Code smells as system-level indicators of maintainability: An empirical study

Journal of Systems and Software ◽

10.1016/j.jss.2013.05.007 ◽

2013 ◽

Vol 86 (10) ◽

pp. 2639-2653 ◽

Author(s):

Aiko Yamashita ◽

Steve Counsell

Keyword(s):

Empirical Study ◽

System Level ◽

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Empirical study on code smells in iOS applications

Proceedings of the IEEE/ACM 7th International Conference on Mobile Software Engineering and Systems ◽

10.1145/3387905.3388597 ◽

2020 ◽

Author(s):

Kristiina Rahkema ◽

Dietmar Pfahl

Keyword(s):

Empirical Study ◽

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On the Effectiveness of Concern Metrics to Detect Code Smells: An Empirical Study

Advanced Information Systems Engineering - Lecture Notes in Computer Science ◽

10.1007/978-3-319-07881-6_44 ◽

2014 ◽

pp. 656-671 ◽

Author(s):

Juliana Padilha ◽

Juliana Pereira ◽

Eduardo Figueiredo ◽

Jussara Almeida ◽

Alessandro Garcia ◽

...

Keyword(s):

Empirical Study ◽

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On the Influence of Human Factors for Identifying Code Smells: A Multi-Trial Empirical Study

2017 ACM/IEEE International Symposium on Empirical Software Engineering and Measurement (ESEM) ◽

10.1109/esem.2017.13 ◽

2017 ◽

Author(s):

Rafael Maiani de Mello ◽

Roberto Oliveira ◽

Alessandro Garcia

Keyword(s):

Empirical Study ◽

Human Factors ◽

Code Smells ◽

Identifying Code

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Empirical Study about Class Change Proneness Prediction using Software Metrics and Code Smells

Proceedings of the 22nd International Conference on Enterprise Information Systems ◽

10.5220/0009410601400147 ◽

2020 ◽

Author(s):

Antonio Martins ◽

Cristiano Melo ◽

José Monteiro ◽

Javam Machado

Keyword(s):

Empirical Study ◽

Software Metrics ◽

Code Smells ◽

Change Proneness

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A large-scale empirical study of code smells in JavaScript projects

Software Quality Journal ◽

10.1007/s11219-019-09442-9 ◽

2019 ◽

Vol 27 (3) ◽

pp. 1271-1314 ◽

Author(s):

David Johannes ◽

Foutse Khomh ◽

Giuliano Antoniol

Keyword(s):

Empirical Study ◽

Large Scale ◽

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An empirical study of code smells in JavaScript projects

2017 IEEE 24th International Conference on Software Analysis, Evolution and Reengineering (SANER) ◽

10.1109/saner.2017.7884630 ◽

2017 ◽

Author(s):

Amir Saboury ◽

Pooya Musavi ◽

Foutse Khomh ◽

Giulio Antoniol

Keyword(s):

Empirical Study ◽

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An Empirical Study on System Level Aspects of Internet of Things (IoT)

IEEE Access ◽

10.1109/access.2020.3029847 ◽

2020 ◽

Vol 8 ◽

pp. 188082-188134

Author(s):

S. Narasimha Swamy ◽

Solomon Raju Kota

Keyword(s):

Internet Of Things ◽

Empirical Study ◽

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Investigating the Impact of Code Smells on System's Quality: An Empirical Study on Systems of Different Application Domains

2013 IEEE International Conference on Software Maintenance ◽

10.1109/icsm.2013.37 ◽

2013 ◽

Author(s):

Francesca Arcelli Fontana ◽

Vincenzo Ferme ◽

Alessandro Marino ◽

Bartosz Walter ◽

Pawel Martenka

Keyword(s):

Empirical Study ◽

Code Smells ◽

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Assessing the capability of code smells to explain maintenance problems: an empirical study combining quantitative and qualitative data

Empirical Software Engineering ◽

10.1007/s10664-013-9250-3 ◽

2013 ◽

Vol 19 (4) ◽

pp. 1111-1143 ◽

Author(s):

Aiko Yamashita

Keyword(s):

Empirical Study ◽

Qualitative Data ◽

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Empirical study on the influencing factors and improvement of public service productivity at system level

2014 11th International Conference on Service Systems and Service Management (ICSSSM) ◽

10.1109/icsssm.2014.6943344 ◽

2014 ◽

Author(s):

Yang Dan

Keyword(s):

Empirical Study ◽

Influencing Factors ◽

Public Service ◽

System Level ◽

Service Productivity

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