Associating Natural Language Comment and Source Code Entities
Sheena Panthaplackel, Milos Gligoric, Raymond J. Mooney, Junyi Jessy Li
Abstract
Comments are an integral part of software development; they are natural language descriptions associated with source code elements. Understanding explicit associations can be useful in improving code comprehensibility and maintaining the consistency between code and comments. As an initial step towards this larger goal, we address the task of associating entities in Javadoc comments with elements in Java source code. We propose an approach for automatically extracting supervised data using revision histories of open source projects and present a manually annotated evaluation dataset for this task. We develop a binary classifier and a sequence labeling model by crafting a rich feature set which encompasses various aspects of code, comments, and the relationships between them. Experiments show that our systems outperform several baselines learning from the proposed supervision. / * * * Check the beanFactory to see whether the bean * named beanName already exists. Accounts for * the fact that the requested bean may be "in * creation", i.e.: we're in the middle of servicing * the initial request for this bean. From JavaConfig's * perspective, this means that the bean does not * actually yet exist, and that it is now our job to * create it for the first time by executing the logic * in the corresponding Bean method. Said another * way, this check repurposes * ConfigurableBeanFactory#isCurrentlyInCreation * to determine whether the container is calling this * method or the user is calling this method. * @param beanName name of bean to check for * @return true if beanName already exists in * the factory * / boolean factoryContainsBean(String beanName)
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Install the CLIlune papers fulltext 87292728-0f54-4e13-8e2f-925aedea7f64Cited by top-tier papers5
- Deep Just-In-Time Inconsistency Detection Between Comments and Source CodeSheena Panthaplackel, Junyi Jessy Li, Milos Gligoric, Raymond J. MooneyAAAI 2021 · 62 citations
- Learning Deep Semantics for Test CompletionPengyu Nie, Rahul Banerjee, Junyi Jessy Li, Raymond J. Mooney et al.ICSE 2023 · 45 citations
- On the naturalness of hardware descriptionsJaeseong Lee, Pengyu Nie, Junyi Jessy Li, Milos GligoricFSE 2020 · 6 citations
- Learning to Update Natural Language Comments Based on Code ChangesSheena Panthaplackel, Pengyu Nie, Milos Gligoric, Junyi Jessy Li et al.ACL 2020 · 1 citation
- KaggleDBQA: Realistic Evaluation of Text-to-SQL ParsersChia-Hsuan Lee, Oleksandr Polozov, Matthew RichardsonACL 2021
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