A Study on Architectural Smells Prediction

Francesca Arcelli Fontana; Paris Avgeriou; Ilaria Pigazzini; Riccardo Roveda

doi:10.1109/SEAA.2019.00057

A Study on Architectural Smells Prediction

Francesca Arcelli Fontana, Paris Avgeriou, Ilaria Pigazzini, Riccardo Roveda

Software Engineering

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › Academic › peer-review

10 Citations (Scopus)

157 Downloads (Pure)

Abstract

Architectural smells can be detrimental to the system maintainability, 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 for the prediction four different supervised learning models 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.

Original language	English
Title of host publication	Proceedings - 45th Euromicro Conference on Software Engineering and Advanced Applications, SEAA 2019
Editors	Miroslaw Staron, Rafael Capilla, Amund Skavhaug
Publisher	Institute of Electrical and Electronics Engineers Inc.
Pages	333-337
Number of pages	5
ISBN (Electronic)	978-1-7281-3421-5
ISBN (Print)	978-1-7281-3422-2
DOIs	https://doi.org/10.1109/SEAA.2019.00057
Publication status	Published - Aug-2019
Event	45th Euromicro Conference on Software Engineering and Advanced Applications, SEAA 2019 - Kallithea, Chalkidiki, Greece Duration: 28-Aug-2019 → 30-Aug-2019

Conference

Conference	45th Euromicro Conference on Software Engineering and Advanced Applications, SEAA 2019
Country/Territory	Greece
City	Kallithea, Chalkidiki
Period	28/08/2019 → 30/08/2019

Keywords

Architectural smells prediction and evolution
architectural technical debt

Access to Document

10.1109/SEAA.2019.00057

A Study on Architectural Smells PredictionFinal publisher's version, 98.9 KBLicence: Taverne

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Arcelli Fontana, F., Avgeriou, P., Pigazzini, I., & Roveda, R. (2019). A Study on Architectural Smells Prediction. In M. Staron, R. Capilla, & A. Skavhaug (Eds.), Proceedings - 45th Euromicro Conference on Software Engineering and Advanced Applications, SEAA 2019 (pp. 333-337). Article 8906714 Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/SEAA.2019.00057

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title = "A Study on Architectural Smells Prediction",

abstract = "Architectural smells can be detrimental to the system maintainability, 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 for the prediction four different supervised learning models 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.",

keywords = "Architectural smells prediction and evolution, architectural technical debt",

author = "{Arcelli Fontana}, Francesca and Paris Avgeriou and Ilaria Pigazzini and Riccardo Roveda",

note = "Publisher Copyright: {\textcopyright} 2019 IEEE.; 45th Euromicro Conference on Software Engineering and Advanced Applications, SEAA 2019 ; Conference date: 28-08-2019 Through 30-08-2019",

year = "2019",

month = aug,

doi = "10.1109/SEAA.2019.00057",

language = "English",

isbn = "978-1-7281-3422-2",

pages = "333--337",

editor = "Miroslaw Staron and Rafael Capilla and Amund Skavhaug",

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publisher = "Institute of Electrical and Electronics Engineers Inc.",

}

Arcelli Fontana, F, Avgeriou, P, Pigazzini, I & Roveda, R 2019, A Study on Architectural Smells Prediction. in M Staron, R Capilla & A Skavhaug (eds), Proceedings - 45th Euromicro Conference on Software Engineering and Advanced Applications, SEAA 2019., 8906714, Institute of Electrical and Electronics Engineers Inc., pp. 333-337, 45th Euromicro Conference on Software Engineering and Advanced Applications, SEAA 2019, Kallithea, Chalkidiki, Greece, 28/08/2019. https://doi.org/10.1109/SEAA.2019.00057

A Study on Architectural Smells Prediction. / Arcelli Fontana, Francesca; Avgeriou, Paris; Pigazzini, Ilaria et al.
Proceedings - 45th Euromicro Conference on Software Engineering and Advanced Applications, SEAA 2019. ed. / Miroslaw Staron; Rafael Capilla; Amund Skavhaug. Institute of Electrical and Electronics Engineers Inc., 2019. p. 333-337 8906714.

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › Academic › peer-review

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N2 - Architectural smells can be detrimental to the system maintainability, 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 for the prediction four different supervised learning models 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.

AB - Architectural smells can be detrimental to the system maintainability, 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 for the prediction four different supervised learning models 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.

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A Study on Architectural Smells Prediction

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