[Remote] Mining Resource-Operation Knowledge to Support Resource Leak Detection
Resource leaks, which are caused by acquired resources not being released, often result in performance degradation and system crashes. Resource leak detection mainly relies on two essential components. First, identify the potential pairs of the Resource Acquisition API method and the corresponding Resource Release API method (\textit{RAR pairs} for short); then based on the RAR pairs, analyze the code to check whether the release API is not subsequently called after the acquisition API.
While the majority of existing resource leak detection techniques are concentrated on proposing more precise and more scalable code analysis, a few of them focus on building a more \textit{complete} RAR pair pool. In particular, existing techniques only consider RAR pairs that are manually predefined or mined from project-specific code corpus. Such RAR pairs have limited coverage in libraries/APIs and might miss potential RAR pairs in the code, which further limits the effectiveness of the subsequent analysis.
To build a more complete RAR pair pool for resource leak detection, in this work, we propose to represent resource-operation knowledge as \textbf{abstract resource acquisition/release operation pairs} (\textit{Abs-RAR pairs} for short), and mine such Abs-RAR pairs from a large code corpus. Based on this idea, we propose MiROK, a novel approach for \textbf{Mi}ning \textbf{R}esource \textbf{O}peration \textbf{K}nowledge, which aims at constructing a better RAR pair pool to support resource leak detection. Given a large code corpus, MiROK first mines Abs-RAR pairs with novel rule-based pair expansion and learning-based pair identification strategies, and then instantiates these Abs-RAR pairs into concrete RAR pairs. We implement MiROK and apply it to mine RAR pairs from a large code corpus of 1,454,224 Java methods and 20,000 Maven libraries. We then perform an extensive evaluation to investigate the mining effectiveness of MiROK and the practical usage of its mined RAR pairs for supporting resource leak detection. Our results show that MiROK mines 1,313 new Abs-RAR pairs and instantiates them into 10,766 RAR pairs with a high precision (i.e., 93.3%). In addition, we feed our mined RAR pairs to existing resource leak analysis approaches, and help them detect more resource leak defects in both online code examples and open-source projects. Our results indicate both the high quality and practical usage of our mined RAR pairs.
Wed 6 DecDisplayed time zone: Pacific Time (US & Canada) change
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