High quality method names are descriptive and readable, which are helpful for code development and maintenance. The majority of recent research suggest method names based on the text summarization approach. They take the token sequence and abstract syntax tree of the source code as input, and generate method names through a powerful neural network based model. However, the tokens composing the method name are closely related to the entity name within its method implementation. Actually, high proportions of the tokens in method name can be found in its corresponding method implementation, which makes it possible for incorporating these common shared token information to improve the performance of method naming task. Inspired by this key observation, we propose a two-stage keywords guided method name generation approach to suggest method names. Specifically, we decompose the method naming task into two subtasks, including keywords extraction task and method name generation task. For the keywords extraction task, we apply a graph neural network based model to extract the keywords from source code. For the method name generation task, we utilize the extracted keywords to guide the method name generation model. We apply a dual selective gate in encoder to control the information flow, and a dual attention mechanism in decoder to combine the semantics of input code sequence and keywords. Experiment results on an open source dataset demonstrate that keywords guidance can facilitate method naming task, which enables our model to outperform the competitive state-of-the-art models by margins of 1.5%-3.5% in ROUGE metrics. Especially when programs share one common token with method names, our approach improves the absolute ROUGE-1 score by 7.8%.
Fri 21 MayDisplayed time zone: Amsterdam, Berlin, Bern, Rome, Stockholm, Vienna change
02:00 - 02:40
|ConfInLog: Leveraging Software Logs to Infer Configuration Constraints
Shulin Zhou National University of Defense Technology, Xiaodong Liu National University of Defense Technology, Shanshan Li National University of Defense Technology, Zhouyang Jia National University of Defense Technology, Yuanliang Zhang National University of Defense Technology, Teng Wang National University of Defense Technology, China, Wang Li National University of Defense Technology, Xiangke Liao National University of Defense Technology, ChinaPre-print Media Attached
|Using Grammar Patterns to Interpret Test Method Name Evolution
Anthony Peruma Rochester Institute of Technology, Emily Hu , Jiajun Chen , Eman Abdullah AlOmar Rochester Institute of Technology, USA, Mohamed Wiem Mkaouer Rochester Institute of Technology, Christian D. Newman Rochester Institute of TechnologyPre-print Media Attached
|Keywords Guided Method Name Generation
ResearchPre-print Media Attached
|Automated Comment Update: How Far are We?
Bo Lin National University of Defense Technology, Shangwen Wang National University of Defense Technology, Kui Liu Huawei Software Engineering Application Technology Lab, Xiaoguang Mao National University of Defense Technology, Tegawendé F. Bissyandé SnT, University of LuxembourgPre-print Media Attached