Performance Prediction Upon Toolchain Migration in Model-Based Software

Changing the development environment can have severe impacts on the system behavior such as the execution-time performance. Since it can be costly to migrate a software application, engineers would like to predict the performance parameters of the application under the new environment with as little effort as possible. In this work, we concentrate on model-driven development and provide a methodology to estimate the execution-time performance of application models under different toolchains. Our approach has low cost compared to the migration effort of an entire application. As part of the approach, we provide methods for characterizing model-driven applications, an algorithm for generating application-specific microbenchmarks, and results on using different methods for estimating the performance. In the work, we focus on SCADE as the development toolchain and use a Cruise Control and a Water Level application as case studies to confirm the technical feasibility and viability of our technique

Monitoring and debugging using an SDK for NFV-powered telecom applications

C

Cloud Services Brokerage: A Survey and Research Roadmap

A Cloud Services Brokerage (CSB) acts as an intermediary between cloud service providers (e.g., Amazon and Google) and cloud service end users, providing a number of value adding services. CSBs as a research topic are in there infancy. The goal of this paper is to provide a concise survey of existing CSB technologies in a variety of areas and highlight a roadmap, which details five future opportunities for research.Comment: Paper published in the 8th IEEE International Conference on Cloud Computing (CLOUD 2015

Smart technologies for effective reconfiguration: the FASTER approach

Current and future computing systems increasingly require that their functionality stays flexible after the system is operational, in order to cope with changing user requirements and improvements in system features, i.e. changing protocols and data-coding standards, evolving demands for support of different user applications, and newly emerging applications in communication, computing and consumer electronics. Therefore, extending the functionality and the lifetime of products requires the addition of new functionality to track and satisfy the customers needs and market and technology trends. Many contemporary products along with the software part incorporate hardware accelerators for reasons of performance and power efficiency. While adaptivity of software is straightforward, adaptation of the hardware to changing requirements constitutes a challenging problem requiring delicate solutions. The FASTER (Facilitating Analysis and Synthesis Technologies for Effective Reconfiguration) project aims at introducing a complete methodology to allow designers to easily implement a system specification on a platform which includes a general purpose processor combined with multiple accelerators running on an FPGA, taking as input a high-level description and fully exploiting, both at design time and at run time, the capabilities of partial dynamic reconfiguration. The goal is that for selected application domains, the FASTER toolchain will be able to reduce the design and verification time of complex reconfigurable systems providing additional novel verification features that are not available in existing tool flows

RELEASE: A High-level Paradigm for Reliable Large-scale Server Software

Erlang is a functional language with a much-emulated model for building reliable distributed systems. This paper outlines the RELEASE project, and describes the progress in the first six months. The project aim is to scale the Erlang’s radical concurrency-oriented programming paradigm to build reliable general-purpose software, such as server-based systems, on massively parallel machines. Currently Erlang has inherently scalable computation and reliability models, but in practice scalability is constrained by aspects of the language and virtual machine. We are working at three levels to address these challenges: evolving the Erlang virtual machine so that it can work effectively on large scale multicore systems; evolving the language to Scalable Distributed (SD) Erlang; developing a scalable Erlang infrastructure to integrate multiple, heterogeneous clusters. We are also developing state of the art tools that allow programmers to understand the behaviour of massively parallel SD Erlang programs. We will demonstrate the effectiveness of the RELEASE approach using demonstrators and two large case studies on a Blue Gene

Code Vectors: Understanding Programs Through Embedded Abstracted Symbolic Traces

With the rise of machine learning, there is a great deal of interest in treating programs as data to be fed to learning algorithms. However, programs do not start off in a form that is immediately amenable to most off-the-shelf learning techniques. Instead, it is necessary to transform the program to a suitable representation before a learning technique can be applied. In this paper, we use abstractions of traces obtained from symbolic execution of a program as a representation for learning word embeddings. We trained a variety of word embeddings under hundreds of parameterizations, and evaluated each learned embedding on a suite of different tasks. In our evaluation, we obtain 93% top-1 accuracy on a benchmark consisting of over 19,000 API-usage analogies extracted from the Linux kernel. In addition, we show that embeddings learned from (mainly) semantic abstractions provide nearly triple the accuracy of those learned from (mainly) syntactic abstractions

A Survey on Compiler Autotuning using Machine Learning

Since the mid-1990s, researchers have been trying to use machine-learning based approaches to solve a number of different compiler optimization problems. These techniques primarily enhance the quality of the obtained results and, more importantly, make it feasible to tackle two main compiler optimization problems: optimization selection (choosing which optimizations to apply) and phase-ordering (choosing the order of applying optimizations). The compiler optimization space continues to grow due to the advancement of applications, increasing number of compiler optimizations, and new target architectures. Generic optimization passes in compilers cannot fully leverage newly introduced optimizations and, therefore, cannot keep up with the pace of increasing options. This survey summarizes and classifies the recent advances in using machine learning for the compiler optimization field, particularly on the two major problems of (1) selecting the best optimizations and (2) the phase-ordering of optimizations. The survey highlights the approaches taken so far, the obtained results, the fine-grain classification among different approaches and finally, the influential papers of the field.Comment: version 5.0 (updated on September 2018)- Preprint Version For our Accepted Journal @ ACM CSUR 2018 (42 pages) - This survey will be updated quarterly here (Send me your new published papers to be added in the subsequent version) History: Received November 2016; Revised August 2017; Revised February 2018; Accepted March 2018

Detection of microservice smells through static analysis

A arquitetura de microsserviços é um modelo arquitetural promissor na área de software, atraindo desenvolvedores e empresas para os seus princípios convincentes. As suas vantagens residem no potencial para melhorar a escalabilidade, a flexibilidade e a agilidade, alinhando se com as exigências em constante evolução da era digital. No entanto, navegar entre as complexidades dos microsserviços pode ser uma tarefa desafiante, especialmente à medida que este campo continua a evoluir. Um dos principais desafios advém da complexidade inerente aos microsserviços, em que o seu grande número e interdependências podem introduzir novas camadas de complexidade. Além disso, a rápida expansão dos microsserviços, juntamente com a necessidade de aproveitar as suas vantagens de forma eficaz, exige uma compreensão mais profunda das potenciais ameaças e problemas que podem surgir. Para tirar verdadeiramente partido das vantagens dos microsserviços, é essencial enfrentar estes desafios e garantir que o desenvolvimento e a adoção de microsserviços sejam bem-sucedidos. O presente documento pretende explorar a área dos smells da arquitetura de microsserviços que desempenham um papel tão importante na dívida técnica dirigida à área dos microsserviços. Embarca numa exploração de investigação abrangente, explorando o domínio dos smells de microsserviços. Esta investigação serve como base para melhorar um catálogo de smells de microsserviços. Esta investigação abrangente obtém dados de duas fontes primárias: systematic mapping study e um questionário a profissionais da área. Este último envolveu 31 profissionais experientes com uma experiência substancial no domínio dos microsserviços. Além disso, são descritos o desenvolvimento e o aperfeiçoamento de uma ferramenta especificamente concebida para identificar e resolver problemas relacionados com os microsserviços. Esta ferramenta destina-se a melhorar o desempenho dos programadores durante o desenvolvimento e a implementação da arquitetura de microsserviços. Por último, o documento inclui uma avaliação do desempenho da ferramenta. Trata-se de uma análise comparativa efetuada antes e depois das melhorias introduzidas na ferramenta. A eficácia da ferramenta será avaliada utilizando o mesmo benchmarking de microsserviços utilizado anteriormente, para além de outro benchmarking para garantir uma avaliação abrangente.The microservices architecture stands as a beacon of promise in the software landscape, drawing developers and companies towards its compelling principles. Its appeal lies in the potential for improved scalability, flexibility, and agility, aligning with the ever-evolving demands of the digital age. However, navigating the intricacies of microservices can be a challenging task, especially as this field continues to evolve. A key challenge arises from the inherent complexity of microservices, where their sheer number and interdependencies can introduce new layers of intricacy. Furthermore, the rapid expansion of microservices, coupled with the need to harness their advantages effectively, demands a deeper understanding of the potential pitfalls and issues that may emerge. To truly unlock the benefits of microservices, it is essential to address these challenges head-on and ensure a successful journey in the world of microservices development and adoption. The present document intends to explore the area of microservice architecture smells that play such an important role in the technical debt directed to the area of microservices. It embarks on a comprehensive research exploration, delving into the realm of microservice smells. This research serves as the cornerstone for enhancing a microservice smell catalogue. This comprehensive research draws data from two primary sources: a systematic mapping research and an industry survey. The latter involves 31 seasoned professionals with substantial experience in the field of microservices. Moreover, the development and enhancement of a tool specifically designed to identify and address issues related to microservices is described. This tool is aimed at improving developers' performance throughout the development and implementation of microservices architecture. Finally, the document includes an evaluation of the tool's performance. This involves a comparative analysis conducted before and after the tool's enhancements. The tool's effectiveness will be assessed using the same microservice benchmarking as previously employed, in addition to another benchmark to ensure a comprehensive evaluation