Results 11 to 20 of about 9,472,967 (176)
Proceedings of the 19th International Conference on Mining Software Repositories, 2022 short ...
Barbara Russo +2 more
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Data Balancing Improves Self-Admitted Technical Debt Detection [PDF]
2021 IEEE/ACM 18th International Conference on Mining Software Repositories (MSR), 2021 11 pages, 1 figure, for ...
Rantala Leevi +3 more
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Identification and Remediation of Self-Admitted Technical Debt in Issue Trackers [PDF]
2020 46th Euromicro Conference on Software Engineering and Advanced Applications (SEAA), 2020 Technical debt refers to taking shortcuts to achieve short-term goals, which might negatively influence software maintenance in the long-term. There is increasing attention on technical debt that is admitted by developers in source code comments (termed as self-admitted technical debt or SATD). But SATD in issue trackers is relatively unexplored.
Yikun Li +2 more
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Characterizing and Mitigating Self-Admitted Technical Debt in Build Systems [PDF]
IEEE Transactions on Software Engineering, 2022 Technical Debt is a metaphor used to describe the situation in which long-term software artifact quality is traded for short-term goals in software projects. In recent years, the concept of self-admitted technical debt (SATD) was proposed, which focuses on debt that is intentionally introduced and described by developers.
Tao Xiao 0001 +6 more
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Negativity in self-admitted technical debt: how sentiment influences prioritization [PDF]
Empirical Software EngineeringAbstract Self-Admitted Technical Debt, or SATD, is a self-admission of technical debt present in a software system. The presence of SATD in software systems negatively affects developers, therefore, managing and addressing SATD is crucial for software engineering. To effectively manage SATD, developers need to estimate its priority and assess
Nathan Cassee +3 more
core +7 more sources
Descriptor: C++ Self-Admitted Technical Debt Dataset (CppSATD)
IEEE Data DescriptionsIn software development, technical debt (TD) refers to suboptimal implementation choices made by the developers to meet urgent deadlines and limited resources, posing challenges for future maintenance. Self-Admitted Technical Debt (SATD) is a sub-type of TD, representing specific TD instances ``openly admitted'' by the developers and often expressed ...
Phuoc Pham +3 more
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An empirical study on self-admitted technical debt in Dockerfiles [PDF]
Empirical Software Engineering, 2022 AbstractIn software development, ad hoc solutions that are intentionally implemented by developers are called self-admitted technical debt (SATD). Because the existence of SATD spreads poor implementations, it is necessary to remove it as soon as possible. Meanwhile, container virtualization has been attracting attention in recent years as a technology
Hideaki Azuma +3 more
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Automated Identification of On-hold Self-admitted Technical Debt [PDF]
2020 IEEE 20th International Working Conference on Source Code Analysis and Manipulation (SCAM), 2020 Replication package of "Automated Identification of On-hold Self-admitted Technical Debt"
Rungroj Maipradit +6 more
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Automatically Learning Patterns for Self-Admitted Technical Debt Removal [PDF]
2020 IEEE 27th International Conference on Software Analysis, Evolution and Reengineering (SANER), 2020 Technical Debt (TD) expresses the need for improvements in a software system, e.g., to its source code or architecture. In certain circumstances, developers “self-admit” technical debt (SATD) in their source code comments. Previous studies investigate when SATD is admitted, and what changes developers perform to remove it. Building on these studies, we
Fiorella Zampetti +2 more
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Self-admitted technical debt in R: detection and causes
Automated Software Engineering, 2022 AbstractSelf-Admitted Technical Debt (SATD) is primarily studied in Object-Oriented (OO) languages and traditionally commercial software. However, scientific software coded in dynamically-typed languages such as R differs in paradigm, and the source code comments’ semantics are different (i.e., more aligned with algorithms and statistics when compared ...
Rishab Sharma +4 more
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