A multi-label classification approach for detecting test smells over java projects

Author:

Hadj-Kacem Mouna,Bouassida Nadia

Publisher

Elsevier BV

Subject

General Computer Science

Reference37 articles.

1. Test smell detection tools: a systematic mapping study;Aljedaani;Evaluation and Assessment in Software Engineering, Association for Computing Machinery,2021

2. Comparing and experimenting machine learning techniques for code smell detection;Arcelli;Empir. Software Eng.,2016

3. An empirical analysis of the distribution of unit test smells and their impact on software maintenance;Bavota;International Conference on Software Maintenance, IEEE,2012

4. Are test smells really harmful? An empirical study;Bavota;Empir. Software Eng.,2015

5. Bladel, B.V., Demeyer, S., 2018. Test behaviour detection as a test refactoring safety, in: International Workshop on Refactoring, pp. 22–25.

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2. The Lost World: Characterizing and Detecting Undiscovered Test Smells;ACM Transactions on Software Engineering and Methodology;2023-11-20

3. On the diffusion of test smells and their relationship with test code quality of Java projects;Journal of Software: Evolution and Process;2023-01-18

4. Detecting and Refactoring Feature Envy Based on Graph Neural Network;2022 IEEE 33rd International Symposium on Software Reliability Engineering (ISSRE);2022-10

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