ࡱ> -/,bjbjUU B??  r      # /{}}}}}}JN}7  77}  7777  {77{777 P77g07:7:7:7077777777}}77777777:777777777 :Resumo Desenvolver software uma atividade complexa e com riscos envolvidos. Muitos dos riscos existentes tem associao com requisitos volteis. Tal volatilidade motivou a criao e a adoo de metodologias geis e hbridas, que hoje so uma realidade nas organizaes. Porm, a volatilidade dos requisitos tambm pode ser encontrada na pesquisa cientfica, que cada vez mais depende de complexas simulaes computacionais. Um dos problemas que ocorriam no sculo passado era a capacidade de coletar dados para os experimentos, com o avano da computao este problema foi em sua grande parte resolvido. Porm a resoluo deste problema ocasiona na mudana da forma de trabalho dos cientistas, necessitando de equipes maiores para o processamento e a anlise destes dados. Esta mudana no foi acompanhado na forma como os cientistas gerenciam o processo de experimentao cientfico tornando um ambiente catico. Requisitos so instveis e mudam constantemente durante a execuo do projeto e sua complexidade exige muito esforo para a compreenso do domnio da pesquisa. Esta dissertao apresenta uma abordagem, denominada SciAgile, que aplica uma srie de prticas de diferentes metodologias geis no ciclo de vida do experimento cientfico baseado em simulao. SciAgile foca justamente na gerncia de um ambiente catico, onde visa responder s mudanas rpidas que os requisitos possam vir a sofrer e ampliar a comunicao da equipe para disseminar o conhecimento mais facilmente. Dessa forma, o ciclo de vida do experimento cientfico se torna orientado a um conjunto de prticas que fornecem a base para melhoria do processo de experimentao cientfica. Para avaliar a proposta, foi realizado um estudo experimental com dois workflows cientficos de referncia da rea de experimentos in silico. Resultados fornecem indcios que a adoo de prticas de metodologias geis capaz de melhorar o processo de experimentao cientfica. Palavras-chave: Metodologias geis, Experimento Cientfico, Workflows Cientficos. Abstract Developing sofware is a complex activity with risks involved. Many of the risks have an association with volatile requirements. Such volatility motivated the creation and adoption of agile and hybrid methodologies, which are now a reality in organizations. However, the volatility of requirements can also be found in scientific research, which increasingly depends on complex computational simulations. One of the problems that occurred in the last century was the ability to collect data for experiments, with the advancement of computing this problem was in its large part solved. However, the resolution of this problem leads to a change in the way of working of scientists, requiring larger teams to process and analyze this data. This change has not been followed by the way scientists manage the process of experimentation, creating a chaotic environment. Requirements are unstable and change constantly during execution of the project and its complexity requires a lot of effort to understand the research domain. This dissertation presents an approach, called SciAgile, which applies a series of different agile methodologies in the life cycle of the simulation-based scientific experiment. SciAgile focuses on the management of a chaotic environment, where it aims to respond to the rapid changes requirements may come to suffer and to broaden the communication of the team to disseminate the changes easily. In this way, the life cycle of the scientific experiment becomes oriented to a set of practices that provide the basis for improving the process of scientific experimentation. To evaluate the proposed approach, we conducted an experimental study with two reference scientific workflows of the area of in-silico experimentation. Results provide indications that the adoption of agile methodologies practices are capable of improving the process of scientific experimentation. Keywords: Agile Methods. Cientific Experiment. Cientific workflows. hLe5 ( _` @P182P:pb. 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