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Technical Debt Engineering - Towards Exploring and Modeling High Priority Technical Debt

Description: Technical debt - refers to code design and implementation that is often applied as ad hoc solutions or workarounds and will require more development costs in the future. The goal of this study is to develop an engineering approach, based on mining software repositories, to identify and model the technical debt that causes chronic resource shortages in development projects and that should be eliminated as a priority. The main outcomes of this study are (1) systematization/detection of various types of technical debt, (2) empirical investigation of the impact of technical debt, and (3) modeling of technical debt with large debt amounts.
Amount: ¥16,640,000
Funding type: research
Funder scheme: Grant-in-Aid for Scientific Research (B)
Start date: 2018-04-01
End date: 2022-03-31
Investigator: Kamei Yasutaka (lead)
Institution: Kyushu University
Funded outputs count: 16
Funder award ID: 18H03222
OpenAlex ID: G1602016358
An empirical study of issue-link algorithms: which issue-link algorithms should we use?
2022 · Masanari Kondo, Yutaro Kashiwa, et al. · Empirical Software Engineering · 9
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An empirical study on self-admitted technical debt in Dockerfiles
2022 · Hideaki Azuma, Shinsuke Matsumoto, et al. · Empirical Software Engineering · 37
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Studying donations and their expenses in open source projects: a case study of GitHub projects collecting donations through open collectives
2021 · Jiayuan Zhou, Shaowei Wang, et al. · Empirical Software Engineering · 13
The Impact of Feature Importance Methods on the Interpretation of Defect Classifiers
2021 · Gopi Krishnan Rajbahadur, Shaowei Wang, et al. · IEEE Transactions on Software Engineering · 158
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SBFL-Suitability: A Software Characteristic for Fault Localization
2020 · Yui Sasaki, Yoshiki Higo, et al. · IEEE International Conference on Software Maintenance (ICSM) · 18
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The Effect of Cognitive Load in Code Reading on Non-Programming Specific Environment
2020 · Hideaki Azuma, Shinsuke Matsumoto, et al. · IEEE Annual International Computer Software and Applications Conference (COMPSAC) · 1
Program Repairing History as Git Repository
2020 · Ryoko Izuta, Shinsuke Matsumoto, et al.
A Study on the Current Status of Functional Idioms in Java
2019 · Hiroto TANAKA, Shinsuke MATSUMOTO, et al. · IEICE Transactions on Information and Systems · 11
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Achievements Visualization in Programming Education
2019 · Kaisei Hanayama, Shinsuke Matsumoto, et al. · IEEE Annual International Computer Software and Applications Conference (COMPSAC)
A survey of self-admitted technical debt
2019 · Giancarlo Sierra, Emad Shihab, et al. · Journal of Systems and Software · 79
Mining Source Code Improvement Patterns from Similar Code Review Works
2019 · Yuki Ueda, Takashi Ishio, et al. · IEEE International Workshop on Software Clones (IWSC) · 6
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Madoop: Improving Browser-Based Volunteer Computing Based on Modern Web Technologies
2019 · Hiroyuki Matsuo, Shinsuke Matsumoto, et al. · IEEE International Conference on Software Analysis, Evolution and Reengineering (SANER) · 5
The impact of feature reduction techniques on defect prediction models
2019 · Masanari Kondo, Cor-Paul Bezemer, et al. · Empirical Software Engineering · 107
Impact of Coding Style Checker on Code Review - A Case Study on the OpenStack Projects
2018 · Yuki Ueda, Akinori Ihara, et al. · International Workshop on Empirical Software Engineering in Practice (IWESEP) · 6
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Bridging Semantic Gaps between Natural Languages and APIs with Word Embedding
2018 · Xiaochen Li, He Jiang, et al. · IEEE Transactions on Software Engineering · 48
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Automatic topic classification of test cases using text mining at an Android smartphone vendor
2018 · Junji Shimagaki, Yasutaka Kamei, et al. · Proceedings of the ... ACM-IEEE International Symposium on Empirical Software Engineering and Measurement/International Symposium on Empirical Software Engineering and Measurement · 9