In 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 through source code comments. Previous research on SATD has focused predominantly on the Java programming language, revealing a significant gap in cross-language SATD. Such a narrow focus limits the generalizability of existing findings as well as SATD detection techniques across multiple programming languages. Our work addresses such limitation by introducing CppSATD, a dedicated C++ SATD dataset, comprising over 531,000 annotated comments and their source code contexts. Our dataset can serve as a foundation for future studies that aim to develop SATD detection methods in C++, generalize the existing findings to other languages, or contribute novel insights to cross-language SATD research.
View on arXiv@article{pham2025_2505.01136,
title={ CppSATD: A Reusable Self-Admitted Technical Debt Dataset in C++ },
author={ Phuoc Pham and Murali Sridharan and Matteo Esposito and Valentina Lenarduzzi },
journal={arXiv preprint arXiv:2505.01136},
year={ 2025 }
}