On the relation between architectural smells and source code changes
Author:
Affiliation:
1. Bernoulli Institute for Mathematics, Computer Science, and Artificial Intelligence University of Groningen Groningen The Netherlands
2. Department of Informatics, Systems, and Communications University of Milano‐Bicocca Milan Italy
Funder
Horizon 2020 Framework Programme
Rijksdienst voor Ondernemend Nederland
Publisher
Wiley
Subject
Software
Link
https://onlinelibrary.wiley.com/doi/pdf/10.1002/smr.2398
Reference38 articles.
1. GarciaJ PopescuD EdwardsG MedvidovicN.Identifying architectural bad smells. In: 2009 13th Proceedings of the European Conference on Software Maintenance and Reengineering CSMR;2009;Kaiserslautern Germany:255‐258.
2. Managing technical debt in software engineering (Dagstuhl Seminar 16162);Avgeriou P;Dagstuhl Rep,2016
3. VerdecchiaR MalavoltaI LagoP. Architectural technical debt identification: the research landscape. In: 2018 ACM/IEEE International Conference on Technical Debt. Gothenburg Sweden; 2018:11‐20.http://www.ivanomalavolta.com/files/papers/TechDebt_2018.pdf
4. FontanaFA PigazziniI RovedaR ZanoniM.Automatic detection of instability architectural smells. In: Proceedings ‐ 2016 IEEE International Conference on Software Maintenance and Evolution ICSME 2016;2016;Raleigh NC USA:433‐437.
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