Rethinking Software Misconfigurations in the Real World: An Empirical Study and Literature Analysis
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arXiv
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| Format: | Preprint |
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2024
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| author | Liu, Yuhao Zhou, Yingnan Zhang, Hanfeng Chang, Zhiwei Xu, Sihan Jia, Yan Wang, Wei Hu, Juncheng Liu, Zheli |
| author_facet | Liu, Yuhao Zhou, Yingnan Zhang, Hanfeng Chang, Zhiwei Xu, Sihan Jia, Yan Wang, Wei Hu, Juncheng Liu, Zheli |
| contents | Software misconfiguration has consistently been a major reason for software failures. Over the past two decades, much work has been done to detect and diagnose software misconfigurations. However, there is still a gap between real-world misconfigurations and the literature. It is desirable to investigate whether existing taxonomy and tools are applicable for real-world misconfigurations in modern software. In this paper, we conduct an empirical study on 772 real-world misconfiguration issues, based on which we propose a novel classification of the root causes of software misconfigurations, i.e., constraint violation, resource unavailability, component integration error, and configuration semantic misinterpretation. Then, we systematically review the literature on misconfiguration troubleshooting to study the trends of research and the practicality of the tools and datasets in this field. We find that the research targets have changed from system and infrastructure software to advanced applications (e.g., cloud service). Meanwhile, research on non-crash misconfigurations has also grown significantly. Despite the progress, a majority of studies lack reproducibility due to the unavailable tools and evaluation datasets. In total, only eleven tools and four datasets are publicly available. We analyze the trends of existing literature on misconfiguration troubleshooting, summarize the challenges that users are faced with, and highlight the suggestions to mitigate and diagnose software misconfigurations. We release the real-world dataset of misconfiguration issues for follow-up research. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2412_11121 |
| institution | arXiv |
| publishDate | 2024 |
| record_format | arxiv |
| spellingShingle | Rethinking Software Misconfigurations in the Real World: An Empirical Study and Literature Analysis Liu, Yuhao Zhou, Yingnan Zhang, Hanfeng Chang, Zhiwei Xu, Sihan Jia, Yan Wang, Wei Hu, Juncheng Liu, Zheli Software Engineering D.2 Software misconfiguration has consistently been a major reason for software failures. Over the past two decades, much work has been done to detect and diagnose software misconfigurations. However, there is still a gap between real-world misconfigurations and the literature. It is desirable to investigate whether existing taxonomy and tools are applicable for real-world misconfigurations in modern software. In this paper, we conduct an empirical study on 772 real-world misconfiguration issues, based on which we propose a novel classification of the root causes of software misconfigurations, i.e., constraint violation, resource unavailability, component integration error, and configuration semantic misinterpretation. Then, we systematically review the literature on misconfiguration troubleshooting to study the trends of research and the practicality of the tools and datasets in this field. We find that the research targets have changed from system and infrastructure software to advanced applications (e.g., cloud service). Meanwhile, research on non-crash misconfigurations has also grown significantly. Despite the progress, a majority of studies lack reproducibility due to the unavailable tools and evaluation datasets. In total, only eleven tools and four datasets are publicly available. We analyze the trends of existing literature on misconfiguration troubleshooting, summarize the challenges that users are faced with, and highlight the suggestions to mitigate and diagnose software misconfigurations. We release the real-world dataset of misconfiguration issues for follow-up research. |
| title | Rethinking Software Misconfigurations in the Real World: An Empirical Study and Literature Analysis |
| topic | Software Engineering D.2 |
| url | https://arxiv.org/abs/2412.11121 |