Descriptor: C++ Self-Admitted Technical Debt Dataset (CppSATD)

TL;DR

This paper introduces CppSATD, a large dataset of C++ source code comments explicitly admitting technical debt, addressing the gap in cross-language SATD research and enabling future detection and analysis methods.

Contribution

The creation of the first extensive C++ SATD dataset with over 531,000 annotated comments, facilitating cross-language SATD studies and detection techniques.

Findings

First large-scale C++ SATD dataset available

Enables cross-language SATD research and detection

Supports future development of SATD identification methods

Abstract

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.