TS-Detector : Detecting Feature Toggle Usage Patterns
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arXiv
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| Main Authors: | , , , |
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| Format: | Preprint |
| Published: |
2025
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| _version_ | 1866916726625533952 |
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| author | Rahman, Tajmilur Fei, Mengzhe Sharma, Tushar Roy, Chanchal |
| author_facet | Rahman, Tajmilur Fei, Mengzhe Sharma, Tushar Roy, Chanchal |
| contents | Feature toggles enable developers to control feature states, allowing the features to be released to a limited group of users while preserving overall software functionality. The absence of comprehensive best practices for feature toggle usage often results in improper implementation, causing code quality issues. Although certain feature toggle usage patterns are prone to toggle smells, there is no tool as of today for software engineers to detect toggle usage patterns from the source code. This paper presents a tool TS-Detector to detect five different toggle usage patterns across ten open-source software projects in six different programming languages. We conducted a manual evaluation and results show that the true positive rates of detecting Spread, Nested, and Dead toggles are 80%, 86.4%, and 66.6% respectively, and the true negative rate of Mixed and Enum usages was 100%. The tool can be downloaded from its GitHub repository and can be used following the instructions provided there. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2505_05326 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | TS-Detector : Detecting Feature Toggle Usage Patterns Rahman, Tajmilur Fei, Mengzhe Sharma, Tushar Roy, Chanchal Software Engineering Feature toggles enable developers to control feature states, allowing the features to be released to a limited group of users while preserving overall software functionality. The absence of comprehensive best practices for feature toggle usage often results in improper implementation, causing code quality issues. Although certain feature toggle usage patterns are prone to toggle smells, there is no tool as of today for software engineers to detect toggle usage patterns from the source code. This paper presents a tool TS-Detector to detect five different toggle usage patterns across ten open-source software projects in six different programming languages. We conducted a manual evaluation and results show that the true positive rates of detecting Spread, Nested, and Dead toggles are 80%, 86.4%, and 66.6% respectively, and the true negative rate of Mixed and Enum usages was 100%. The tool can be downloaded from its GitHub repository and can be used following the instructions provided there. |
| title | TS-Detector : Detecting Feature Toggle Usage Patterns |
| topic | Software Engineering |
| url | https://arxiv.org/abs/2505.05326 |