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MSR 2021
Mon 17 - Wed 19 May 2021
co-located with ICSE 2021
Tue 18 May 2021 10:01 - 10:04 at MSR Room 1 - Developer communications Chair(s): Hourieh Khalajzadeh

Self-Admitted Technical Debt (SATD) represents the admission, made through source code comments or other channels, of portions of a program being poorly implemented, containing provisional solutions or, in general, simply being not ready yet. To better understand developers’ habits in SATD annotation, and possibly support their exploitation in tool support, this paper provides an in-depth analysis of the content provided in SATD comments, and the expressed sentiment. We manually inspect and classify 1038 instances from an existing dataset, grouping them along a taxonomy composed of 41 categories (of which 9 top-level ones), identifying their sentiment, and the presence of external references such as author names or issue IDs. Results of our study indicate that (i) the SATD content is crosscutting along life-cycle dimensions identified in previous work, (ii) comments related to functional problems or on-hold SATD are generally more negative than poor implementation choices or partially implemented functionality, and (iii) despite observations from previous literature, only a minority of SATD comments leverage external references.

Conference Day
Tue 18 May

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

10:00 - 10:50
Developer communicationsTechnical Papers / Data Showcase at MSR Room 1
Chair(s): Hourieh KhalajzadehMonash University, Australia
Waiting around or job half-done? Sentiment in self-admitted technical debt
Technical Papers
Gianmarco FucciUniversity of Sannio, Nathan CasseeEindhoven University of Technology, Fiorella ZampettiUniversity of Sannio, Italy, Nicole NovielliUniversity of Bari, Alexander SerebrenikEindhoven University of Technology, Massimiliano Di PentaUniversity of Sannio, Italy
Pre-print Media Attached
Research paper
Automatically Selecting Follow-up Questions for Deficient Bug Reports
Technical Papers
Mia Mohammad ImranVirginia Commonwealth University, Agnieszka Ciborowska Virginia Commonwealth University, Kostadin DamevskiVirginia Commonwealth University
Challenges in Developing Desktop Web Apps: a Study of Stack Overflow and GitHub
Technical Papers
Gian Luca ScocciaUniversity of L'Aquila, Patrizio MigliariniDISIM, University of L'Aquila, Marco AutiliUniversity of L'Aquila, Italy
Search4Code: Code Search Intent Classification Using Weak Supervision
Data Showcase
Nikitha RaoMicrosoft Research, Chetan BansalMicrosoft Research, Joe GuanMicrosoft
Live Q&A
Discussions and Q&A
Technical Papers

Information for Participants
Info for MSR Room 1: