Towards Automatically Addressing Self-Admitted Technical Debt: How Far Are We?

Upon evolving their software, organizations and individual developers have to spend a substantial effort to pay back technical debt, i.e, the fact that software is released in a shape not as good as it should be, e.g, in terms of functionality, reliability, or maintainability. This paper empirically...

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Veröffentlicht in:	IEEE/ACM International Conference on Automated Software Engineering : [proceedings] S. 585 - 597
Hauptverfasser:	Mastropaolo, Antonio, Di Penta, Massimiliano, Bavota, Gabriele
Format:	Tagungsbericht
Sprache:	Englisch
Veröffentlicht:	IEEE 11.09.2023
Schlagworte:	Codes Machine Learning for Code Organizations Pre-trained models Self-Admitted Technical Debt Shape Software Software reliability Training Transformers
ISSN:	2643-1572
Online-Zugang:	Volltext
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