Several studies are focused on the study of code smells and many detection techniques have been proposed. In this scenario, the use of rules involving software-metrics has been widely used in refactoring tools as a mechanism to detect code smells automatically. However, actual approaches present two unsatisfactory aspects: they present a low agreement in its results and, they do not consider the developers' feedback. In this way, these approaches detect smells that are not relevant to the developers. In order to solve the above mentioned unsatisfactory aspects in the state-of theart of code smells detection, we propose the Smell Platform able to recognize code smells more relevant to developers by using its feedback. In this paper we present how such platform is able to detect four well known code smells. Finally, we evaluate the Smell Platform comparing its results with traditional detection techniques.
In software engineering, Software Configuration Management is a set of support activities that allows for the orderly absorption of changes inherent to software development. For that, organization models for code versioning like Gitflow have been proposed. In Gitflow, two fixed branches (master and develop) are used to store the project history and be the starting point for changes. Despite the popularity of Gitflow for being considered a simple workflow, there are few: (a) reports of its use in practice and / or (b) documentation on how to deploy it in a real environment. This paper presents the process of adapting Gitflow and creating rules for its application in a real software development project. This adaptation took into account the opinions of managers and developers of a team of approximately 30 people within an agile Scrum life cycle. As a result, definitions and documents were generated to keep track of development, in addition to defining the necessary steps for its application considering the development process adopted by the team.
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