Code Parameter Summarization Based on Transformer and Fusion Strategy

IF 1.5 4区 计算机科学 Q3 COMPUTER SCIENCE, SOFTWARE ENGINEERING
IET Software Pub Date : 2024-12-31 DOI:10.1049/sfw2/3706673
Fanlong Zhang, Jiancheng Fan, Weiqi Li, Siau-cheng Khoo
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引用次数: 0

Abstract

Context: As more time has been spent on code comprehension activities during software development, automatic code summarization has received much attention in software engineering research, with the goal of enhancing software comprehensibility. In the meantime, it is prevalently known that a good knowledge about the declaration and the use of method parameters can effectively enhance the understanding of the associated methods. A traditional approach used in software development is to declare the types of method parameters.

Objective: In this work, we advocate parameter-level code summarization and propose a novel approach to automatically generate parameter summaries of a given method. Parameter summarization is considerably challenging, as neither do we know the kind of information of the parameters that can be employed for summarization nor do we know the methods for retrieving such information.

Method: We present paramTrans, which is a novel approach for parameter summarization. paramTrans characterizes the semantic features from parameter-related information based on transformer; it also explores three fusion strategies for absorbing the method-level information to enhance the performance. Moreover, to retrieve parameter-related information, a parameter slicing algorithm (named paramSlice) is proposed, which slices the parameter-related node from the abstract syntax tree (AST) at the statement level.

Results: We conducted experiments to verify the effectiveness of our approach. Experimental results show that our approach possesses an effective ability in summarizing parameters; such ability can be further enhanced by understanding the available summaries about individual methods, through the introduction of three fusion strategies.

Conclusion: We recommend developers employ our approach as well as the fusion strategies to produce parameter summaries to enhance the comprehensibility of code.

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来源期刊
IET Software
IET Software 工程技术-计算机:软件工程
CiteScore
4.20
自引率
0.00%
发文量
27
审稿时长
9 months
期刊介绍: IET Software publishes papers on all aspects of the software lifecycle, including design, development, implementation and maintenance. The focus of the journal is on the methods used to develop and maintain software, and their practical application. Authors are especially encouraged to submit papers on the following topics, although papers on all aspects of software engineering are welcome: Software and systems requirements engineering Formal methods, design methods, practice and experience Software architecture, aspect and object orientation, reuse and re-engineering Testing, verification and validation techniques Software dependability and measurement Human systems engineering and human-computer interaction Knowledge engineering; expert and knowledge-based systems, intelligent agents Information systems engineering Application of software engineering in industry and commerce Software engineering technology transfer Management of software development Theoretical aspects of software development Machine learning Big data and big code Cloud computing Current Special Issue. Call for papers: Knowledge Discovery for Software Development - https://digital-library.theiet.org/files/IET_SEN_CFP_KDSD.pdf Big Data Analytics for Sustainable Software Development - https://digital-library.theiet.org/files/IET_SEN_CFP_BDASSD.pdf
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