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MSR 2021
Mon 17 - Wed 19 May 2021
co-located with ICSE 2021
Wed 19 May 2021 02:09 - 02:13 at MSR Room 2 - NLP Chair(s): Chunyang Chen

Primitive types are fundamental components available in any programming language, which serve as the building blocks of data manipulation. Understanding the role of these types in source code is essential to write software. The most convenient way to express the functionality of these variables in the code is through describing them in comments. Little work has been conducted on how often these variables are documented in code comments and what types of knowledge the comments provide about variables of primitive types. In this paper, we present an approach for detecting primitive variables and their description in comments using lexical matching and semantic matching. We evaluate our approaches by comparing the lexical and semantic matching performance in terms of recall, precision, and F-score, against 600 manually annotated variables from a sample of GitHub projects. The performance of our semantic approach based on F-score was superior compared to lexical matching, 0.986 and 0.942, respectively. We then create a taxonomy of the types of knowledge contained in these comments about variables of primitive types. Our study showed that developers usually documented the variables’ identifiers of a numeric data type with their purpose (69.16%) and concept (72.75%) more than the variables’ identifiers of type String which were less documented with purpose (61.14%) and concept (55.46%). Our findings characterise the current state of the practice of documenting primitive variables and point at areas that are often not well documented, such as the meaning of boolean variables or the purpose of fields and local variables.

Wed 19 May

Displayed time zone: Amsterdam, Berlin, Bern, Rome, Stockholm, Vienna change

02:00 - 02:50
NLPRegistered Reports / Technical Papers at MSR Room 2
Chair(s): Chunyang Chen Monash University
02:01
4m
Talk
Automatic Part-of-Speech Tagging for Security Vulnerability Descriptions
Technical Papers
SOFONIAS YITAGESU Tianjin University, Xiaowang Zhang Tianjin University, Zhiyong Feng Tianjin University, Li Xiaohong TianJin University, Zhenchang Xing Australian National University
Pre-print
02:05
4m
Talk
Attention-based model for predicting question relatedness on Stack Overflow
Technical Papers
Jiayan Pei South China University of Technology, Yimin Wu South China University of Technology, Research Institute of SCUT in Yangjiang, Zishan Qin South China University of Technology, Yao Cong South China University of Technology, Jingtao Guan Research Institute of SCUT in Yangjiang
Pre-print
02:09
4m
Talk
Characterising the Knowledge about Primitive Variables in Java Code Comments
Technical Papers
Mahfouth Alghamdi The University of Adelaide, Shinpei Hayashi Tokyo Institute of Technology, Takashi Kobayashi Tokyo Institute of Technology, Christoph Treude University of Adelaide
Pre-print
02:13
4m
Talk
Googling for Software Development: What Developers Search For and What They Find
Technical Papers
Pre-print
02:17
3m
Talk
Evaluating Pre-Trained Models for User Feedback Analysis in Software Engineering: A Study on Classification of App-Reviews
Registered Reports
Mohammad Abdul Hadi University of British Columbia, Fatemeh Hendijani Fard University of British Columbia
Pre-print
02:20
3m
Talk
Cross-status Communication and Project Outcomes in OSS Development–A Language Style Matching Perspective
Registered Reports
Yisi Han Nanjing University, Zhendong Wang University of California, Irvine, Yang Feng State Key Laboratory for Novel Software Technology, Nanjing University, Zhihong Zhao Nanjing Tech Unniversity, Yi Wang Beijing University of Posts and Telecommunications
Pre-print
02:23
27m
Live Q&A
Discussions and Q&A
Technical Papers


Information for Participants
Wed 19 May 2021 02:00 - 02:50 at MSR Room 2 - NLP Chair(s): Chunyang Chen
Info for room MSR Room 2:

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