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Empirical evaluation of software maintainability based on a manually validated refactoring dataset

  • Published:2018-03 Issue: Volume:95 Page:313-327
  • ISSN:0950-5849
  • Container-title:Information and Software Technology
  • language:en
  • Short-container-title:Information and Software Technology

Author:

Hegedűs Péter,Kádár István,Ferenc Rudolf,Gyimóthy Tibor

Funder

Ministry of Human Capacities

Publisher

Elsevier BV

Subject

Computer Science Applications,Information Systems,Software

Reference54 articles.

1. Refactoring: Improving the Design of Existing Code;Fowler,1999

2. Java quality assurance by detecting code smells;van Emden,2002

3. Impact of refactoring on quality code evaluation;Fontana,2011

4. An exploratory study of the impact of code smells on software change-proneness;Khomh,2009

5. A taxonomy and an initial empirical study of bad smells in code;Mantyla,2003

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1. REARRANGE: Effort estimation approach for software clustering-based remodularisation;Information and Software Technology;2024-12

2. Revealing MOVE METHOD: Machine Learning-driven Real-time Refactoring Identification for Enhanced Software Quality;2024 International Conference on Emerging Systems and Intelligent Computing (ESIC);2024-02-09

3. Handling Imbalanced Datasets in Software Refactoring Prediction;Communications in Computer and Information Science;2024

4. Software Maintainability and Refactorings Prediction Based on Technical Debt Issues;Studia Universitatis Babeș-Bolyai Informatica;2023-12-22

5. A Survey of Refactoring Techniques to Maximize Code Coverage Metric;2023 15th International Congress on Advanced Applied Informatics Winter (IIAI-AAI-Winter);2023-12-11
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