Um estudo exploratório a partir de um framework para seleção de práticas ágeis

Dissertação (mestrado) - Universidade Federal de Santa Catarina, Centro Tecnológico. Programa de Pós-Graduação em Ciência da ComputaçãoO principal objetivo dos métodos ágeis existentes é promover o desenvolvimento eficiente de software através de práticas que priorizam a comunicação com o cliente e entregas frequentes. Cada método ágil apresenta um conjunto próprio de práticas. Com esta diversidade de práticas torna-se interessante a construção de novos processos ágeis que contemplem apenas as práticas mais adequadas a partir destes métodos. O problema, entretanto, é que a combinação de práticas de diferentes métodos ágeis não garante, necessariamente, que o novo processo definido seja ágil. Este trabalho avalia a agilidade do conjunto de práticas de um framework de práticas ágeis e busca identificar quais práticas apresentam maior harmonia quando usadas no mesmo processo. A agilidade das práticas é avaliada através dos dados de uma grande pesquisa de opinião online e a harmonia entre elas é identificada através da técnica de análise de agrupamentos. Os melhores resultados foram apresentados pelas práticas de Integração contínua, Desenvolvimento lado a lado e Testes de aceitação. A análise de agrupamentos, por sua vez, formou quatro grupos de práticas: o primeiro formado por Projeto da arquitetura do sistema e Lista de requisitos; o segundo por Desenvolvimento coletivo de código, Integração contínua, Refatoração e Testes de aceitação; o terceiro por Projeto da iteração e Modelagem geral; e o quarto por Desenvolvimento lado a lado e Reuniões diárias.The main objective of agile methods is to promote efficient software development through practices that prioritize communication with the client and frequent deliveries. Each agile method presents its unique set of practices. This diversity of practices may lead to the definition of new agile processes that include only the more appropriate practices from these methods. The problem, however, is that combining practices from different methods does not guarantee that the resulting process can be considered agile. This work assesses the agility of a set of practices of a framework for selecting agile practices and seeks to identify which practices provide more harmony when used in the same process. The agility of the practices is evaluated using data from a large online survey and the harmony between them is identified by the technique of cluster analysis. The best results were presented by the practices of Continuous integration, Side by side development and Acceptance tests. The cluster analysis resulted in four practice groups: the first with System architectural design and Requirements list; the second with Collective code ownership, Continuous integration, Refactoring and Acceptance tests; the third with Iteration design and General modeling; and the fourth with Side by side development and Daily meetings

Hybrid Fuzzy-Bayesian Dynamic Decision Support Tool for Resource-Based Scheduling of Construction Projects

Title from PDF of title page viewed September 7, 2017Dissertation advisor: Ceki HalmenVitaIncludes bibliographical references (pages 153-165)Thesis (Ph.D.)--School of Computing and Engineering and Bloch School of Management. University of Missouri--Kansas City, 2017This dissertation proposes a flexible and intelligent decision support tool for scheduling and resource allocation of construction projects. A hybrid Fuzzy-Bayesian scheduling network and a new optimization model and solution approach have been developed to assess the combinatory effect of different risk factors on scheduling and optimize the time-cost tradeoff. Developed decision support tool employs interval-valued fuzzy numbers and Bayesian networks to dynamically quantify uncertainty and predict project performance during its make span. Using interval-valued fuzzy numbers makes the model more flexible and intelligent comparing to conventional fuzzy risk assessment models through incorporating the decision makers` confidence degree. The linguistic assessments of experts regarding the likelihood and severity of increase or decrease in task duration and cost when influenced by different risk factors are used to generate a set of duration and cost prior-probability distributions. A learning dynamic Bayesian scheduling network is developed to probabilistically combine the prior-probability distributions with initial activity duration estimates and update them as new evidence in form of actual activity data feed into the network. This model also predicts project performance at any point of time during its execution. Optimization model explicitly considers variation of time-cost tradeoff relationship during project execution and complex payment terms to maximize the project net present value (NPV). A sequential solution approach is proposed to combine a procedure for updating time-cost tradeoff data, and mixed integer linear programming (MILP) methods to obtain optimal project crashing and scheduling solutions that is adaptive to the current project status and crew productivity. Capability of proposed model in quantifying uncertainty at initial phases of project where project performance data are scarce, learning from data and predicting project performance, considering financial aspects of scheduling through optimal resource allocation and providing useful and clear advice to managers are advantages of developed decision support tool over already existing approaches.Introduction -- Literature review -- Methodology -- Case study and model validation -- Conclusion and recommendations -- Appendix. Detailed Fuzzy Weighted Average Calculations for a-cut = 0 Based on the Max-Min Paired Elimination Algorit

Analyse der Wirkung von Nutzer-Feedback auf die Entwicklungszeit komplexer Softwareprodukte

In der Softwareentwicklung verursacht der Entwicklungsaufwand, und die damit zusammenhängende Entwicklungsdauer, i. A. einen Großteil der Produktionskosten. In einem unsicheren, dynamischen Umfeld hat die Überarbeitungsdauer einen großen Anteil an der Entwicklungszeit. Ziel dieser Arbeit ist es die Struktur inkrementeller Softwareentwicklungsprozesse, die wiederholtes (zyklisches) Feedback erlauben, zu untersuchen. Darauf basierend werden Modelle entwickelt, anhand derer die Wirkungszusammenhänge der Einflussfaktoren der Entwicklungsdauer dieser Prozesse, wie Unsicherheit und Komplexität, analysiert und Empfehlungen zur Reduzierung der Entwicklungsdauer gegeben werden können