique mobile et la Réalité Augmentée. Le framework réalisé au cours de cette thèse est une approche générique pour l’implémentation d’applications de SLAM : Simultaneous Localization And Mapping (algorithme de localisation par rapport à un modèle simultanément reconstruit). L’approche intègre une multitude de contraintes dans les processus de localisation et de reconstruction. Ces contraintes proviennent de données capteurs mais également d’a priori liés au contexte applicatif. Chaque contrainte est utilisée au sein d’un même algorithme d’optimisation afin d’améliorer l’estimation du mouvement ainsi que la précision du modèle reconstruit. Trois problèmes ont été abordés au cours de ce travail. Le premier concerne l’utilisation de contraintes sur le modèle reconstruit pour l’estimation précise d’objets 3D partiellement connus et présents dans l’environnement. La seconde problématique traite de la fusion de données multi-capteurs, donc hétérogènes et asynchrones, en utilisant un unique algorithme d’optimisation. La dernière problématique concerne la génération automatique et efficace d’algorithmes d’optimisation à contraintes multiples. L’objectif est de proposer une solution temps réel 1 aux problèmes de SLAM à contraintes multiples. Une approche générique est utilisée pour concevoir le framework afin de gérer une multitude de configurations liées aux différentes contraintes des problèmes de SLAM. Un intérêt tout particulier a été porté à la faible consommation de ressources (mémoire et CPU) tout en conservant une grande portabilité. De plus, la méta-programmation est utilisée pour générer automatiquement et spécifiquement les parties les plus complexes du code en fonction du problème à résoudre. La bibliothèque d’optimisation LMA qui a été développée au cours de cette thèse est mise à disposition de la communauté en open-source. Des expérimentations sont présentées à la fois sur des données de synthèse et des données réelles. Un comparatif exhaustif met en évidence les performances de la bibliothèque LMA face aux alternatives les plus utilisées de l’état de l’art. De plus, le framework de SLAM est utilisé sur des problèmes impliquant une difficulté et une quantité de contraintes croissantes. Les applications de robotique mobile et de Réalité Augmentée mettent en évidence des performances temps réel et un niveau de précision qui croît avec le nombre de contraintes utilisées. / This report describes my thesis work conducted within the ComSee (Computers That See) team related to the ISPR axis (ImageS, Perception Systems and Robotics) of Institut Pascal. It was financed by the Auvergne Région and the European Fund of Regional Development. The thesis was motivated by localization issues related to Augmented Reality and autonomous navigation. The framework developed during this thesis is a generic approach to implement SLAM algorithms : Simultaneous Localization And Mapping. The proposed approach use multiple constraints in the localization and mapping processes. Those constraints come from sensors data and also from knowledge given by the application context. Each constraint is used into one optimization algorithm in order to improve the estimation of the motion and the accuracy of the map. Three problems have been tackled. The first deals with constraints on the map to accurately estimate the pose of 3D objects partially known in the environment. The second problem is about merging multiple heterogeneous and asynchronous data coming from different sensors using an optimization algorithm. The last problem is to write an efficient and real-time implementation of the SLAM problem using multiple constraints. A generic approach is used to design the framework and to generate different configurations, according to the constraints, of each SLAM problem. A particular interest has been put in the low computational requirement (in term of memory and CPU) while offering a high portability. Moreover, meta-programming techniques have been used to automatically and specifically generate the more complex parts of the code according to the given problem. The optimization library LMA, developed during this thesis, is made available of the community in open-source. Several experiments were done on synthesis and real data. An exhaustive benchmark shows the performances of the LMA library compared to the most used alternatives of the state of the art. Moreover, the SLAM framework is used on different problems with an increasing difficulty and amount of constraints. Augmented Reality and autonomous navigation applications show the good performances and accuracies in multiple constraints context.