A Semiautomatic Approach to Identify Architectural Technical Debt from Heterogeneous Artifacts
Architectural Technical Debt (ATD) is a metaphor used to describe decisions taken by software architects to accomplish short-term goals but possibly negatively affecting the long-term health of the system. However, ATD doesn’t receive enough attention for the architect teams because it is hard to identify, to measure, to prioritize, and its value is related to long-term maintenance and evolution of a system. In this Ph.D. research, we propose a model-driven approach that focuses on building a binary classification model for ATD identification based on the information gathered from artifacts produced during architecture design. This model will allow software architects to support the managing of conscious and unconscious ATD in their software projects. This proposal focuses on TD at the architecture-level only without considering source code. The effectiveness of this proposal will be evaluated using case studies and expert interviews.
Fri 18 SepDisplayed time zone: Amsterdam, Berlin, Bern, Rome, Stockholm, Vienna change
16:10 - 16:50
|Does BERT understand code? - An exploratory study on the detection of architectural tactics in codeshort-paperResearch Track
|A Semiautomatic Approach to Identify Architectural Technical Debt from Heterogeneous ArtifactsDoctoral Symposium
Boris Rainiero Perez Gutierrez University of Los Andes, Colombia