LIMA, T. N.; http://lattes.cnpq.br/9053103503054879; LIMA, Thiago Nascimento de.
Résumé:
Bug ixing is a natural step in the life cycle of a software, from development
to the user interaction phase, problems will arise. Users,
in general, report these problems through reports, however it is
common that the information in these reports is incomplete or poorly
structured. Among this information, the steps for reproduction
elucidate the sequence of actions that reproduce the error and are
considered as one of the most important information in the report.
However, it is common that such information is not present or is
present in an unstructured way, making it diicult, for example,
for the developer to ind the problem and generate automatic tests.
Thus, an application is necessary to identify and structure the steps
to reproduce a bug by extracting information from the body of the
text of the reports, in order to provide data that can be used in the
most diverse applications. This project proposes the development
of machine learning models based on Natural Language Processing
with the ability to identify and structure the steps for reproduction.
In which, high eiciency was evidenced in the detection of reproduction
steps in a report (F1 = 0.69), but low capacity to promote
the structuring of report components, such as actors and actions.
