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ICSE 2023
Sun 14 - Sat 20 May 2023 Melbourne, Australia
Fri 19 May 2023 17:00 - 17:07 at Level G - Plenary Room 1 - Software quality Chair(s): Valentina Lenarduzzi

Developers sometimes choose design and implementation shortcuts due to the pressure from tight release schedules. However, shortcuts introduce technical debt that increases as the software evolves. The debt needs to be repaid as fast as possible to minimize its impact on software development and software quality. Sometimes, technical debt is admitted by developers in comments and commit messages. Such debt is known as self-admitted technical debt (SATD). In data-intensive systems, where data manipulation is a critical functionality, the presence of SATD in the data access logic could seriously harm performance and maintainability. Understanding the composition and distribution of the SATDs across software systems and their evolution could provide insights into managing technical debt efficiently. We present a large-scale empirical study on the prevalence, composition, and evolution of SATD in data-intensive systems. We analyzed 83 open-source systems relying on relational databases as well as 19 systems relying on NoSQL databases. We detected SATD in source code comments obtained from different snapshots of the subject systems. To understand the evolution dynamics of SATDs, we conducted a survival analysis. Next, we performed a manual analysis of 361 sample data-access SATDs, investigating the composition of data-access SATDs and the reasons behind their introduction and removal. We identified 15 new SATD categories, out of which 11 are specific to database access operations. We found that most of the data-access SATDs are introduced in the later stages of change history rather than at the beginning. We also observed that bug fixing and refactoring are the main reasons behind the introduction of data-access SATDs.

Fri 19 May

Displayed time zone: Hobart change

15:45 - 17:15
15:45
15m
Talk
DuetCS: Code Style Transfer through Generation and Retrieval
Technical Track
Binger Chen Technische Universität Berlin, Ziawasch Abedjan Leibniz Universität Hannover
16:00
15m
Talk
Understanding Why and Predicting When Developers Adhere to Code-Quality Standards
SEIP - Software Engineering in Practice
Manish Motwani Georgia Institute of Technology, Yuriy Brun University of Massachusetts
Pre-print
16:15
15m
Talk
Code Compliance Assessment as a Learning Problem
SEIP - Software Engineering in Practice
16:30
15m
Talk
An Empirical Study on Quality Issues of Deep Learning Platform
SEIP - Software Engineering in Practice
Yanjie Gao Microsoft Research, Xiaoxiang Shi , Haoxiang Lin Microsoft Research, Hongyu Zhang The University of Newcastle, Hao Wu , Rui Li , Mao Yang Microsoft Research
Pre-print
16:45
7m
Talk
Can static analysis tools find more defects? A qualitative study of design rule violations found by code review
Journal-First Papers
Sahar Mehrpour George Mason University, USA, Thomas LaToza George Mason University
16:52
7m
Talk
DebtFree: minimizing labeling cost in self-admitted technical debt identification using semi-supervised learning
Journal-First Papers
Huy Tu North Carolina State University, USA, Tim Menzies North Carolina State University
Link to publication Pre-print
17:00
7m
Talk
FIXME: synchronize with database! An empirical study of data access self-admitted technical debt
Journal-First Papers
Biruk Asmare Muse Polytechnique Montréal, Csaba Nagy Software Institute - USI, Lugano, Anthony Cleve University of Namur, Foutse Khomh Polytechnique Montréal, Giuliano Antoniol Polytechnique Montréal
17:07
7m
Talk
How does quality deviate in stable releases by backporting?
NIER - New Ideas and Emerging Results
Jarin Tasnim University of Saskatchewan, Debasish Chakroborti University of Saskatchewan, Chanchal K. Roy University of Saskatchewan, Kevin Schneider University of Saskatchewan
Link to publication Pre-print