This thesis examines integration testing of object-oriented software. The process of integrating and testing procedural programs is reviewed as foundation for testing object-oriented software. The complexity of object-oriented software is examined. The relationship of integration testing and the software development life cycle is presented. Scenarios are discussed which account for the introduction of defects into the software. The Unified Modeling Language (UML) is chosen for representing pre-implementation and post-implementation models of the software. A demonstration of the technique of using post-implementation models representing the logical and physical views as an aid in integration and system testing of the software is presented. The use of UML diagrams developed from the software is suggested as a technique for integration testing of object-oriented software. The need for automating the data collection and model building is recognized. The technique is integrated into the Revised Spiral Model for Object-Oriented Software Development developed by du Plessis and van der Walt. / Computing / D.Phil. (Computer Science)

This thesis examines integration testing of object-oriented software. The process of integrating and testing procedural programs is reviewed as foundation for testing object-oriented software. The complexity of object-oriented software is examined. The relationship of integration testing and the software development life cycle is presented. Scenarios are discussed which account for the introduction of defects into the software. The Unified Modeling Language (UML) is chosen for representing pre-implementation and post-implementation models of the software. A demonstration of the technique of using post-implementation models representing the logical and physical views as an aid in integration and system testing of the software is presented. The use of UML diagrams developed from the software is suggested as a technique for integration testing of object-oriented software. The need for automating the data collection and model building is recognized. The technique is integrated into the Revised Spiral Model for Object-Oriented Software Development developed by du Plessis and van der Walt. / Computing / D.Phil. (Computer Science)

Les sociétés modernes dépendent de plus en plus sur les systèmes informatiques et ainsi, il y a de plus en plus de pression sur les équipes de développement pour produire des logiciels de bonne qualité. Plusieurs compagnies utilisent des modèles de qualité, des suites de programmes qui analysent et évaluent la qualité d'autres programmes, mais la construction de modèles de qualité est difficile parce qu'il existe plusieurs questions qui n'ont pas été répondues dans la littérature. Nous avons étudié les pratiques de modélisation de la qualité auprès d'une grande entreprise et avons identifié les trois dimensions où une recherche additionnelle est désirable : Le support de la subjectivité de la qualité, les techniques pour faire le suivi de la qualité lors de l'évolution des logiciels, et la composition de la qualité entre différents niveaux d'abstraction. Concernant la subjectivité, nous avons proposé l'utilisation de modèles bayésiens parce qu'ils sont capables de traiter des données ambiguës. Nous avons appliqué nos modèles au problème de la détection des défauts de conception. Dans une étude de deux logiciels libres, nous avons trouvé que notre approche est supérieure aux techniques décrites dans l'état de l'art, qui sont basées sur des règles. Pour supporter l'évolution des logiciels, nous avons considéré que les scores produits par un modèle de qualité sont des signaux qui peuvent être analysés en utilisant des techniques d'exploration de données pour identifier des patrons d'évolution de la qualité. Nous avons étudié comment les défauts de conception apparaissent et disparaissent des logiciels. Un logiciel est typiquement conçu comme une hiérarchie de composants, mais les modèles de qualité ne tiennent pas compte de cette organisation. Dans la dernière partie de la dissertation, nous présentons un modèle de qualité à deux niveaux. Ces modèles ont trois parties: un modèle au niveau du composant, un modèle qui évalue l'importance de chacun des composants, et un autre qui évalue la qualité d'un composé en combinant la qualité de ses composants. L'approche a été testée sur la prédiction de classes à fort changement à partir de la qualité des méthodes. Nous avons trouvé que nos modèles à deux niveaux permettent une meilleure identification des classes à fort changement. Pour terminer, nous avons appliqué nos modèles à deux niveaux pour l'évaluation de la navigabilité des sites web à partir de la qualité des pages. Nos modèles étaient capables de distinguer entre des sites de très bonne qualité et des sites choisis aléatoirement. Au cours de la dissertation, nous présentons non seulement des problèmes théoriques et leurs solutions, mais nous avons également mené des expériences pour démontrer les avantages et les limitations de nos solutions. Nos résultats indiquent qu'on peut espérer améliorer l'état de l'art dans les trois dimensions présentées. En particulier, notre travail sur la composition de la qualité et la modélisation de l'importance est le premier à cibler ce problème. Nous croyons que nos modèles à deux niveaux sont un point de départ intéressant pour des travaux de recherche plus approfondis. / As society becomes ever more dependent on computer systems, there is more and more pressure on development teams to produce high-quality software. Many companies therefore rely on quality models, program suites that analyse and evaluate the quality of other programs, but building good quality models is hard as there are many questions concerning quality modelling that have yet to be adequately addressed in the literature. We analysed quality modelling practices in a large organisation and identified three dimensions where research is needed: proper support of the subjective notion of quality, techniques to track the quality of evolving software, and the composition of quality judgments from different abstraction levels. To tackle subjectivity, we propose using Bayesian models as these can deal with uncertain data. We applied our models to the problem of anti-pattern detection. In a study of two open-source systems, we found that our approach was superior to state of the art rule-based techniques. To support software evolution, we consider scores produced by quality models as signals and the use of signal data-mining techniques to identify patterns in the evolution of quality. We studied how anti-patterns are introduced and removed from systems. Software is typically written using a hierarchy of components, yet quality models do not explicitly consider this hierarchy. As the last part of our dissertation, we present two level quality models. These are composed of three parts: a component-level model, a second model to evaluate the importance of each component, and a container-level model to combine the contribution of components with container attributes. This approach was tested on the prediction of class-level changes based on the quality and importance of its components: methods. It was shown to be more useful than single-level, traditional approaches. To finish, we reapplied this two-level methodology to the problem of assessing web site navigability. Our models could successfully distinguish award-winning sites from average sites picked at random. Throughout the dissertation, we present not only theoretical problems and solutions, but we performed experiments to illustrate the pros and cons of our solutions. Our results show that there are considerable improvements to be had in all three proposed dimensions. In particular, our work on quality composition and importance modelling is the first that focuses on this particular problem. We believe that our general two-level models are only a starting point for more in-depth research.

Defect prediction models assist tester practitioners on prioritizing the most defect-prone parts of the software. The approach called Cross-Project Defect Prediction (CPDP) refers to the use of known external projects to compose the training set. This approach is useful when the amount of historical defect data of a company to compose the training set is inappropriate or insufficient. Although the principle is attractive, the predictive performance is a limiting factor. In recent years, several methods were proposed aiming at improving the predictive performance of CPDP models. However, to the best of our knowledge, there is no evidence of which CPDP methods typically perform best. Moreover, there is no evidence on which CPDP methods perform better for a specific application domain. In fact, there is no machine learning algorithm suitable for all domains. The decision task of selecting an appropriate algorithm for a given application domain is investigated in the meta-learning literature. A meta-learning model is characterized by its capacity of learning from previous experiences and adapting its inductive bias dynamically according to the target domain. In this work, we investigate the feasibility of using meta-learning for the recommendation of CPDP methods. In this thesis, three main goals were pursued. First, we provide an experimental analysis to investigate the feasibility of using Feature Selection (FS) methods as an internal procedure to improve the performance of two specific CPDP methods. Second, we investigate which CPDP methods present typically best performances. We also investigate whether the typically best methods perform best for the same project datasets. The results reveal that the most suitable CPDP method for a project can vary according to the project characteristics, which leads to the third investigation of this work. We investigate the several particularities inherent to the CPDP context and propose a meta-learning solution able to learn from previous experiences and recommend a suitable CDPD method according to the characteristics of the project being predicted. We evaluate the learning capacity of the proposed solution and its performance in relation to the typically best CPDP methods. / Modelos de predição de defeitos auxiliam profissionais de teste na priorização de partes do software mais propensas a conter defeitos. A abordagem de predição de defeitos cruzada entre projetos (CPDP) refere-se à utilização de projetos externos já conhecidos para compor o conjunto de treinamento. Essa abordagem é útil quando a quantidade de dados históricos de defeitos é inapropriada ou insuficiente para compor o conjunto de treinamento. Embora o princípio seja atrativo, o desempenho de predição é um fator limitante nessa abordagem. Nos últimos anos, vários métodos foram propostos com o intuito de melhorar o desempenho de predição de modelos CPDP. Contudo, na literatura, existe uma carência de estudos comparativos que apontam quais métodos CPDP apresentam melhores desempenhos. Além disso, não há evidências sobre quais métodos CPDP apresentam melhor desempenho para um domínio de aplicação específico. De fato, não existe um algoritmo de aprendizado de máquina que seja apropriado para todos os domínios de aplicação. A tarefa de decisão sobre qual algoritmo é mais adequado a um determinado domínio de aplicação é investigado na literatura de meta-aprendizado. Um modelo de meta-aprendizado é caracterizado pela sua capacidade de aprender a partir de experiências anteriores e adaptar seu viés de indução dinamicamente de acordo com o domínio alvo. Neste trabalho, nós investigamos a viabilidade de usar meta-aprendizado para a recomendação de métodos CPDP. Nesta tese são almejados três principais objetivos. Primeiro, é conduzida uma análise experimental para investigar a viabilidade de usar métodos de seleção de atributos como procedimento interno de dois métodos CPDP, com o intuito de melhorar o desempenho de predição. Segundo, são investigados quais métodos CPDP apresentam um melhor desempenho em um contexto geral. Nesse contexto, também é investigado se os métodos com melhor desempenho geral apresentam melhor desempenho para os mesmos conjuntos de dados (ou projetos de software). Os resultados revelam que os métodos CPDP mais adequados para um projeto podem variar de acordo com as características do projeto sendo predito. Essa constatação conduz à terceira investigação realizada neste trabalho. Foram investigadas as várias particularidades inerentes ao contexto CPDP a fim de propor uma solução de meta-aprendizado capaz de aprender com experiências anteriores e recomendar métodos CPDP adequados, de acordo com as características do software. Foram avaliados a capacidade de meta-aprendizado da solução proposta e a sua performance em relação aos métodos base que apresentaram melhor desempenho geral.

The technical debt field covers an critical problem of software engineering, and this is one of the reasons why this field has received significant attention in recent years. The technical debt metaphor helps developers to think about, and to monitor software quality. The metaphor refers to flaws in software (usually caused by shortcuts to save time) that may affect future maintenance and evolution. It was created by Cunningham to improve the quality of software delivery. Many times the technical debt items are unknown, unmonitored and therefore not managed, thus resulting in high maintenance costs throughout the software life-cycle. We conducted an empirical study in an academic environment, during two offerings of a laboratory course on Extreme Programming (XP Lab) at University of São Paulo and in two Brazilian Software Companies (Company A and B). We analyzed thirteen teams, nine in the Academy and four in the Companies environment. The teams had a comprehensive lecture about technical debt and several ways to identify and manage technical debt were presented. We monitored the teams, performed interviews, did close observations and collected feedback. The obtained results show that the awareness of technical debt influences team behavior. Team members report thinking and discussing more on software quality after becoming aware of technical debt in their projects. We identified some impacts on the teams and the projects after having considered technical debt. A conceptual model for technical debt management was created including ways of how identifying, monitoring, categorizing, measuring, prioritizing, and paying off the technical debt. A few approaches and techniques for the technical debt management, identification, monitoring, measure, and payment are also suggested. / A metáfora de dívida técnica engloba um importante problema da engenharia de software e essa é uma das razões pelas quais este campo tem recebido uma grande atenção nos últimos anos. Essa metáfora auxilia os desenvolvedores de software a refletirem sobre e a monitorarem a qualidade de software. A metáfora se refere a falhas no software (geralmente causadas por atalhos para economizar tempo) que podem afetar a futura manutenção e evolução do mesmo. A metáfora foi criada por Cunningham com o objetivo de melhorar a qualidade das entregas de software. Muitas vezes as dívidas técnicas não são conhecidas, monitoradas e nem geridas, resultando em um alto custo de manutenção ao longo do ciclo de vida do software. Logo, conduziu-se um estudo empírico na academia, durante duas ofertas da disciplina de Programação Extrema (XP Lab) na Universidade de São Paulo e em duas empresas Brasileiras de desenvolvimento de software (Empresa A e B). Foram analisados treze times, sendo nove na academia e quatro nas empresas. Os times tiveram uma apresentação sobre dívida técnica e foram apresentadas algumas sugestões de abordagens para gerir dívida técnica. Monitorou-se os times, foram realizadas entrevistas, observações fechadas e informações foram coletadas. Os resultados mostraram que considerar dívida técnica influenciou o comportamento dos times. Eles reportaram que após considerar dívida técnica passaram a refletir e discutir mais a qualidade do software. Identificou-se alguns impactos nos times e nos projetos depois de considerarem dívida técnica. Um modelo conceitual para gestão de dívida técnica foi criado, incluindo formas, técnicas e abordagens de como identificar, monitorar, categorizar, medir, priorizar e pagar os itens de dívida técnica.

Esta pesquisa trata do desenvolvimento de uma estrutura conceitual para um framework de maturidade, para o domínio de ecossistemas digitais de produção de software, utilizando a pesquisa-ação como paradigma de pesquisa. A estrutura de medição proposta tem como base o critério descrito no item 5 da Norma ISO/IEC 15504-2 Uma Estrutura de Medição para a capacidade de processo, com as adaptações necessárias para o domínio do Software Publico Brasileiro (SPB). O framework tem como objetivo o desenvolvimento de referências conceituais para um modelo de maturidade de um ecossistema público de software, considerando as referências do pensamento sistêmico. A abordagem do pensamento sistêmico permitiu identificar que o ecossistema evolui em ciclos de aprendizado que resultaram em um modelo de maturidade. Foi observado também que a mesma abordagem pode ser utilizada em outros ecossistemas. O objeto de pesquisa, o ecossistema do SPB, é uma experiência inovadora na administração pública, que combina características do modelo de produção de software livre com o conceito de bens públicos e é entregue por um portal que une pessoas e interesses diferentes. O portal do SPB é um espaço virtual para disseminação e aprimoramento de ferramentas de software. Em algumas comunidades acontecem atividades de desenvolvimento de novas funcionalidades ou mesmo de novas versões de ferramentas. Portanto, acontecem processos de desenvolvimento de software, porém ainda sem um processo de qualidade instituído. O desenvolvimento da pesquisa utilizou como referências teóricas frameworks de modelos de maturidade de processos, framework de métodos para construção de modelos, conceitos de sistemas complexos, pensamento sistêmico e ecossistemas digitais. A metodologia de pesquisa utilizada foi a pesquisa-ação e o trabalho de campo teve a duração de dois anos. / This research project addresses the development of a conceptual structure to measure the quality of software production in the digital ecosystem domain, using the action research paradigm. The proposed measurement framework is based on the criteria described in item 5 of ISO / IEC 15504-2 - A Measurement Framework for process capability, with the necessary adaptations to the Public Domain Software (PDS). Development of the structure aims to contribute to the creation of conceptual references for a maturity model for a public software development ecosystem, using the literature on Systems Thinking. The Systems Thinking Approach identified the ecosystem evolves in learning cycles that resulted in a maturity model. It was also observed that the same approach can be used in other ecosystems. The research object is the Brazilian Public Software Ecosystem (BPS), an innovative experience in public administration that combines features of the free software production model with the concept of public goods and is delivered by a portal that links different people and interests. The BPS portal is a virtual space for the development, dissemination and enhancement of software by software communities. These communities engage in activities involving the development of new functionality or even new versions of solutions. Thus they involve software development processes but without a minimum of quality assurance. The theoretical references for the research project ranged from frameworks for process maturity models and frameworks for model construction to concepts of complex systems, systemic thinking and digital ecosystems. The research methodology used was action research and the field work had duration of two years.

Made available in DSpace on 2016-12-23T14:33:34Z (GMT). No. of bitstreams: 1 dissertacao.pdf: 2213112 bytes, checksum: 3a6ab4529d8b828448bf6f9f73340ce8 (MD5) Previous issue date: 2006-10-30 / O movimento de Software Livre tem ganhado cada vez mais espaço e importância nos segmentos da comunidade de software (governo, academia, indústria etc), tanto em âmbito mundial quanto nacional, contando atualmente com a existência de diversos projetos dessa classe em andamento. Esse tipo de software não traz consigo somente inovações na forma de se desenvolver software, mas também proporciona à comunidade uma nova filosofia, afetando muitos dos atuais princípios da indústria de software. Apesar de seu notório crescimento, na maioria das vezes, seu desenvolvimento não tem sido realizado segundo as melhores práticas da Engenharia de Software, incluindo nesse cenário a não utilização de processos de software bem definidos. A elaboração desses processos pode ser facilitada se assistida por normas e modelos de qualidade de processo de software adequados. A aplicação dos processos definidos a uma organização se torna mais viável se auxiliados por um bom ambiente de apoio ao desenvolvimento de software. No caso do desenvolvimento de Software Livre, esse ambiente deve ser composto por ferramentas preferencialmente disponíveis pela Internet, dada a dispersão geográfica dos colaboradores participantes de projetos desse tipo. Este trabalho tem por objetivo definir uma infra-estrutura para apoiar o desenvolvimento de software livre a ser aplicada ao Projeto ODE (Ontology-based software Development Environment), dando origem ao Projeto ODE Livre. O Projeto ODE visa ao desenvolvimento de um Ambiente de Desenvolvimento de Software Centrado em Processos e é o principal projeto em andamento no Laboratório de Engenharia de Software (LabES) da Universidade Federal do Espírito Santo. A infra-estrutura proposta inclui processos padrão para software livre, bem como a definição de requisitos para a construção de um ambiente de apoio aos processos elaborados o Portal ODE Livre. / Free Software is more and more earning space in software market. Nowadays, there are several projects of this kind in progress around the world. This new software development model brings along a new philosophy, affecting many of the software industry principles. Despite of its importance and growth, in most cases, free software development is not being done according to the best practices of Software Engineering. In this scenario, many times software processes are not formally defined. This paper discusses an effort for defining a standard process for free software projects at LabES/UFES. The initial goal of defining these processes is to apply it in ODE´s Project, a project that aims to develop a software engineering environment as a free software The goal of this work is to define an infrastructure to support free software projects at LabES/UFES, which includes standard software processes for open source software projects, as well as the definition of requirements for the development of an environment that is able to support the processes defined. This infrastructure is to be applied to ODE Project, a project that aims to develop the software engineering environment ODE (Ontology-based software Development Environment) as a free software, giving rise to the Free ODE Project. ODE Project aims to develop a Process Centered Software Development Environment and it is the main project in progress in the Software Engineering Laboratory of the Federal University of Espírito Santo (LabES/UFES).

Verification of knowledge-bases is a critical step to ensure the quality of a knowledge-based system. The success of these systems depends heavily on how qualitative the knowledge is. Manual verification is however cumbersome and error prone, especially for large knowledge-bases. This thesis provides a design theory, based upon the suggested framework by Gregor and Jones (2007). The theory proposes a general design of automated verification tools, which have the abilities of verifying heuristic knowledge in rule-based systems utilizing certainty factors. Included is a verification of completeness and consistency technique customized to this class of knowledge-based systems. The design theory is instantiated in a real-world verification tool development project at Uppsala University. Considerable attention is given to the design and implementation of this artifact – uncovering issues and considerations involved in the development process. For the knowledge management practitioner, this thesis offers guidance and recommendations for automated verification tool development projects. For the IS research community, the thesis contributes with extensions of existing design theory, and reveals some of the complexity involved with verification of a specific rule-based system utilizing certainty factors.

軟體產業向來都是腦力密集產業，面對全球化的趨勢，其競爭層次早已不再侷限於國內，而是提升至跨國與跨區域的領域。因此唯有強化競爭力才得以屹立於產業中。 卡內基美隆大學的軟體工學院(Software Engineer Institute, SEI)制定之能力成熟度整合模型(Capability Maturity Model Integration, CMMI)，已成為國際軟體工程中廣泛認同的標準。行政院制定的六年國家展計畫(2002–2008)，其中數位台灣(e–Taiwan)專案中政府更擬定推動民間業者CMMI的計畫,以提升國內軟體開發的素質與強化國際競爭力。 CMMI的導入，無疑是希望從組織面、成本面、品質面等面向全面提升軟體的品質。然而在眾多的導入案例中，學術界對於台灣的軟體企業導入CMMI產生之影響所進行的研究論文相對匱乏。而且國內的資訊軟體業者普遍為中小型機構，是否可以獲得預期的效益也未可知，然在導入的過程卻必須先面臨接踵而來的衝擊。 本文針對已經有成功導入經驗的業者進行研究，藉由研究執行CMMI所衍生的負面衝擊並釐清這些衝擊產生的原因，以協助企業在開始執行之前便能了解其影響，以及相關衝擊產生之原因。讓企業經營階層在執行導入CMMI決策時有更為完整的參考依據，以降低導入CMMI時所衍生出的負面衝擊，進而提升效益。

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