ConfInLog: Leveraging Software Logs to Infer Configuration Constraints
Shulin Zhou, Xiaodong Liu, Shanshan Li, Zhouyang Jia, Yuanliang Zhang,, Teng Wang, Wang Li, Xiangke Liao

TL;DR
This paper introduces ConfInLog, a tool that infers configuration constraints from software logs, effectively complementing static analysis methods and improving the accuracy of identifying configuration-related issues.
Contribution
ConfInLog leverages natural language patterns in logs to infer configuration constraints, addressing limitations of static code analysis and enhancing constraint detection accuracy.
Findings
ConfInLog inferred 22 to 163 constraints per system.
Approximately 60% of inferred constraints were novel compared to prior methods.
Developers confirmed and accepted 10 constraints in practical patches.
Abstract
Misconfigurations have become the dominant causes of software failures in recent years, drawing tremendous attention for their increasing prevalence and severity. Configuration constraints can preemptively avoid misconfiguration by defining the conditions that configuration options should satisfy. Documentation is the main source of configuration constraints, but it might be incomplete or inconsistent with the source code. In this regard, prior researches have focused on obtaining configuration constraints from software source code through static analysis. However, the difficulty in pointer analysis and context comprehension prevents them from collecting accurate and comprehensive constraints. In this paper, we observed that software logs often contain configuration constraints. We conducted an empirical study and summarized patterns of configuration-related log messages. Guided by the…
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Taxonomy
TopicsSoftware System Performance and Reliability · Software Engineering Research · Advanced Software Engineering Methodologies
