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MSR 2021
Mon 17 - Wed 19 May 2021
co-located with ICSE 2021

This program is tentative and subject to change.

Wed 19 May 2021 02:16 - 02:25 at MSR Room 2 - NLP

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.

This program is tentative and subject to change.

Wed 19 May
Times are displayed in time zone: Amsterdam, Berlin, Bern, Rome, Stockholm, Vienna change

02:00 - 02:50
02:00
8m
Talk
Automatic Part-of-Speech Tagging for Security Vulnerability Descriptions
Technical Papers
SOFONIAS YITAGESUTianjin University, Xiaowang ZhangTianjin University, Zhiyong FengTianjin University, Li XiaohongTianJin University, Zhenchang XingAustralian National University
Pre-print
02:08
8m
Talk
Attention-based model for predicting question relatedness on Stack Overflow
Technical Papers
Jiayan PeiSouth China University of Technology, Yimin WuSouth China University of Technology, Research Institute of SCUT in Yangjiang, Zishan QinSouth China University of Technology, Yao CongSouth China University of Technology, Jingtao GuanResearch Institute of SCUT in Yangjiang
Pre-print
02:16
8m
Talk
Characterising the Knowledge about Primitive Variables in Java Code Comments
Technical Papers
Mahfouth AlghamdiThe University of Adelaide, Shinpei HayashiTokyo Institute of Technology, Takashi KobayashiTokyo Institute of Technology, Christoph TreudeUniversity of Adelaide
Pre-print
02:25
8m
Talk
Googling for Software Development: What Developers Search For and What They Find
Technical Papers
Pre-print
02:33
8m
Talk
Evaluating Pre-Trained Models for User Feedback Analysis in Software Engineering: A Study on Classification of App-Reviews
Registered Reports
Mohammad Abdul HadiUniversity of British Columbia, Fatemeh Hendijani FardUniversity of British Columbia
02:41
8m
Talk
Cross-status Communication and Project Outcomes in OSS Development–A Language Style Matching Perspective
Registered Reports
Yisi HanNanjing University, Zhendong WangUniversity of California, Irvine, Yang FengState Key Laboratory for Novel Software Technology, Nanjing University, Zhihong ZhaoNanjing Tech Unniversity, Yi WangBeijing University of Posts and Telecommunications