Collecting Service-Based Maintainability Metrics from RESTful API Descriptions: Static Analysis and Threshold Derivation

While many maintainability metrics have been explicitly designed for service-based systems, tool-supported approaches to automatically collect these metrics are lacking. Especially in the context of microservices, decentralization and technological heterogeneity may pose challenges for static analysis. We therefore propose the modular and extensible RAMA approach (RESTful API Metric Analyzer) to calculate such metrics from machine-readable interface descriptions of RESTful services. We also provide prototypical tool support, the RAMA CLI, which currently parses the formats OpenAPI, RAML, and WADL and calculates 10 structural service-based metrics proposed in scientific literature. To make RAMA measurement results more actionable, we additionally designed a repeatable benchmark for quartile-based threshold ranges (green, yellow, orange, red). In an exemplary run, we derived thresholds for all RAMA CLI metrics from the interface descriptions of 1,737 publicly available RESTful APIs. Researchers and practitioners can use RAMA to evaluate the maintainability of RESTful services or to support the empirical evaluation of new service interface metrics.Comment: Accepted at CSE/QUDOS workshop (collocated with ECSA 2020

Exploring maintainability and performance in Ballerina Microservices

Microservices architecture currently is the industry norm for creating applications since it allows teams to focus on individual services related to specific business functionalities, reducing the overall application complexity and improving its maintainability. However, microservices architecture has liabilities regarding service integration, communication, governance, and data management. To solve these liabilities, the industry and academic community have focused on creating new frameworks and solutions. More recently, the focus changed to creating new programming languages focused on microservices. This study aims to investigate the effects of language-oriented approaches in developing microservices. The work focuses on Ballerina, a programming language created to simplify the creation and integration of microservices. From the literature’s analysis, Ballerina demonstrates the ability to be more beneficial than the most common implementations of microservices that use more common frameworks. To further investigate these statements, an experience based on the migration of existing microservices developed in Java with the use of the framework Spring Boot was conducted. This experience used a migration strategy created based on the language’s specificities. The resulting Ballerina microservice is compared with its original counterpart. The experience focused on analyzing both solutions in terms of maintainability and performance. Therefore, the Goals, Questions, Metrics (GQM) approach was used to obtain metrics for the mentioned quality attributes. From the obtained results, it was concluded that the Ballerina solution presents differences from the Spring Boot solution, being superior regarding maintainability and inferior in performance.A arquitetura baseada em microserviços atualmente é dentro da indústria considerada a norma para a criação de aplicações. A arquitetura baseada em microserviços apresenta diversas vantagens, como a possibilidade de distribuir as diferentes funcionalidades da aplicação por diversas equipas, possibilitando também o desenvolvimento dos seus serviços em linguagens de programação diferentes. Esta modularização traduz-se num acréscimo à independência das equipas, possibilitando a implementação dos seus próprios processos de trabalho como também reduz a complexidade total da aplicação, aumentando a sua manutenibilidade. Contudo, a arquitetura baseada em microserviços, dado o aumento na sua utilização, deu origem a novas questões e preocupações para as equipas de desenvolvimento e para as organizações. As equipas de desenvolvimento encontraram dificuldades na integração e comunicação dos seus serviços, principalmente quando estes eram desenvolvidos em linguagens de programação bastante divergentes. Apesar da modularidade e desacoplamento dos serviços, começou a ser detetada uma grande dependência com metodologias de implantação do código, onde o sucesso de microserviços encontrava-se fortemente dependente do uso de contentores e sistemas de orquestração. As organizações identificaram um aumento nos seus custos devido ao aumento de processos, armazenamento em servidores e de software para suporte às diversas equipas. Estas dificuldades advêm do facto de as linguagens de programação habitualmente usadas para a criação de microserviços não terem sido edificadas com o objetivo de suportar microserviços bem como não salvaguardam algumas das preocupações identificadas anteriormente. De forma a combater estas dificuldades, a indústria e a comunidade académica incidiram as suas investigações em novas frameworks e soluções. Recentemente, dado o novo foco na otimização para o "desenvolvimento", surgiram novas linguagens de programação orientadas a microserviços. Este estudo tem como objetivo investigar os efeitos da utilização de linguagens de programação orientadas a microserviços e subsequentemente a análise do seu impacto relativamente a atributos de qualidade relevantes para os mesmos. O foco deste estudo incidirá na linguagem de programação Ballerina, uma linguagem de programação criada com o intuito de facilitar a criação de serviços resilientes capazes de se integrarem e orquestrarem através de pontos de saída distribuídos. Foi realizada uma investigação à literatura existente sobre microserviços e sobre Ballerina, com especial atenção na literatura referente à utilização de Ballerina em microserviços. Esta investigação objetivou a identificação dos atributos de qualidade relevantes, de onde se precisou a manutenibilidade e a performance como sendo os atributos a avaliar. Derivada da análise da literatura, quando confrontada com implementações de linguagens de programação mais tradicionais, Ballerina demonstra a capacidade de proporcionar benefícios aquando da sua utilização em microserviços. Ballerina apresenta vantagens tais como o suporte nativo para a utilização de contentores, suporte a DevOps e funcionalidades focadas na segurança e resiliência das aplicações. De forma a aferir estas afirmações, foi efetuada uma experiência controlada baseada na migração de microserviços desenvolvidos na linguagem de programação Java com recurso à framework Spring Boot para a linguagem Ballerina. Para a realização desta experiência, primeiramente foi escolhido um projeto base do qual se realizaria a migração. O projeto a migrar teria de cumprir alguns requisitos, tais como: ser open-source, ter atividade recente e um número significativo de microserviços. Com base nestes requisitos, foi selecionado o projeto Lakeside Mutual, um projeto sobre uma companhia de seguros fictícia, desenvolvido com o propósito de demonstrar a utilização de padrões sobre APIs e design orientado ao domínio. Seguidamente, foi desenhada uma estratégia de migração com base nas especificidades da linguagem. Dada a implementação da estratégia, foi edificado um serviço em Ballerina à semelhança do original implementado em Java, mantendo todos os seus atributos e funcionalidades. As soluções foram comparadas em termos de manutenibilidade e performance, em que para tal foi utilizada a abordagem Goal, Question, Metrics (GQM) de forma a obter métricas para os atributos de qualidade previamente mencionados. Em termos de manutenibilidade, foram analisados os números de linhas de código existentes e a complexidade calculada através dos níveis de indentação dado que Ballerina ainda não suporta ferramentas como o Sonarqube. Relativamente à performance, foi desenhado e implementado um plano de testes com um número variado de utilizadores virtuais que executavam um conjunto de pedidos REST. Dos resultados obtidos, foi concluído que existem diferenças notáveis entre ambas as soluções. A solução em Ballerina apresenta melhores resultados do que a solução em Spring Boot relativamente à manutenibilidade. Contudo, relativamente à performance, a solução em Spring Boot demonstra obter melhores resultados

Analysis of Microservice Coupling Measures

Microservices architectures are composed of a collection of modular, fault-tolerant services. In recent years, the software engineering community has published research on viable, recurring, and effective architectural patterns in microservices-based architectures, as they are critical to the maintenance and scaling of microservice-based systems. As well as, ensuring low coupling and strong cohesion among the microservices that comprise the cloud-native application is a crucial property.Services that are loosely connected and highly coherent allow development teams to work in parallel, eliminating communication overhead between teams. In the first section of this thesis, we attempted to generate a dataset by starting with a selected list of microservice-based projects. The collection is made up of 20 open-source applications that all use certain microservice architecture patterns. Furthermore, the dataset includes information about the aforementioned projects’ interservice calls and dependencies. In the second section, we suggested methods for computing and visualizing the coupling be- tween microservices by expanding and adapting the notions underlying standard of structural coupling calculation. We validate these measures using a case study of 17 projects selected from the aforementioned dataset, and we propose an automated method for measuring them. The findings of this study emphasize how these metrics give practitioners with quantitative and visual views of service architecture, that can be used to design advanced measures to monitor the development of services

Dynamic Evaluation of Microservice Granularity Adaptation

Microservices have gained acceptance in software industries as an emerging architectural style for autonomic, scalable, and more reliable computing. Among the critical microservice architecture design decisions is when to adapt the granularity of a microservice architecture by merging/decomposing microservices. No existing work investigates the following question: how can we reason about the trade-off between predicted benefits and cost of pursuing microservice granularity adaptation under uncertainty? To address this question, we provide a novel formulation of the decision problem to pursue granularity adaptation as a real options problem. We propose a novel evaluation process for dynamically evaluating granularity adaptation design decisions under uncertainty. Our process is based on a novel combination of real options and the concept of Bayesian surprises. We show the benefits of our evaluation process by comparing it to four representative industrial microservice runtime monitoring tools which can be used for retrospective evaluation for granularity adaptation decisions. Our comparison shows that our process can supersede and/or complement these tools. We implement a microservice application — Filmflix — using Amazon Web Service (AWS) Lambda and use this implementation as a case study to show the unique benefit of our process compared to traditional application of real options analysis

MICRO-FRONTENDS FOR WEB CONTENT MANAGEMENT SYSTEMS

Content Management Systems are a fundamental part of the modern world wide web. They are used to create various types of web applications. With the advent of service oriented architecture (SOA), it is commonplace for content management systems to be separate from the presentation layer that eventually displays the content. However, as the complexity of the system grows the frontend may become increasingly hard to maintain and scale. This study aims to apply the micro-frontend pattern to the presentation layer of headless web content management systems in order to provide improved maintainability to the frontend. A multivocal literature review which combines academic literature with grey literature is carried out in this study. The review is to determine the implementation strategies currently being used in research and industry as well as the approach to evaluation of micro-frontend architecture. This work provides a model architecture for applying micro-frontends to general purpose content management systems using WordPress as a case study. The success of the micro-frontend implementation is measured using system stability, web performance and code complexity metrics to compare against a functionally equivalent monolithic implementation. The results of the systematic review show the growing popularity of the micro-frontend approach as well as the different tools and techniques used in implementing the architecture. Client-side rendering and unified single page applications (SPA) are the dominant rendering and composition approaches of micro-frontend used in literature. The evaluation results that micro-frontends perform favourably compared to the headless approach. Micro-frontends had a maintainability index of 75.48 compared to an index of 74.64 for the monolithic version. In all the web performance metrics considered, micro-frontends posted a superior score than the monolithic versions. Micro-frontends did show a significant increase in the complexity of individual modules compared to the equivalent modules in the monolith

Guidelines for Testing Microservice-based Applications

Há uma tendência no desenvolvimento de software de adotar uma arquitetura baseada em microserviços. Apesar de vários benefícios como maior modularização, escalabilidade e manutenibilidade, esta abordagem levanta outros desafios para a organização. Ao aplicar este padrão de arquitetura, a estratégia de teste precisa de ser ajustada. Um sistema baseado em microserviços é inerentemente distribuído e pressupõe que os vários serviços estejam em constante comunicação entre si, através de conexões de rede, para responder aos requisitos de negócio. Testar um microserviço por si só é mais fácil, pois este está naturalmente isolado do resto do sistema, mas a execução de testes de integração torna-se mais complexa. A utilização de microserviços também oferece várias opções sobre onde e o que testar. Este trabalho tem o objetivo de estudar, comparar e sistematizar soluções e abordagens atuais para o desenvolvimento de testes em sistemas baseados em microserviços e propor um conjunto de diretrizes, métodos e boas práticas universais para facilitar o seu processo de testagem, ajudando as organizações a produzir testes com qualidade, mais valiosos e com menos custos. De modo a perceber os problemas e desafios enfrentados a testar microserviços, um projeto em forma de prova de conceito (PoC) e utilizando uma arquitetura baseadas em microserviços foi planeado, desenhado e testes, relativos a alguns casos de uso foram investigados. Também foram sugeridos um conjunto de indicadores que pretendem medir a qualidade e valor da estratégia de testes. Para cada indicador foi proposto onde pode ser recolhido, um racional com a explicação do seu propósito e uma escala de medida. Este trabalho concluiu que, apesar da existência de estratégias e frameworks de testes capazes de ajudar as organizações a testar as suas aplicações corretamente, é necessária a mentalidade certa para atingir uma estratégia de testes de qualidade. Deste modo, este trabalho propõe um conjunto de recomendações e boas práticas que promovem a mentalidade correta para desenhar e implementar testes sobre todas as camadas do sistema. São também sugeridos passos a seguir para definir e decompor cenários de teste, e soluções para os vários tipos de testes estudados. Assim, este trabalho pode também ser considerado uma base de conhecimento na área de testes em microserviços e ajudar a acelerar a sua adoção.There’s a trend in software development to adopt a microservice-based architecture. Despite several benefits such as increased modularization, scalability and maintainability, this approach brings other challenges to the table. When applying this architectural pattern, the testing strategy needs to be adapted. A microservice-based application presupposes that the various services that compose the system are communication with each other, across network boundaries, to fulfil business requirements and is inherently distributed. Testing a microservice by itself is easier, as it is naturally isolated from the rest of the system, but integration testing becomes more challenging. Microservices also offer several options about where and what to test. This work focus on studying, comparing, and systemizing current solutions and approaches for testing in microservice-based systems and proposing a set of universal guidelines, methods, and best practices to facilitate microservice-based application testing, helping organizations produce more valuable and quality tests with less costs. To understand the problems and challenges presented by microservices testing, a proof-ofconcept (PoC) project, using a microservice-based architecture, was designed and tests for some use cases were explored. Furthermore, indicators to measure test quality and value were proposed, describing it source, rational and measurement scale. This works concludes that, although many testing approaches and frameworks exist that can help organizations test their applications correctly, they need to be used with the right mindset. To achieved this, this work proposes a set of guidelines and best practices that promote the right mindset for designing and implementation tests at all system layers. It also proposes a workflow for test definition and decomposition, and solutions for the various studied testing types

Käytettävyyden ja kehityksen modernisointi mikropalveluilla

Vanhat ohjelmistojärjestelmät, joilla tarkoitetaan vanhoja ja vanhentuneita ohjelmistoja joita on tehty vanhentuneilla työskentelytavoilla, ovat todellisuus jonka kanssa suurin osa ohjelmistokehitysyrityksistä joutuvat kamppailemaan. Vanhat työskentelytavat ja teknologiat aiheuttavat usein ohjelmiston kehityksen ja julkaisun hidastumista, sillä niiden jatkuvassa käytössä voi piillä yhteensopivuus, turvallisuus, skaalautuvuus sekä ekonomisia ongelmia, muiden ongelmien muassa. Ohjelmistojärjestelmien modernisointi, uudelleensuunnittelu ja refaktorointi voivat lievittää vanhoista järjestelmistä nousevia ongelmia, oli se sitten työskentelytapojen muutoksella, teknologioiden päivityksellä tai ohjelmistoalustojen vaihdolla. On olemassa monia teknologioita ja metodeja jotka voivat helpottaa ohjelmistojärjestelmien modernisointia, mukaanlukien siirto käyttämään erilaista arkkitehtuuria, uusien teknologioiden käyttöönotto ja ohjelmistokehityksen tapojen vaihto. Näillä teknologioilla ja metodeilla, ja modernisaatiolla yleensäkkin, on omat riskinsä ja haasteensa, jotka tulee ottaa huomioon onnistuneen modernisaation aikaansaamiseksi; Nämä strategiset huomiot ovat avaintekijöitä modernisaatiossa. Tämä opinnäytetyö tutkii ohjelmistojen modernisaatiota yleisellä tasolla kirjallisuusarvostelun kautta, ja käyttää tietyn yrityksen tapaustutkimuksen dataa, joka on kerätty kyselyjen ja yhtiön lokien kautta, katsoen mitä teknologioita, konsepteja ja strategioita tarvitaan onnistuneeseen modernisaatioon, ja mitä vaikutuksia modernisaatiolla on modernisoitavaan ohjelmistojärjestelmään loppukäyttäjien sekä ohjelmistokehittäjien näkökulmasta. Tämän tutkimuksen lopputulos paljastaa miksi modernisaatio on monimutkainen aihe jossa on monia haasteita, mutta joka samaan aikaan tarjoaa monia hyötyjä modernisoitavalle ohjelmistojärjestelmälle. Näitä tuloksia on parasta käyttää ohjeina siihen, mihin ongelmiin kannattaa keskittyä modernisoinnin aikana, pitäen mielessä tapaustutkimuksen rajoitetun soveltamisalan.Legacy software systems, which refers to old and likely outdated software applications and practices, are a reality that most software development companies have to contend with. Old practices and technologies are often at fault for slowing down development and deployment of software, as they can have compatibility, security, scalability and economic issues with their continued use, among other issues. Software modernization, reengineering and refactoring can alleviate the issues stemming from legacy systems, whether it be in the form of altering practices, updating technologies or changing platforms. There are many technologies and methods that can facilitate the modernization of a software system, including a move to using different architectures, specific newer technologies and changing the methods of working and developing the software system. These technologies and methods, and modernization in general, come with their own risks and challenges that must be considered for a successful modernization to take place; These strategic considerations are a key factor in modernization. This thesis will explore software modernization in general through literature reviews and as a case study for a specific company using data from surveys and the case company’s logs, with a look into the technologies, concepts and strategies required for a successful modernization, and what kinds of effects modernization can have on the software system being modernized, both from a user perspective as well as from a developer perspective. The end-result of this exploration reveals that modernization is a complex subject with many challenges, but that also offers benefits to the software system being modernized. These results are best used as a guideline on what issues should be concentrated on during modernization, with a mindful consideration for the limited scope of the case study represented within

Facilitating and Enhancing the Performance of Model Selection for Energy Time Series Forecasting in Cluster Computing Environments

Applying Machine Learning (ML) manually to a given problem setting is a tedious and time-consuming process which brings many challenges with it, especially in the context of Big Data. In such a context, gaining insightful information, finding patterns, and extracting knowledge from large datasets are quite complex tasks. Additionally, the configurations of the underlying Big Data infrastructure introduce more complexity for configuring and running ML tasks. With the growing interest in ML the last few years, particularly people without extensive ML expertise have a high demand for frameworks assisting people in applying the right ML algorithm to their problem setting. This is especially true in the field of smart energy system applications where more and more ML algorithms are used e.g. for time series forecasting. Generally, two groups of non-expert users are distinguished to perform energy time series forecasting. The first one includes the users who are familiar with statistics and ML but are not able to write the necessary programming code for training and evaluating ML models using the well-known trial-and-error approach. Such an approach is time consuming and wastes resources for constructing multiple models. The second group is even more inexperienced in programming and not knowledgeable in statistics and ML but wants to apply given ML solutions to their problem settings. The goal of this thesis is to scientifically explore, in the context of more concrete use cases in the energy domain, how such non-expert users can be optimally supported in creating and performing ML tasks in practice on cluster computing environments. To support the first group of non-expert users, an easy-to-use modular extendable microservice-based ML solution for instrumenting and evaluating ML algorithms on top of a Big Data technology stack is conceptualized and evaluated. Our proposed solution facilitates applying trial-and-error approach by hiding the low level complexities from the users and introduces the best conditions to efficiently perform ML tasks in cluster computing environments. To support the second group of non-expert users, the first solution is extended to realize meta learning approaches for automated model selection. We evaluate how meta learning technology can be efficiently applied to the problem space of data analytics for smart energy systems to assist energy system experts which are not data analytics experts in applying the right ML algorithms to their data analytics problems. To enhance the predictive performance of meta learning, an efficient characterization of energy time series datasets is required. To this end, Descriptive Statistics Time based Meta Features (DSTMF), a new kind of meta features, is designed to accurately capture the deep characteristics of energy time series datasets. We find that DSTMF outperforms the other state-of-the-art meta feature sets introduced in the literature to characterize energy time series datasets in terms of the accuracy of meta learning models and the time needed to extract them. Further enhancement in the predictive performance of the meta learning classification model is achieved by training the meta learner on new efficient meta examples. To this end, we proposed two new approaches to generate new energy time series datasets to be used as training meta examples by the meta learner depending on the type of time series dataset (i.e. generation or energy consumption time series). We find that extending the original training sets with new meta examples generated by our approaches outperformed the case in which the original is extended by new simulated energy time series datasets