Trend Application of Machine Learning in Test Case Prioritization: A Review on Techniques
Software quality can be assured by passing the process of software testing. However, software testing process involve many phases which lead to more resources and time consumption. To reduce these downsides, one of the approaches is to adopt test case prioritization (TCP) where numerous works has in...
| Main Authors: | , , , , , , |
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| Format: | Article |
| Language: | English |
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IEEE
2021-01-01
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| Series: | IEEE Access |
| Subjects: | |
| Online Access: | https://ieeexplore.ieee.org/document/9650902/ |
| _version_ | 1798003357005119488 |
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| author | Muhammad Khatibsyarbini Mohd Adham Isa Dayang N. A. Jawawi Muhammad Luqman Mohd Shafie Wan Mohd Nasir Wan-Kadir Haza Nuzly Abdull Hamed Muhammad Dhiauddin Mohamed Suffian |
| author_facet | Muhammad Khatibsyarbini Mohd Adham Isa Dayang N. A. Jawawi Muhammad Luqman Mohd Shafie Wan Mohd Nasir Wan-Kadir Haza Nuzly Abdull Hamed Muhammad Dhiauddin Mohamed Suffian |
| author_sort | Muhammad Khatibsyarbini |
| collection | DOAJ |
| description | Software quality can be assured by passing the process of software testing. However, software testing process involve many phases which lead to more resources and time consumption. To reduce these downsides, one of the approaches is to adopt test case prioritization (TCP) where numerous works has indicated that TCP do improve the overall software testing performance. TCP does have several kinds of techniques which have their own strengths and weaknesses. As for this review paper, the main objective of this paper is to examine deeper on machine learning (ML) techniques based on research questions created. The research method for this paper was designed in parallel with the research questions. Consequently, 110 primary studies were selected where, 58 were journal articles, 50 were conference papers and 2 considered as others articles. For overall result, it can be said that ML techniques in TCP has trending in recent years yet some improvements are certainly welcomed. There are multiple ML techniques available, in which each technique has specified potential values, advantages, and limitation. It is notable that ML techniques has been considerably discussed in TCP approach for software testing. |
| first_indexed | 2024-04-11T12:06:06Z |
| format | Article |
| id | doaj.art-7dba2a4b639343e3bf5746cb7e669f5d |
| institution | Directory Open Access Journal |
| issn | 2169-3536 |
| language | English |
| last_indexed | 2024-04-11T12:06:06Z |
| publishDate | 2021-01-01 |
| publisher | IEEE |
| record_format | Article |
| series | IEEE Access |
| spelling | doaj.art-7dba2a4b639343e3bf5746cb7e669f5d2022-12-22T04:24:43ZengIEEEIEEE Access2169-35362021-01-01916626216628210.1109/ACCESS.2021.31355089650902Trend Application of Machine Learning in Test Case Prioritization: A Review on TechniquesMuhammad Khatibsyarbini0https://orcid.org/0000-0001-6839-1755Mohd Adham Isa1https://orcid.org/0000-0002-0049-8510Dayang N. A. Jawawi2https://orcid.org/0000-0001-8300-8523Muhammad Luqman Mohd Shafie3Wan Mohd Nasir Wan-Kadir4https://orcid.org/0000-0003-4459-4050Haza Nuzly Abdull Hamed5https://orcid.org/0000-0001-8619-4149Muhammad Dhiauddin Mohamed Suffian6https://orcid.org/0000-0001-9309-7718Faculty of Engineering, School of Computing, Universiti Teknologi Malaysia, Johor Bahru, Johor, MalaysiaFaculty of Engineering, School of Computing, Universiti Teknologi Malaysia, Johor Bahru, Johor, MalaysiaFaculty of Engineering, School of Computing, Universiti Teknologi Malaysia, Johor Bahru, Johor, MalaysiaFaculty of Engineering, School of Computing, Universiti Teknologi Malaysia, Johor Bahru, Johor, MalaysiaFaculty of Engineering, School of Computing, Universiti Teknologi Malaysia, Johor Bahru, Johor, MalaysiaFaculty of Engineering, School of Computing, Universiti Teknologi Malaysia, Johor Bahru, Johor, MalaysiaBusiness Solution and Services, MIMOS Technology Solutions Sdn. Bhd., Kuala Lumpur, MalaysiaSoftware quality can be assured by passing the process of software testing. However, software testing process involve many phases which lead to more resources and time consumption. To reduce these downsides, one of the approaches is to adopt test case prioritization (TCP) where numerous works has indicated that TCP do improve the overall software testing performance. TCP does have several kinds of techniques which have their own strengths and weaknesses. As for this review paper, the main objective of this paper is to examine deeper on machine learning (ML) techniques based on research questions created. The research method for this paper was designed in parallel with the research questions. Consequently, 110 primary studies were selected where, 58 were journal articles, 50 were conference papers and 2 considered as others articles. For overall result, it can be said that ML techniques in TCP has trending in recent years yet some improvements are certainly welcomed. There are multiple ML techniques available, in which each technique has specified potential values, advantages, and limitation. It is notable that ML techniques has been considerably discussed in TCP approach for software testing.https://ieeexplore.ieee.org/document/9650902/Machine learningsoftware engineeringsoftware testingsystematic literature reviewtest case prioritization |
| spellingShingle | Muhammad Khatibsyarbini Mohd Adham Isa Dayang N. A. Jawawi Muhammad Luqman Mohd Shafie Wan Mohd Nasir Wan-Kadir Haza Nuzly Abdull Hamed Muhammad Dhiauddin Mohamed Suffian Trend Application of Machine Learning in Test Case Prioritization: A Review on Techniques IEEE Access Machine learning software engineering software testing systematic literature review test case prioritization |
| title | Trend Application of Machine Learning in Test Case Prioritization: A Review on Techniques |
| title_full | Trend Application of Machine Learning in Test Case Prioritization: A Review on Techniques |
| title_fullStr | Trend Application of Machine Learning in Test Case Prioritization: A Review on Techniques |
| title_full_unstemmed | Trend Application of Machine Learning in Test Case Prioritization: A Review on Techniques |
| title_short | Trend Application of Machine Learning in Test Case Prioritization: A Review on Techniques |
| title_sort | trend application of machine learning in test case prioritization a review on techniques |
| topic | Machine learning software engineering software testing systematic literature review test case prioritization |
| url | https://ieeexplore.ieee.org/document/9650902/ |
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