Architectural smells can be detrimental to system maintainability and evolvability, and represent a source of architectural debt. Thus, it is very important to be able to understand how they evolved in the past and to predict their future evolution. In this paper, we evaluate if the existence of architectural smells in the past versions of a project can be used to predict their presence in the future. We analyzed four Java projects in 295 Github releases and we applied four different supervised learning models for the prediction in a repeated cross-validation setting. We found that historical architectural smell information can be used to predict the presence of architectural smells in the future. Hence, practitioners should carefully monitor the evolution of architectural smells and take preventative actions to avoid introducing them and stave off their progressive growth.

Arcelli Fontana, F., Avgeriou, P., Pigazzini, I., Roveda, R. (2019). A Study on Architectural Smells Prediction. In Proceedings - 45th Euromicro Conference on Software Engineering and Advanced Applications, SEAA 2019 (pp.333-337). Institute of Electrical and Electronics Engineers Inc. [10.1109/SEAA.2019.00057].

A Study on Architectural Smells Prediction

Arcelli Fontana, F
;
Pigazzini, I
;
Roveda, R
2019

Abstract

Architectural smells can be detrimental to system maintainability and evolvability, and represent a source of architectural debt. Thus, it is very important to be able to understand how they evolved in the past and to predict their future evolution. In this paper, we evaluate if the existence of architectural smells in the past versions of a project can be used to predict their presence in the future. We analyzed four Java projects in 295 Github releases and we applied four different supervised learning models for the prediction in a repeated cross-validation setting. We found that historical architectural smell information can be used to predict the presence of architectural smells in the future. Hence, practitioners should carefully monitor the evolution of architectural smells and take preventative actions to avoid introducing them and stave off their progressive growth.
Si
paper
Architectural smells prediction and evolution, architectural technical debt
English
Euromicro Conference Series on Software Engineering and Advanced Applications (SEAA) AUG 28-30
978-172813285-3
Arcelli Fontana, F., Avgeriou, P., Pigazzini, I., Roveda, R. (2019). A Study on Architectural Smells Prediction. In Proceedings - 45th Euromicro Conference on Software Engineering and Advanced Applications, SEAA 2019 (pp.333-337). Institute of Electrical and Electronics Engineers Inc. [10.1109/SEAA.2019.00057].
Arcelli Fontana, F; Avgeriou, P; Pigazzini, I; Roveda, R
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/10281/242857
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