510 research outputs found
Software model refactoring based on performance analysis: better working on software or performance side?
Several approaches have been introduced in the last few years to tackle the
problem of interpreting model-based performance analysis results and
translating them into architectural feedback. Typically the interpretation can
take place by browsing either the software model or the performance model. In
this paper, we compare two approaches that we have recently introduced for this
goal: one based on the detection and solution of performance antipatterns, and
another one based on bidirectional model transformations between software and
performance models. We apply both approaches to the same example in order to
illustrate the differences in the obtained performance results. Thereafter, we
raise the level of abstraction and we discuss the pros and cons of working on
the software side and on the performance side.Comment: In Proceedings FESCA 2013, arXiv:1302.478
Approaching the Model-Driven Generation of Feedback to Remove Software Performance Flaws
Abstract—The problem of interpreting results of perfor-mance analysis and providing feedback on software models to overcome performance flaws is probably the most critical open issue in the field of software performance engineering. Automation in this step would help to introduce perfor-mance validation as an integrated activity in the software lifecycle, without dramatically affecting the daily practices of software developers. In this paper we approach the problem with model-driven techniques, on which we build a general solution. Basing on the concept of performance antipatterns, that are bad practices in software modeling leading to performance flaws, we introduce metamodels and transformations that can support the whole process of flaw detection and solution. The approach that we propose is notation-independent and can be embedded in any (existing or future) concrete modeling notation by using weaving models and automatically generated model transformations. Finally, we discuss the issues opened from this work and the future achievements that are at the hand in this domain thanks to model-driven techniques
A Bi-Level Multi-Objective Approach for Web Service Design Defects Detection
Peer Reviewedhttps://deepblue.lib.umich.edu/bitstream/2027.42/152453/1/JSS_WSBi_Level__Copy_fv.pd
Intelligent Web Services Architecture Evolution Via An Automated Learning-Based Refactoring Framework
Architecture degradation can have fundamental impact on software quality and productivity, resulting in inability to support new features, increasing technical debt and leading to significant losses. While code-level refactoring is widely-studied and well supported by tools, architecture-level refactorings, such as repackaging to group related features into one component, or retrofitting files into patterns, remain to be expensive and risky. Serval domains, such as Web services, heavily depend on complex architectures to design and implement interface-level operations, provided by several companies such as FedEx, eBay, Google, Yahoo and PayPal, to the end-users. The objectives of this work are: (1) to advance our ability to support complex architecture refactoring by explicitly defining Web service anti-patterns at various levels of abstraction, (2) to enable complex refactorings by learning from user feedback and creating reusable/personalized refactoring strategies to augment intelligent designers’ interaction that will guide low-level refactoring automation with high-level abstractions, and (3) to enable intelligent architecture evolution by detecting, quantifying, prioritizing, fixing and predicting design technical debts. We proposed various approaches and tools based on intelligent computational search techniques for (a) predicting and detecting multi-level Web services antipatterns, (b) creating an interactive refactoring framework that integrates refactoring path recommendation, design-level human abstraction, and code-level refactoring automation with user feedback using interactive mutli-objective search, and (c) automatically learning reusable and personalized refactoring strategies for Web services by abstracting recurring refactoring patterns from Web service releases. Based on empirical validations performed on both large open source and industrial services from multiple providers (eBay, Amazon, FedEx and Yahoo), we found that the proposed approaches advance our understanding of the correlation and mutual impact between service antipatterns at different levels, revealing when, where and how architecture-level anti-patterns the quality of services. The interactive refactoring framework enables, based on several controlled experiments, human-based, domain-specific abstraction and high-level design to guide automated code-level atomic refactoring steps for services decompositions. The reusable refactoring strategy packages recurring refactoring activities into automatable units, improving refactoring path recommendation and further reducing time-consuming and error-prone human intervention.Ph.D.College of Engineering & Computer ScienceUniversity of Michigan-Dearbornhttps://deepblue.lib.umich.edu/bitstream/2027.42/142810/1/Wang Final Dissertation.pdfDescription of Wang Final Dissertation.pdf : Dissertatio
Many-Objective Optimization of Non-Functional Attributes based on Refactoring of Software Models
Software quality estimation is a challenging and time-consuming activity, and
models are crucial to face the complexity of such activity on modern software
applications. In this context, software refactoring is a crucial activity
within development life-cycles where requirements and functionalities rapidly
evolve. One main challenge is that the improvement of distinctive quality
attributes may require contrasting refactoring actions on software, as for
trade-off between performance and reliability (or other non-functional
attributes). In such cases, multi-objective optimization can provide the
designer with a wider view on these trade-offs and, consequently, can lead to
identify suitable refactoring actions that take into account independent or
even competing objectives. In this paper, we present an approach that exploits
NSGA-II as the genetic algorithm to search optimal Pareto frontiers for
software refactoring while considering many objectives. We consider performance
and reliability variations of a model alternative with respect to an initial
model, the amount of performance antipatterns detected on the model
alternative, and the architectural distance, which quantifies the effort to
obtain a model alternative from the initial one. We applied our approach on two
case studies: a Train Ticket Booking Service, and CoCoME. We observed that our
approach is able to improve performance (by up to 42\%) while preserving or
even improving the reliability (by up to 32\%) of generated model alternatives.
We also observed that there exists an order of preference of refactoring
actions among model alternatives. We can state that performance antipatterns
confirmed their ability to improve performance of a subject model in the
context of many-objective optimization. In addition, the metric that we adopted
for the architectural distance seems to be suitable for estimating the
refactoring effort.Comment: Accepted for publication in Information and Software Technologies.
arXiv admin note: substantial text overlap with arXiv:2107.0612
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 princÃpios 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 dÃvida técnica dirigida à área dos
microsserviços.
Embarca numa exploração de investigação abrangente, explorando o domÃnio 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 domÃnio 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
Introducing Interactions in Multi-Objective Optimization of Software Architectures
Software architecture optimization aims to enhance non-functional attributes
like performance and reliability while meeting functional requirements.
Multi-objective optimization employs metaheuristic search techniques, such as
genetic algorithms, to explore feasible architectural changes and propose
alternatives to designers. However, the resource-intensive process may not
always align with practical constraints. This study investigates the impact of
designer interactions on multi-objective software architecture optimization.
Designers can intervene at intermediate points in the fully automated
optimization process, making choices that guide exploration towards more
desirable solutions. We compare this interactive approach with the fully
automated optimization process, which serves as the baseline. The findings
demonstrate that designer interactions lead to a more focused solution space,
resulting in improved architectural quality. By directing the search towards
regions of interest, the interaction uncovers architectures that remain
unexplored in the fully automated process
Performance assessment of an architecture with adaptative interfaces for people with special needs
People in industrial societies carry more and more portable electronic devices (e.g., smartphone or console) with some kind of wireles connectivity support. Interaction with auto-discovered target devices present in the environment (e.g., the air conditioning of a hotel) is not so easy since devices may provide inaccessible user interfaces
(e.g., in a foreign language that the user cannot
understand). Scalability for multiple concurrent users and response times are still problems in this domain. In this paper, we assess an interoperable architecture, which enables interaction between people with some kind of special need and their environment. The assessment, based on performance patterns and antipatterns, tries to detect
performance issues and also tries to enhance the architecture design for improving system performance. As a result of the assessment, the initial design changed substantially. We refactorized the design according to the Fast Path pattern and The Ramp antipattern. Moreover,
resources were correctly allocated. Finally, the required response time was fulfilled in all system scenarios. For a specific scenario, response time was reduced from 60 seconds to less than 6 seconds
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