O custo de serviços na Internet tem encorajado o uso de cache a nível de aplicação para suprir as demandas dos usuários e melhorar a escalabilidade e disponibilidade de aplicações. Cache a nível de aplicação, onde desenvolvedores manualmente controlam o conteúdo cacheado, tem sido adotada quando soluções tradicionais de cache não são capazes de atender aos requisitos de desempenho desejados. Apesar de sua crescente popularidade, este tipo de cache é tipicamente endereçado de maneira ad-hoc, uma vez que depende de detalhes específicos da aplicação para ser desenvolvida. Dessa forma, tal cache consiste em uma tarefa que requer tempo e esforço, além de ser altamente suscetível a erros. Esta dissertação avança o trabalho relacionado a cache a nível de aplicação provendo uma compreensão de seu estado de prática e automatizando a identificação de conteúdo cacheável, fornecendo assim suporte substancial aos desenvolvedores para o projeto, implementação e manutenção de soluções de caching. Mais especificamente, este trabalho apresenta três contribuições: a estruturação de conhecimento sobre caching derivado de um estudo qualitativo, um levantamento do estado da arte em abordagens de cache estáticas e adaptativas, e uma técnica que automatiza a difícil tarefa de identificar oportunidades de cache O estudo qualitativo, que envolveu a investigação de dez aplicações web (código aberto e comercial) com características diferentes, permitiu-nos determinar o estado de prática de cache a nível de aplicação, juntamente com orientações práticas aos desenvolvedores na forma de padrões e diretrizes. Com base nesses padrões e diretrizes derivados, também propomos uma abordagem para automatizar a identificação de métodos cacheáveis, que é geralmente realizado manualmente por desenvolvedores. Tal abordagem foi implementada como um framework, que pode ser integrado em aplicações web para identificar automaticamente oportunidades de cache em tempo de execução, com base na monitoração da execução do sistema e gerenciamento adaptativo das decisões de cache. Nós avaliamos a abordagem empiricamente com três aplicações web de código aberto, e os resultados indicam que a abordagem é capaz de identificar oportunidades de cache adequadas, melhorando o desempenho das aplicações em até 12,16%. / Latency and cost of Internet-based services are encouraging the use of application-level caching to continue satisfying users’ demands, and improve the scalability and availability of origin servers. Application-level caching, in which developers manually control cached content, has been adopted when traditional forms of caching are insufficient to meet such requirements. Despite its popularity, this level of caching is typically addressed in an adhoc way, given that it depends on specific details of the application. Furthermore, it forces application developers to reason about a crosscutting concern, which is unrelated to the application business logic. As a result, application-level caching is a time-consuming and error-prone task, becoming a common source of bugs. This dissertation advances work on application-level caching by providing an understanding of its state-of-practice and automating the decision regarding cacheable content, thus providing developers with substantial support to design, implement and maintain application-level caching solutions. More specifically, we provide three key contributions: structured knowledge derived from a qualitative study, a survey of the state-of-the-art on static and adaptive caching approaches, and a technique and framework that automate the challenging task of identifying cache opportunities The qualitative study, which involved the investigation of ten web applications (open-source and commercial) with different characteristics, allowed us to determine the state-of-practice of application-level caching, along with practical guidance to developers as patterns and guidelines to be followed. Based on such patterns and guidelines derived, we also propose an approach to automate the identification of cacheable methods, which is often manually done and is not supported by existing approaches to implement application-level caching. We implemented a caching framework that can be seamlessly integrated into web applications to automatically identify and cache opportunities at runtime, by monitoring system execution and adaptively managing caching decisions. We evaluated our approach empirically with three open-source web applications, and results indicate that we can identify adequate caching opportunities by improving application throughput up to 12.16%. Furthermore, our approach can prevent code tangling and raise the abstraction level of caching.

Submitted by Renata Lopes (renatasil82@gmail.com) on 2017-10-21T01:04:22Z No. of bitstreams: 1 claudioaugustosilveiralelis.pdf: 7232359 bytes, checksum: 731c10b688562fad8855da41890a7f97 (MD5) / Approved for entry into archive by Adriana Oliveira (adriana.oliveira@ufjf.edu.br) on 2017-10-21T13:13:19Z (GMT) No. of bitstreams: 1 claudioaugustosilveiralelis.pdf: 7232359 bytes, checksum: 731c10b688562fad8855da41890a7f97 (MD5) / Made available in DSpace on 2017-10-21T13:13:19Z (GMT). No. of bitstreams: 1 claudioaugustosilveiralelis.pdf: 7232359 bytes, checksum: 731c10b688562fad8855da41890a7f97 (MD5) Previous issue date: 2017-08-30 / CAPES - Coordenação de Aperfeiçoamento de Pessoal de Nível Superior / A importância dos softwares nas organizações é crescente. No entanto, para manter seu valor, o software deve ser alterado e atualizado. A manutenção de software depende da alocação de recursos humanos para o cumprimento das atividades de alteração definidas. Entretanto, em um cenário distribuído no qual a colaboração é fundamental para o bom funcionamento das atividades, torna-se uma tarefa não trivial designar desenvolvedores para as atividades de manutenção. Neste contexto, a reputação se torna um elemento chave, afetando os elementos de colaboração, tais como: a coordenação, a cooperação, e a comunicação. Portanto, o acompanhamento da evolução da reputação é importante para promover a colaboração nas atividades de manutenção. A teoria de Dinâmica de Sistemas pode ser aplicada no acompanhamento da evolução da reputação. Através dos dados obtidos, é possível compreender o passado, estabelecer o que ocorre no presente e projetar o comportamento futuro da reputação. Diante disso, este trabalho apresenta um modelo para cálculo da reputação dos desenvolvedores de software, apoiado por técnicas de Dinâmica de Sistemas, o qual permite simular como a reputação se comporta ao longo do tempo. Este modelo serviu de base para a construção de uma infraestrutura para informações de reputação dinâmica, cujo objetivo é possibilitar o gerenciamento e acompanhamento de informações de reputação dos desenvolvedores geograficamente distribuídos de forma a apoiar a alocação desses desenvolvedores às tarefas de manutenção. Além disso, oferece elementos de visualização e colaboração, em um ambiente integrado às atividades de manutenção de software. Uma prova de conceito e um experimento realizados com dados reais de uma empresa são apresentados com o intuito de identificar a viabilidade e aderência do modelo proposto, bem como dos demais recursos oferecidos pela infraestrutura. / The importance of software in organizations is growing. However, to maintain its value, the software must be changed and updated. Software maintenance depends on the allocation of human resources to fulfill defined change activities. However, in a distributed scenario in which collaboration is critical to the well running of activities, designate developers for maintenance activities becomes a non-trivial task. In this context, reputation becomes a key element, affecting elements of collaboration, such as: coordination, cooperation, and communication. Therefore, tracking reputation evolution is important to promote collaboration in maintenance activities. The theory of System Dynamics can be applied in monitoring the evolution of reputation. Through the data obtained, it is possible to understand the past, establish what occurs in the present, and project future reputation behavior. Therefore, this work presents a model for calculating the reputation of software developers, supported by System Dynamics techniques, which allows simulating how reputation behaves over time. This model served as the basis for building an infrastructure for dynamic reputation information, which aims to enable the management and tracking reputation information of geographically distributed developers to support the allocation of these developers to maintenance tasks. In addition, it provides visualization and collaboration elements in an integrated environment for software maintenance activities. A proof of concept and an experiment made with real data of a company are presented with the intention of identifying the feasibility and adherence of the proposed model, as well as of the other resources offered by the infrastructure.

A variety of markup languages exist for formatting text and exporting to HTML. These languages are tailored to the needs in a specific context by specialising tags, selecting tags and limiting the number of possible distinctions to a subset of what is available in HTML. However, limiting the number of possible distinctions creates problems when changes occur in the context. The real world is ever-changing, thus that which models it must be able to reflect the changes in the operational environment to remain relevant and satisfactory. Incorporating new requirements and adjusting to the changes in requirements means adapting and evolving. This thesis explores giving document authors the possibility to extend and modify the repertoire of available markup tags when new user requirements demand it. What is presented is a prototype which allows the user to tailor the markup and also adapt it to changes in the environment. The system allows users to create their own set of markup tags, annotate their documents with them, and export a generated XML document. Users create the tag and assign a meaning to it, when changes occur in the requirements they can be implemented by modifying the tags, extending the repertoire by adding tags, or changing the meaning of a defined tag.

Abstract To gain competitive advantage and thrive in the market, companies have introduced Kanban in software development. Kanban has been used in the manufacturing industry for over six decades. In the software engineering domain, Kanban was introduced in 2004 to increase flexibility in coping with dynamic requirements, bring visibility to workflow and related tasks, improve communication, and promote the pull system. However, the existing scientific literature lacks empirical evidence of the use of Kanban in software companies. This doctoral thesis aims to improve the understanding of the use of Kanban in software engineering. The research was performed in two phases: 1) analysis of scientific literature on Kanban in software engineering and industrial engineering and 2) investigation of Kanban implementation trends in software companies. The data was collected through systematic literature reviews, survey and semi-structured interviews. The results were synthesized to draw conclusions and outline implications for research and practice. The results indicate growing interest in the use of Kanban in software companies. The findings suggest that Kanban is applicable to software development, software maintenance, and portfolio management in software companies. Kanban brings visibility to task and offering status, limits work in progress at any given time gives people greater control over their work and limit task switching. Although Kanban offers several benefits, as reported in this dissertation, the findings show that software companies find it challenging to implement Kanban incrementally. / Tiivistelmä Ohjelmistoteollisuudessa Kanbanin käyttö on yleistynyt vuodesta 2004 alkaen. Sillä pyritään tuomaan joustavuutta muuttuvien vaatimusten hallintaan, tuomaan näkyvyyttä työnkulkuun ja toisiinsa liittyviin tehtäviin, parantamaan kommunikaatiota sekä edistämään imuohjauksen hyödyntämistä. Kanbania on käytetty valmistavassa teollisuudessa jo yli kuuden vuosikymmenen ajan. Olemassa olevassa tieteellisessä kirjallisuudessa on kuitenkin esitetty hyvin vähän empiirisiä tutkimustuloksia Kanbanin käytöstä ohjelmistoyrityksissä. Väitöskirjan tavoitteena on parantaa ymmärrystä Kanbanin käytöstä ohjelmistotuotannossa. Tutkimus toteutettiin kahdessa vaiheessa: 1) Kirjallisuusanalyysi Kanbanin käytöstä ohjelmistotuotannossa ja tuotantotekniikassa ja 2) Empiirinen tutkimus Kanbanin käyttöönoton trendeistä ohjelmistoyrityksissä. Tutkimusaineisto kerättiin systemaattisten kirjallisuuskatsausten, kyselytutkimuksen ja puolistrukturoitujen teemahaastattelujen kautta. Tutkimustulosten synteesin pohjalta tehtiin johtopäätöksiä Kanbanin käytöstä ohjelmistotuotannossa sekä niiden merkityksestä alan tutkimukselle ja Kanbanin käytölle yrityksissä. Tutkimuksen tulokset osoittavat kasvavaa kiinnostusta Kanbanin käyttöä kohtaan ohjelmistoyrityksissä. Tulosten perusteella Kanban soveltuu käytettäväksi ohjelmistokehityksessä, ohjelmistojen ylläpidossa sekä tuoteportfolion hallinnassa. Kanban tuo näkyvyyttä ohjelmistokehitykseen, niin meneillään olevien tehtävien kuin portfoliotarjoaman osalta. Se myös auttaa rajoittamaan työtehtävien ruuhkautumista ja antaa kehittäjille paremman tavan hallita työtään rajoittamalla työtehtävien vaihtoa. Vaikka Kanbanin käytöllä on mahdollista saavuttaa väitöskirjatutkimuksessa esitettyjä hyötyjä, tulokset osoittavat, että ohjelmistoyrityksillä on haasteita Kanbanin inkrementaalisessa käyttöönotossa.

This report evaluates the team-structure of three software maintenance teams in order to decide their level of featureness (a term that defines to what extent a team has the quality (the set of characteristics) of being a feature team). Simulations of changes that are expressed as beneficial in an agile environment and that could increase the teams‘ level of featureness within the team structure are performed. The results show that each team‘s level of featureness is affected differently by each change. Partly, this underlines the importance of understanding the current team-structure before implementing changes that aim to increase the level of featureness. And secondly, within the scope of the study, the change where a user expert is declared a team member is concluded as the change that increases the teams‘ level of featureness the most. Based on the results the report also concludes that it is essential to implement changes that affect different, which in combination can increase the level of featureness.

Masters of Science / Coders of databases repeatedly face the problem of checking their Structured Query Language (SQL) code. Instructors face the difficulty of checking student projects and lab assignments in database courses. We collect and categorize common MySQL programming errors into three groups: data definition errors, data manipulation errors, and transaction control errors. We build these into a comprehensive list of MySQL errors, which novices are inclined make during database programming. We collected our list of common MySQL errors both from the technical literature and directly by noting errors made in assignments handed in by students. In the results section of this research, we check and summarize occurrences of these errors based on three characteristics as semantics, syntax, and logic. These data form the basis of a future static MySQL checker that will eventually assist database coders to correct their code automatically. These errors also form a useful checklist to guide students away from the mistakes that they are prone to make.

Les systèmes logiciels sont devenus de plus en plus répondus et importants dans notre société. Ainsi, il y a un besoin constant de logiciels de haute qualité. Pour améliorer la qualité de logiciels, l’une des techniques les plus utilisées est le refactoring qui sert à améliorer la structure d'un programme tout en préservant son comportement externe. Le refactoring promet, s'il est appliqué convenablement, à améliorer la compréhensibilité, la maintenabilité et l'extensibilité du logiciel tout en améliorant la productivité des programmeurs. En général, le refactoring pourra s’appliquer au niveau de spécification, conception ou code. Cette thèse porte sur l'automatisation de processus de recommandation de refactoring, au niveau code, s’appliquant en deux étapes principales: 1) la détection des fragments de code qui devraient être améliorés (e.g., les défauts de conception), et 2) l'identification des solutions de refactoring à appliquer. Pour la première étape, nous traduisons des régularités qui peuvent être trouvés dans des exemples de défauts de conception. Nous utilisons un algorithme génétique pour générer automatiquement des règles de détection à partir des exemples de défauts. Pour la deuxième étape, nous introduisons une approche se basant sur une recherche heuristique. Le processus consiste à trouver la séquence optimale d'opérations de refactoring permettant d'améliorer la qualité du logiciel en minimisant le nombre de défauts tout en priorisant les instances les plus critiques. De plus, nous explorons d'autres objectifs à optimiser: le nombre de changements requis pour appliquer la solution de refactoring, la préservation de la sémantique, et la consistance avec l’historique de changements. Ainsi, réduire le nombre de changements permets de garder autant que possible avec la conception initiale. La préservation de la sémantique assure que le programme restructuré est sémantiquement cohérent. De plus, nous utilisons l'historique de changement pour suggérer de nouveaux refactorings dans des contextes similaires. En outre, nous introduisons une approche multi-objective pour améliorer les attributs de qualité du logiciel (la flexibilité, la maintenabilité, etc.), fixer les « mauvaises » pratiques de conception (défauts de conception), tout en introduisant les « bonnes » pratiques de conception (patrons de conception). / Software systems have become prevalent and important in our society. There is a constant need for high-quality software. Hence, to improve software quality, one of the most-used techniques is the refactoring which improves design structure while preserving the external behavior. Refactoring has promised, if applied well, to improve software readability, maintainability and extendibility while increasing the speed at which programmers can write and maintain their code. In general, refactoring can be performed in various levels such as the requirement, design, or code level. In this thesis, we mainly focus on the source code level where automated refactoring recommendation can be performed through two main steps: 1) detection of code fragments that need to be improved/fixed (e.g., code-smells), and 2) identification of refactoring solutions to achieve this goal. For the code-smells identification step, we translate regularities that can be found in such code-smell examples into detection rules. To this end, we use genetic programming to automatically generate detection rules from examples of code-smells. For the refactoring identification step, a search-based approach is used. The process aims at finding the optimal sequence of refactoring operations that improve software quality by minimizing the number of detected code-smells while prioritizing the most critical ones. In addition, we explore other objectives to optimize using a multi-objective approach: the code changes needed to apply refactorings, semantics preservation, and the consistency with development change history. Hence, reducing code changes allows us to keep as much as possible the initial design. On the other hand, semantics preservation insures that the refactored program is semantically coherent, and that it models correctly the domain-semantics. Indeed, we use knowledge from historical code change to suggest new refactorings in similar contexts. Furthermore, we introduce a novel multi-objective approach to improve software quality attributes (i.e., flexibility, maintainability, etc.), fix “bad” design practices (i.e., code-smells) while promoting “good” design practices (i.e., design patterns).

Bons códigos importam, mas como saber quando a qualidade está baixa? Maus cheiros de código, ou anomalias, auxiliam desenvolvedores na identificação de trechos de código problemáticos, porém a maioria dos maus cheiros catalogados são voltados para práticas e tecnologias tradicionais, criadas entre as décadas de 70 a 90, como orientação a objetos e Java. Ainda há dúvidas sobre maus cheiros em tecnologias que surgiram na última década, como o Android, principal plataforma móvel em 2017 com mais de 86% de participação de mercado. Alguns pesquisadores derivaram maus cheiros Android relacionados à eficiência e à usabilidade. Outros notaram que maus cheiros específicos ao Android são muito mais frequentes nos aplicativos do que maus cheiros tradicionais. Diversas pesquisas concluíram que os componentes Android mais afetados por maus cheiros tradicionais são Activities e Adapters, que pertencem à camada de apresentação. Notou-se também que em alguns aplicativos, códigos da camada de apresentação representam a maior parte do código do projeto. Vale ressaltar que a camada de apresentação Android também é composta por arquivos XML, chamados de recursos, usados na construção da interface do usuário (User Interface - UI), porém nenhuma das pesquisas citadas os considerou em suas análises. Nesta dissertação, investigamos a existência de maus cheiros relacionados à camada de apresentação Android considerando inclusive os recursos. Fizemos isso através de dois questionários e um experimento de código online, totalizando a participação de 316 desenvolvedores. Nossos resultados mostram a existência de uma percepção comum entre desenvolvedores sobre más práticas no desenvolvimento da camada de apresentação Android. Nossas principais contribuições são um catálogo com 20 maus cheiros da camada de apresentação Android e uma análise estatística da percepção de desenvolvedores sobre os 7 principais maus cheiros catalogados. Nossas contribuições servirão a pesquisadores como ponto de partida para a definição de heurísticas e implementação de ferramentas automatizadas e a desenvolvedores como auxílio na identificação de códigos problemáticos, ainda que de forma manual. / We are aware that good code matters, but how to know when quality is low? Code smells, or anomalies, help us identify problematic code snippets, but most of the code smells cataloged are based on traditional practices and technologies, created from the 70s through the 90s, such as object oriented programming and Java. There are still doubts about code smells in technologies that have emerged in the last decade, such as Android, the main mobile platform in 2017 with more than 86% market share. Some researchers have defined code smells related to Android efficiency and usability. Other research concludes that the components most affected by traditional code smells are related to the front-end components, such as Activities and Adapters. Also noticed in some applications, front-end code represent the larger part of the projects code. It is worth mentioning that the Android presentation layer is also composed of XML files, called resources, used to build the user interface (UI), but none of the cited research considered them in their analyzes. In this dissertation, we investigate the existence of code smells related to the Android front-end, including application resources. We performed two online surveys and one online code experiment, summing 316 developers. Our results show that there is a common perception among Android developers about bad practices on Android front-end. Our main contributions are a catalog of 20 code smells related to the Android front-end and a statistical analysis of the perceptions of developers about the 7 main code smells cataloged. Our contributions will provide to researchers a starting point for the definition of heuristics and implementation of automated tools and to developers as an aid in identifying problematic codes.

"Because many software systems used for business today are considered legacy systems, the need for software evolution techniques has never been greater. We propose a novel evolution methodology for legacy systems that integrates the concepts of features, regression testing, and Component-Based Software Engineering (CBSE). Regression test suites are untapped resources that contain important information about the features of a software system. By exercising each feature with its associated test cases using code profilers and similar tools, code can be located and refactored to create components. The unique combination of Feature Engineering and CBSE makes it possible for a legacy system to be modernized quickly and affordably. We develop a new framework to evolve legacy software that maps the features to software components refactored from their feature implementation. In this dissertation, we make the following contributions: First, a new methodology to evolve legacy code is developed that improves the maintainability of evolved legacy systems. Second, the technique describes a clear understanding between features and functionality, and relationships among features using our feature model. Third, the methodology provides guidelines to construct feature-based reusable components using our fine-grained component model. Fourth, we bridge the complexity gap by identifying feature-based test cases and developing feature-based reusable components. We show how to reuse existing tools to aid the evolution of legacy systems rather than re-writing special purpose tools for program slicing and requirement management. We have validated our approach on the evolution of a real-world legacy system. By applying this methodology, American Financial Systems, Inc. (AFS), has successfully restructured its enterprise legacy system and reduced the costs of future maintenance. "

Bons códigos importam, mas como saber quando a qualidade está baixa? Maus cheiros de código, ou anomalias, auxiliam desenvolvedores na identificação de trechos de código problemáticos, porém a maioria dos maus cheiros catalogados são voltados para práticas e tecnologias tradicionais, criadas entre as décadas de 70 a 90, como orientação a objetos e Java. Ainda há dúvidas sobre maus cheiros em tecnologias que surgiram na última década, como o Android, principal plataforma móvel em 2017 com mais de 86% de participação de mercado. Alguns pesquisadores derivaram maus cheiros Android relacionados à eficiência e à usabilidade. Outros notaram que maus cheiros específicos ao Android são muito mais frequentes nos aplicativos do que maus cheiros tradicionais. Diversas pesquisas concluíram que os componentes Android mais afetados por maus cheiros tradicionais são Activities e Adapters, que pertencem à camada de apresentação. Notou-se também que em alguns aplicativos, códigos da camada de apresentação representam a maior parte do código do projeto. Vale ressaltar que a camada de apresentação Android também é composta por arquivos XML, chamados de recursos, usados na construção da interface do usuário (User Interface - UI), porém nenhuma das pesquisas citadas os considerou em suas análises. Nesta dissertação, investigamos a existência de maus cheiros relacionados à camada de apresentação Android considerando inclusive os recursos. Fizemos isso através de dois questionários e um experimento de código online, totalizando a participação de 316 desenvolvedores. Nossos resultados mostram a existência de uma percepção comum entre desenvolvedores sobre más práticas no desenvolvimento da camada de apresentação Android. Nossas principais contribuições são um catálogo com 20 maus cheiros da camada de apresentação Android e uma análise estatística da percepção de desenvolvedores sobre os 7 principais maus cheiros catalogados. Nossas contribuições servirão a pesquisadores como ponto de partida para a definição de heurísticas e implementação de ferramentas automatizadas e a desenvolvedores como auxílio na identificação de códigos problemáticos, ainda que de forma manual. / We are aware that good code matters, but how to know when quality is low? Code smells, or anomalies, help us identify problematic code snippets, but most of the code smells cataloged are based on traditional practices and technologies, created from the 70s through the 90s, such as object oriented programming and Java. There are still doubts about code smells in technologies that have emerged in the last decade, such as Android, the main mobile platform in 2017 with more than 86% market share. Some researchers have defined code smells related to Android efficiency and usability. Other research concludes that the components most affected by traditional code smells are related to the front-end components, such as Activities and Adapters. Also noticed in some applications, front-end code represent the larger part of the projects code. It is worth mentioning that the Android presentation layer is also composed of XML files, called resources, used to build the user interface (UI), but none of the cited research considered them in their analyzes. In this dissertation, we investigate the existence of code smells related to the Android front-end, including application resources. We performed two online surveys and one online code experiment, summing 316 developers. Our results show that there is a common perception among Android developers about bad practices on Android front-end. Our main contributions are a catalog of 20 code smells related to the Android front-end and a statistical analysis of the perceptions of developers about the 7 main code smells cataloged. Our contributions will provide to researchers a starting point for the definition of heuristics and implementation of automated tools and to developers as an aid in identifying problematic codes.