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On The Relation of Test Smells to Software Code Quality. / Spadini, Davide; Palomba, Fabio; Zaidman, Andy; Bruntink, Magiel; Bacchelli, Alberto.

Proceedings - 2018 IEEE International Conference on Software Maintenance and Evolution, ICSME 2018. Los Alamitos, CA : IEEE, 2018. p. 12-23.

Research output: Chapter in Book/Report/Conference proceedingConference contributionScientificpeer-review

Harvard

Spadini, D, Palomba, F, Zaidman, A, Bruntink, M & Bacchelli, A 2018, On The Relation of Test Smells to Software Code Quality. in Proceedings - 2018 IEEE International Conference on Software Maintenance and Evolution, ICSME 2018. IEEE, Los Alamitos, CA, pp. 12-23, ICSME 2018, Madrid, Spain, 23/09/18. https://doi.org/10.1109/ICSME.2018.00010

APA

Spadini, D., Palomba, F., Zaidman, A., Bruntink, M., & Bacchelli, A. (2018). On The Relation of Test Smells to Software Code Quality. In Proceedings - 2018 IEEE International Conference on Software Maintenance and Evolution, ICSME 2018 (pp. 12-23). Los Alamitos, CA: IEEE. https://doi.org/10.1109/ICSME.2018.00010

Vancouver

Spadini D, Palomba F, Zaidman A, Bruntink M, Bacchelli A. On The Relation of Test Smells to Software Code Quality. In Proceedings - 2018 IEEE International Conference on Software Maintenance and Evolution, ICSME 2018. Los Alamitos, CA: IEEE. 2018. p. 12-23 https://doi.org/10.1109/ICSME.2018.00010

Author

Spadini, Davide ; Palomba, Fabio ; Zaidman, Andy ; Bruntink, Magiel ; Bacchelli, Alberto. / On The Relation of Test Smells to Software Code Quality. Proceedings - 2018 IEEE International Conference on Software Maintenance and Evolution, ICSME 2018. Los Alamitos, CA : IEEE, 2018. pp. 12-23

BibTeX

@inproceedings{4555186f113c45c08b06fb106295ae8e,
title = "On The Relation of Test Smells to Software Code Quality",
abstract = "Test smells are sub-optimal design choices in the implementation of test code. As reported by recent studies, their presence might not only negatively affect the comprehension of test suites but can also lead to test cases being less effective in finding bugs in production code. Although significant steps toward understanding test smells, there is still a notable absence of studies assessing their association with software quality.In this paper, we investigate the relationship between the presence of test smells and the change- and defect-proneness of test code, as well as the defect-proneness of the tested production code. To this aim, we collect data on 221 releases of ten software systems and we analyze more than a million test cases to investigate the association of six test smells and their co-occurrence with software quality. Key results of our study include:(i) tests with smells are more change- and defect-prone, (ii) ‘Indirect Testing’, ‘Eager Test’, and ‘Assertion Roulette’ are the most significant smells for change-proneness and, (iii) production code is more defect-prone when tested by smelly tests.",
keywords = "test smells, code quality, automated testing",
author = "Davide Spadini and Fabio Palomba and Andy Zaidman and Magiel Bruntink and Alberto Bacchelli",
year = "2018",
doi = "10.1109/ICSME.2018.00010",
language = "English",
pages = "12--23",
booktitle = "Proceedings - 2018 IEEE International Conference on Software Maintenance and Evolution, ICSME 2018",
publisher = "IEEE",
address = "United States",

}

RIS

TY - GEN

T1 - On The Relation of Test Smells to Software Code Quality

AU - Spadini, Davide

AU - Palomba, Fabio

AU - Zaidman, Andy

AU - Bruntink, Magiel

AU - Bacchelli, Alberto

PY - 2018

Y1 - 2018

N2 - Test smells are sub-optimal design choices in the implementation of test code. As reported by recent studies, their presence might not only negatively affect the comprehension of test suites but can also lead to test cases being less effective in finding bugs in production code. Although significant steps toward understanding test smells, there is still a notable absence of studies assessing their association with software quality.In this paper, we investigate the relationship between the presence of test smells and the change- and defect-proneness of test code, as well as the defect-proneness of the tested production code. To this aim, we collect data on 221 releases of ten software systems and we analyze more than a million test cases to investigate the association of six test smells and their co-occurrence with software quality. Key results of our study include:(i) tests with smells are more change- and defect-prone, (ii) ‘Indirect Testing’, ‘Eager Test’, and ‘Assertion Roulette’ are the most significant smells for change-proneness and, (iii) production code is more defect-prone when tested by smelly tests.

AB - Test smells are sub-optimal design choices in the implementation of test code. As reported by recent studies, their presence might not only negatively affect the comprehension of test suites but can also lead to test cases being less effective in finding bugs in production code. Although significant steps toward understanding test smells, there is still a notable absence of studies assessing their association with software quality.In this paper, we investigate the relationship between the presence of test smells and the change- and defect-proneness of test code, as well as the defect-proneness of the tested production code. To this aim, we collect data on 221 releases of ten software systems and we analyze more than a million test cases to investigate the association of six test smells and their co-occurrence with software quality. Key results of our study include:(i) tests with smells are more change- and defect-prone, (ii) ‘Indirect Testing’, ‘Eager Test’, and ‘Assertion Roulette’ are the most significant smells for change-proneness and, (iii) production code is more defect-prone when tested by smelly tests.

KW - test smells

KW - code quality

KW - automated testing

U2 - 10.1109/ICSME.2018.00010

DO - 10.1109/ICSME.2018.00010

M3 - Conference contribution

SP - 12

EP - 23

BT - Proceedings - 2018 IEEE International Conference on Software Maintenance and Evolution, ICSME 2018

PB - IEEE

CY - Los Alamitos, CA

ER -

ID: 45599699