Performance Improvements Using Dynamic Performance Stubs

This thesis proposes a new methodology to extend the software performance engineering process. Common performance measurement and tuning principles mainly target to improve the software function itself. Hereby, the application source code is studied and improved independently of the overall system performance behavior. Moreover, the optimization of the software function has to be done without an estimation of the expected optimization gain. This often leads to an under- or overoptimization, and hence, does not utilize the system sufficiently. The proposed performance improvement methodology and framework, called dynamic performance stubs, improves the before mentioned insufficiencies by evaluating the overall system performance improvement. This is achieved by simulating the performance behavior of the original software functionality depending on an adjustable optimization level prior to the real optimization. So, it enables the software performance analyst to determine the systems’ overall performance behavior considering possible outcomes of different improvement approaches. Moreover, by using the dynamic performance stubs methodology, a cost-benefit analysis of different optimizations regarding the performance behavior can be done. The approach of the dynamic performance stubs is to replace the software bottleneck by a stub. This stub combines the simulation of the software functionality with the possibility to adjust the performance behavior depending on one or more different performance aspects of the replaced software function. A general methodology for using dynamic performance stubs as well as several methodologies for simulating different performance aspects is discussed. Finally, several case studies to show the application and usability of the dynamic performance stubs approach are presented

Surveillance et analyse de machine virtuelle assistée par l'hôte

L’arrivée des extensions de processeurs Intel VMX et AMD SVM ont rendu possible la virtualisation de la plateforme x86 en exécutant des systèmes invités non modifiés. Les technologies de virtualisation telles que KVM et Xen sont devenues de plus en plus populaires et sont largement adoptées par l’industrie et les groupes de recherche pour une variété d’applications. Les systèmes virtualisés bénéficient de l’isolation virtuelle offerte par la virtualisation, ce qui donne l’illusion du contrôle absolu sur les ressources de l’hôte. Cette isolation affecte la performance de toute application s’exécutant dans un environnement de machine virtuelle, principalement en raison du surcoût induit par les interactions avec l’hyperviseur et aussi les interactions avec d’autres machines virtuelles cohabitant sur la même machine. Cependant, il est possible de bénéficier de cette fonctionnalité pour investiguer des causes profondes de dégradation de performance pendant que le système passe par des phases critiques comme le démarrage et l’arrêt, ce qui est très difficile à surveiller dans un environnement non virtualisé. L’objectif de cette étude est de fournir une infrastructure de surveillance basée sur des techniques de paravirtualisation qui facilite la collaboration entre l’hôte et les invités et permet ainsi une détection précise des temps de latence. Pour atteindre cet objectif, nous utilisons des canaux de communication, l’hypercall et la mémoire partagée, des techniques basées sur la paravirtualisation que nous avons développées dans le traceur Ftrace. Notre approche fonctionne à travers l’infrastructure de l’hyperviseur pour faciliter le partage des données des systèmes invités, sans recourir aux opérations d’E/S utilisant le réseau et le disque, car les deux ne sont pas disponibles pendant le démarrage ou l’arrêt de la VM. De plus, en utilisant ces opérations d’E/S, les machines virtuelles souffrent d’une baisse significative des performances. Enfin, nous avons développé une optimisation KVM afin de supprimer la multiplication de sortie et permettre à notre approche de surveiller efficacement les environnements imbriqués.----------ABSTRACT: The introduction of hardware-assisted virtualization capabilities support, in both Intel VMX and AMD SVM processor extensions, made x86 virtualization possible while running unmodified OS guests. Virtualization technologies such as KVM and Xen have become increasingly popular, and are widely adopted by industry and researchers for a variety of applications. Virtualized systems benefit from the virtual isolation offered by virtualization, which gives the illusion of absolute control over the host resources. This isolation impact the performance of any application running in a virtual machine environment, mostly because of the overhead induced from interactions happening with the host hypervisor and other co-located virtual machines. However, it is possible to benefit from virtualization features to find the root cause of performance problems while a system is executing in critical phases like boot-up and shutdown. During these phases, very few communication channels are available (e.g. only serial ports) and it is very difficult to monitor the execution in a non-virtualized environment. The objective of this study is to provide a paravirtualization-based monitoring infrastructure which facilitates host and guest collaboration and enables accurate latency detection. To accomplish this objective, we use hypercall and shared memory communication channels, a paravirtualization-based technique that we developed within the Ftrace tracer. Our approach relies on the hypervisor infrastructure to allow the guest trace data to be shared without relying on I/O operations from devices like the network and disk, because neither is available while a VM is booting up or shutting down. Moreover, when using I/O operations, VMs suffer from a significant performance drop. Finally, we developed a KVM optimization in order to remove exit multiplication and enable our approach to efficiently monitor nested environments

A STUDY ON VARIOUS PROGRAMMING LANGUAGES TO KEEP PACE WITH INNOVATION

A programming language is a formal computer language designed to communicate instructions to a machine, particularly a computer. Programming languages can be used to create programs to control the behaviour of a machine or to express algorithms. The earliest known programmable machine preceded the invention of the digital computer and is the automatic flute player described in the 9th century by the brothers Musa in Baghdad, "during the Islamic Golden Age". From the early 1800s, "programs" were used to direct the behavior of machines such as Jacquard looms and player pianos. Thousands of different programming languages have been created, mainly in the computer field, and many more still are being created every year. Many programming languages require computation to be specified in an imperative form (i.e., as a sequence of operations to perform) while other languages use other forms of program specification such as the declarative form (i.e. the desired result is specified, not how to achieve it). The description of a programming language is usually split into the two components of syntax (form) and semantics (meaning). Some languages are defined by a specification document (for example, the C programming language is specified by an ISO Standard) while other languages (such as Perl) have a dominant implementation that is treated as a reference. Some languages have both, with the basic language defined by a standard and extensions taken from the dominant implementation being common. An attempt is made in this paper to have a study on various programming languages

Automatic detection of safety and security vulnerabilities in open source software

Growing software quality requirements have raised the stakes on software safety and security. Building secure software focuses on techniques and methodologies of design and implementation in order to avoid exploitable vulnerabilities. Unfortunately, coding errors have become common with the inexorable growth tendency of software size and complexity. According to the US National Institute of Standards and Technology (NIST), these coding errors lead to vulnerabilities that cost the US economy $60 billion each year. Therefore, tracking security and safety errors is considered as a fundamental cornerstone to deliver software that are free from severe vulnerabilities. The main objective of this thesis is the elaboration of efficient, rigorous, and practical techniques for the safety and security evaluation of source code. To tackle safety errors related to the misuse of type and memory operations, we present a novel type and effect discipline that extends the standard C type system with safety annotations and static safety checks. We define an inter-procedural, flow-sensitive, and alias-sensitive inference algorithm that automatically propagates type annotations and applies safety checks to programs without programmers' interaction. Moreover, we present a dynamic semantics of our C core language that is compliant with the ANSI C standard. We prove the consistency of the static semantics with respect to the dynamic semantics. We show the soundness of our static analysis in detecting our targeted set of safety errors. To tackle system-specific security properties, we present a security verification framework that combines static analysis and model-checking. We base our approach on the GCC compiler and its GIMPLE representation of source code to extract model-checkable abstractions of programs. For the verification process, we use an off-the-shelf pushdown system model-checker, and turn it into a fully-fledged security verification framework. We also allow programmers to define a wide range of security properties using an automata-based specification approach. To demonstrate the efficiency and the scalability of our approach, we conduct extensive experiments and case studies on large scale open-source software to verify their compliance with a representative set of the CERT standard secure coding rules

Supporting general data structures and execution models in runtime environments

Para aprovechar las plataformas paralelas, se necesitan herramientas de programación para poder representar apropiadamente los algoritmos paralelos. Además, los entornos paralelos requieren sistemas en tiempo de ejecución que ofrezcan diferentes paradigmas de computación. Existen diferentes áreas a estudiar con el fin de construir un sistema en tiempo de ejecución completo para un entorno paralelo. Esta Tesis aborda dos problemas comunes: el soporte unificado de datos densos y dispersos, y la integración de paralelismo orientado a mapeo de datos y paralelismo orientado a flujo de datos. Esta Tesis propone una solución que desacopla la representación, partición y reparto de datos, del algoritmo y de la estrategia de diseño paralelo para integrar manejo para datos densos y dispersos. Además, se presenta un nuevo modelo de programación basado en el paradigma de flujo de datos, donde diferentes actividades pueden ser arbitrariamente enlazadas para formar redes genéricas pero estructuradas que representan el cómputo globalDepartamento de Informática (Arquitectura y Tecnología de Computadores, Ciencias de la Computación e Inteligencia Artificial, Lenguajes y Sistemas Informáticos

Intelligent Load Balancing in Cloud Computer Systems

Cloud computing is an established technology allowing users to share resources on a large scale, never before seen in IT history. A cloud system connects multiple individual servers in order to process related tasks in several environments at the same time. Clouds are typically more cost-effective than single computers of comparable computing performance. The sheer physical size of the system itself means that thousands of machines may be involved. The focus of this research was to design a strategy to dynamically allocate tasks without overloading Cloud nodes which would result in system stability being maintained at minimum cost. This research has added the following new contributions to the state of knowledge: (i) a novel taxonomy and categorisation of three classes of schedulers, namely OS-level, Cluster and Big Data, which highlight their unique evolution and underline their different objectives; (ii) an abstract model of cloud resources utilisation is specified, including multiple types of resources and consideration of task migration costs; (iii) a virtual machine live migration was experimented with in order to create a formula which estimates the network traffic generated by this process; (iv) a high-fidelity Cloud workload simulator, based on a month-long workload traces from Google's computing cells, was created; (v) two possible approaches to resource management were proposed and examined in the practical part of the manuscript: the centralised metaheuristic load balancer and the decentralised agent-based system. The project involved extensive experiments run on the University of Westminster HPC cluster, and the promising results are presented together with detailed discussions and a conclusion

Semantic discovery and reuse of business process patterns

Patterns currently play an important role in modern information systems (IS) development and their use has mainly been restricted to the design and implementation phases of the development lifecycle. Given the increasing significance of business modelling in IS development, patterns have the potential of providing a viable solution for promoting reusability of recurrent generalized models in the very early stages of development. As a statement of research-in-progress this paper focuses on business process patterns and proposes an initial methodological framework for the discovery and reuse of business process patterns within the IS development lifecycle. The framework borrows ideas from the domain engineering literature and proposes the use of semantics to drive both the discovery of patterns as well as their reuse

XX Workshop de Investigadores en Ciencias de la Computación - WICC 2018 : Libro de actas

Actas del XX Workshop de Investigadores en Ciencias de la Computación (WICC 2018), realizado en Facultad de Ciencias Exactas y Naturales y Agrimensura de la Universidad Nacional del Nordeste, los dìas 26 y 27 de abril de 2018.Red de Universidades con Carreras en Informática (RedUNCI

XX Workshop de Investigadores en Ciencias de la Computación - WICC 2018 : Libro de actas

Actas del XX Workshop de Investigadores en Ciencias de la Computación (WICC 2018), realizado en Facultad de Ciencias Exactas y Naturales y Agrimensura de la Universidad Nacional del Nordeste, los dìas 26 y 27 de abril de 2018.Red de Universidades con Carreras en Informática (RedUNCI