Abstract
Background. Companies frequently try to improve the quality of their software by resolving technical issues that are perceived to have an impact on software quality. Technical information is any information that may be gathered from the source code or the software development process, for instance: code or documentation guidelines, and the use of specific patterns. If these issues are not fixed they may generate technical debt. Goal. The goal of the Ph.D., which started on January 2022, is to understand which are the causes of Architectural Technical Debt in a real case study and to develop a Dashboard to notify developers as earlier as possible. Methods and expected contribution. We first plan to investigate the actual production code process and then, and then to work with teams to find the best practices and strategies to easily manage Architectural Technical Debt.
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CITATION STYLE
Amoroso d’Aragona, D. (2022). Architectural Degradation and Technical Debt Dashboards. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 13709 LNCS, pp. 638–643). Springer Science and Business Media Deutschland GmbH. https://doi.org/10.1007/978-3-031-21388-5_49
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