The growing need for computer software in different sectors of activity, (health, agriculture, industries, education, aeronautic, science and telecommunication) together with the increasing reliance of the society as a whole on information technology, is placing a heavy and fast growing demand on complex and high quality software systems. In this regard, the anticipation has been on non-functional requirements (NFRs) engineering and formal methods. Despite their common objective, these techniques have in most cases evolved separately. NFRs engineering proceeds firstly, by deriving measures to evaluate the quality of the constructed software (product-oriented approach), and secondarily by improving the engineering process (process-oriented approach). With the ability to combine the analysis of both functional and non-functional requirements, Goal-Oriented Requirements Engineering (GORE) approaches have become de facto leading requirements engineering methods. They propose through refinement/operationalisation, means to satisfy NFRs encoded in softgoals at an early phase of software development. On the other side, formal methods have kept, so far, their promise to eliminate errors in software artefacts to produce high quality software products and are therefore particularly solicited for safety and mission critical systems for which a single error may cause great loss including human life. This thesis introduces the concept of Complementary Non-functional action (CNF-action) to extend the analysis and development of NFRs beyond the traditional goals/softgoals analysis, based on refinement/operationalisation, and to propagate the influence of NFRs to other software construction phases. Mechanisms are also developed to integrate the formal technique Z/Object-Z into the standardised User Requirements Notation (URN) to formalise GRL models describing functional and non-functional requirements, to propagate CNF-actions of the formalised NFRs to UCMs maps, to facilitate URN construction process and the quality of URN models. / School of Computing / D. Phil (Computer Science)

Uma arquitetura distribuída é composta de diversos sistemas que trocam mensagens entre si. Falhas na integração destes sistemas podem ocorrer, exigindo uma investigação detalhada dos profissionais de suporte para encontrar a causa raiz do problema. O processo manual de identificação de falhas é difícil e demorado. Ganhos significativos podem ser obtidos através da automação do processo de classificação de falhas. Este trabalho tem por objetivo apresentar um método para auxílio no processo de diagnóstico de falhas, classificando automaticamente as falhas geradas em uma arquitetura orientada a serviços. Este método, denominado SOAFaultControl, se beneficia de arquiteturas distribuídas que adotam SOA e um Enterprise Service Bus (ESB). Utilizando-se de técnicas de aprendizado de máquina, foi possível estabelecer um modelo para classificação de falhas em categorias preestabelecidas. Para alcançar o objetivo deste trabalho foi necessário testar e avaliar os seguintes algoritmos de aprendizagem de máquina: Support Vector Machine, Naive Bayes e AdaBoost. Como resultado, o algoritmo Support Vector Machine obteve melhor desempenho nas métricas: acurácia, precisão, revocação e F1. / A distributed architecture is composed of many systems that exchange messages between each other. Faults in the integration of these systems may occur and they required a detailed investigation of support professionals to identifying the root cause of the problem. The manual process to identify causes of failure is difficult and time-consuming. Significant efficiency gains can be achieved by automating the faults classification process. This work presents a method to support the automated fault diagnostic process, automatically classifying faults generated in a Service Oriented Architecture (SOA). This method denominated SOAFaultControl, may be executed in a distributed architecture that adote SOA and an Enterprise Service Bus (ESB). Using machine learning techniques, was possible build a model to classify fault messages captured in a SOA environment, in pre-established classes. To achieve the objectives of this work it was necessary to test the following machine learning algorithms: Support Vector Machine, Naive Bayes, and AdaBoost. Results show that Support Vector Machine algorithm achieved better performance in the following metrics: precision, accuracy, recall, and F1.

Test Driven Development (TDD) é uma prática ágil que ganhou popularidade ao ser definida como parte fundamental na eXtreme Programming (XP). Essa prática determina que os testes devem ser escritos antes da implementação do código. TDD e seus efeitos têm sido amplamente estudados e comparados com a prática Test Last Development (TLD) em diversos trabalhos. Entretanto, poucos estudos abordam TDD no desenvolvimento de Web Services (WS), devido à complexidade em testar as dependências entre os componentes distribuídos e as particularidades da Service Oriented Architecture (SOA). Este trabalho tem por objetivo definir e validar uma abordagem para o desenvolvimento de WS baseada na prática de TDD, denominada WS-TDD. Essa abordagem guia os desenvolvedores no uso de TDD durante o desenvolvimento de WS, sugerindo ferramentas e técnicas para lidar com as dependências e as particularidades de SOA, com foco na criação dos testes unitários e integrados automatizados na linguagem Java. No intuito de definir e validar a abordagem proposta, quatro métodos de pesquisa foram executados: (i) questionário presencial; (ii) experimento; (iii) entrevista presencial com cada participante do experimento e (iv) triangulação dos resultados com as pessoas que participaram nos três métodos anteriores. De acordo com os resultados obtidos, a WS-TDD mostrou-se mais eficiente quando comparada a TLD, aumentando a qualidade interna do software e a produtividade dos desenvolvedores. No entanto, a qualidade externa do software diminuiu, apresentando um maior número de defeitos quando comparada a TLD. Por fim, é importante destacar que a abordagem proposta surge como uma alternativa simples e prática para a adoção de TDD no desenvolvimento de WS, trazendo benefícios a qualidade interna e contribuindo para aumentar a produtividade dos desenvolvedores. Porém, a qualidade externa do software diminuiu ao utilizar a WS-TDD. / Test Driven Development (TDD) is an agile practice that gained popularity when defined as a fundamental part in eXtreme Programming (XP). This practice determines that the tests should be written before implementing the code. TDD and its effects have been widely studied and compared with the Test Last Development (TLD) in several studies. However, few studies address TDD practice in the development of Web Services (WS), due to the complexity of testing the dependencies among distributed components and the specific characteristics of Service Oriented Architecture (SOA). This study aims to define and validate an approach to develop WS based on the practice of TDD, called WS-TDD. This approach guides developers to use TDD to develop WS, suggesting tools and techniques to deal with SOA particularities and dependencies, focusing on the creation of the unitary and integrated automated tests in Java. In order to define and validate the proposed approach, four research methods have been carried out: (i) questionnaire; (ii) practical experiment; (iii) personal interview with each participant in the experiment and (iv) triangulation of the results with the people who participated in the three previous methods. According to the obtained results, WS-TDD was more efficient compared to TLD, increasing internal software quality and developer productivity. However, the external software quality has decreased due to a greater number of defects compared to the TLD approach. Finally, it is important to highlight that the proposed approach is a simple and practical alternative for the adoption of TDD in the development of WS, bringing benefits to internal quality and contributing to increase the developers’ productivity. However, the external software quality has decreased when using WS-TDD.

Uma arquitetura distribuída é composta de diversos sistemas que trocam mensagens entre si. Falhas na integração destes sistemas podem ocorrer, exigindo uma investigação detalhada dos profissionais de suporte para encontrar a causa raiz do problema. O processo manual de identificação de falhas é difícil e demorado. Ganhos significativos podem ser obtidos através da automação do processo de classificação de falhas. Este trabalho tem por objetivo apresentar um método para auxílio no processo de diagnóstico de falhas, classificando automaticamente as falhas geradas em uma arquitetura orientada a serviços. Este método, denominado SOAFaultControl, se beneficia de arquiteturas distribuídas que adotam SOA e um Enterprise Service Bus (ESB). Utilizando-se de técnicas de aprendizado de máquina, foi possível estabelecer um modelo para classificação de falhas em categorias preestabelecidas. Para alcançar o objetivo deste trabalho foi necessário testar e avaliar os seguintes algoritmos de aprendizagem de máquina: Support Vector Machine, Naive Bayes e AdaBoost. Como resultado, o algoritmo Support Vector Machine obteve melhor desempenho nas métricas: acurácia, precisão, revocação e F1. / A distributed architecture is composed of many systems that exchange messages between each other. Faults in the integration of these systems may occur and they required a detailed investigation of support professionals to identifying the root cause of the problem. The manual process to identify causes of failure is difficult and time-consuming. Significant efficiency gains can be achieved by automating the faults classification process. This work presents a method to support the automated fault diagnostic process, automatically classifying faults generated in a Service Oriented Architecture (SOA). This method denominated SOAFaultControl, may be executed in a distributed architecture that adote SOA and an Enterprise Service Bus (ESB). Using machine learning techniques, was possible build a model to classify fault messages captured in a SOA environment, in pre-established classes. To achieve the objectives of this work it was necessary to test the following machine learning algorithms: Support Vector Machine, Naive Bayes, and AdaBoost. Results show that Support Vector Machine algorithm achieved better performance in the following metrics: precision, accuracy, recall, and F1.

Test Driven Development (TDD) é uma prática ágil que ganhou popularidade ao ser definida como parte fundamental na eXtreme Programming (XP). Essa prática determina que os testes devem ser escritos antes da implementação do código. TDD e seus efeitos têm sido amplamente estudados e comparados com a prática Test Last Development (TLD) em diversos trabalhos. Entretanto, poucos estudos abordam TDD no desenvolvimento de Web Services (WS), devido à complexidade em testar as dependências entre os componentes distribuídos e as particularidades da Service Oriented Architecture (SOA). Este trabalho tem por objetivo definir e validar uma abordagem para o desenvolvimento de WS baseada na prática de TDD, denominada WS-TDD. Essa abordagem guia os desenvolvedores no uso de TDD durante o desenvolvimento de WS, sugerindo ferramentas e técnicas para lidar com as dependências e as particularidades de SOA, com foco na criação dos testes unitários e integrados automatizados na linguagem Java. No intuito de definir e validar a abordagem proposta, quatro métodos de pesquisa foram executados: (i) questionário presencial; (ii) experimento; (iii) entrevista presencial com cada participante do experimento e (iv) triangulação dos resultados com as pessoas que participaram nos três métodos anteriores. De acordo com os resultados obtidos, a WS-TDD mostrou-se mais eficiente quando comparada a TLD, aumentando a qualidade interna do software e a produtividade dos desenvolvedores. No entanto, a qualidade externa do software diminuiu, apresentando um maior número de defeitos quando comparada a TLD. Por fim, é importante destacar que a abordagem proposta surge como uma alternativa simples e prática para a adoção de TDD no desenvolvimento de WS, trazendo benefícios a qualidade interna e contribuindo para aumentar a produtividade dos desenvolvedores. Porém, a qualidade externa do software diminuiu ao utilizar a WS-TDD. / Test Driven Development (TDD) is an agile practice that gained popularity when defined as a fundamental part in eXtreme Programming (XP). This practice determines that the tests should be written before implementing the code. TDD and its effects have been widely studied and compared with the Test Last Development (TLD) in several studies. However, few studies address TDD practice in the development of Web Services (WS), due to the complexity of testing the dependencies among distributed components and the specific characteristics of Service Oriented Architecture (SOA). This study aims to define and validate an approach to develop WS based on the practice of TDD, called WS-TDD. This approach guides developers to use TDD to develop WS, suggesting tools and techniques to deal with SOA particularities and dependencies, focusing on the creation of the unitary and integrated automated tests in Java. In order to define and validate the proposed approach, four research methods have been carried out: (i) questionnaire; (ii) practical experiment; (iii) personal interview with each participant in the experiment and (iv) triangulation of the results with the people who participated in the three previous methods. According to the obtained results, WS-TDD was more efficient compared to TLD, increasing internal software quality and developer productivity. However, the external software quality has decreased due to a greater number of defects compared to the TLD approach. Finally, it is important to highlight that the proposed approach is a simple and practical alternative for the adoption of TDD in the development of WS, bringing benefits to internal quality and contributing to increase the developers’ productivity. However, the external software quality has decreased when using WS-TDD.

Indiana University-Purdue University Indianapolis (IUPUI) / The emergence of information exchange and act of offering features through external interfaces is a vast but immensely valuable challenge, and essential elements of learning environments cannot be excluded. Nowadays, there are a lot of different service providers working in the learning systems market and each of them has their own advantages. On that premise, in today's world even large learning management systems are trying to cooperate with each other in order to be best. For instance, Instructure is a substantial company and can easily employ a dedicated team tasked with the development of a video conferencing functionality, but it chooses to use an open source alternative instead: The BigBlueButton. Unfortunately, different learning system manufacturers are using different technologies for various reasons, making integration that much harder. Standards in learning environments have come to resolve problems regarding exchanging information, providing and consuming functionalities externally and simultaneously minimizing the amount of effort needed to integrate systems. In addition to defining and simplifying these standards, careful consideration is essential when designing new, comprehensive and useful systems, as well as adding interoperability to existing systems, all which subsequently took part in this research. In this research I have reviewed most of the standards and protocols for integration in learning environments and proposed a revised approach for app stores in learning environments. Finally, as a case study, a learning tool has been developed to avail essential functionalities of a social educational learning management system integrated with other learning management systems. This tool supports the dominant and most popular standards for interoperability and can be added to learning management systems within seconds.