STONE: Um Processo de Gerência de Configuração de Software para Projetos Acadêmicos

Abstract

Software Configuration Management (SCM) is a subarea of Software Engineering that is fundamental to the control of all changes that occur within a project. Although its application has many benefits, such as faster problem correction, its use is not encouraged in projects developed by students during their university period. Lacking a predefined process that supports SCM, these developed projects are often delivered on time, their artifacts become inconsistent, meaning that somehow the execution of project activities leaves points to be desired. Many models, such as MPS-BR, PMBoK, and CMMI have their own definition of the Configuration Management process, however, their practical application, usually performed in the industry, requires skilled labor and a robust infrastructure to support the SCM activities, making it difficult to use in the academic context. Although some SCM practices have been applied at an academic level, such as the implementation of a version control tool for student-produced projects, it has not been found in the literature, papers that proposed a specific solution to the problems caused by the lack of SCM in projects. of software developed in an academic environment. In this context, this paper presents a SCM process focused on academic projects, in order to help students control changes and, consequently, avoid certain types of problems that may arise. The defined process was based on good practices from MPS-BR, ISO 10007 and other works published in the area. Subsequently, a survey was conducted through questionnaires with undergraduate students of the Computer course and related areas to identify their main difficulties and validate some activities of the process. With this information collected, changes were made in the process, so that it suits the needs pointed out by the students. An experiment was performed to evaluate the use of two tools during the execution of the Change Control phase of the STONE process. The resulting data were collected and interpreted so that the process could be improved.