Paper Info
Title
Using Natural Language Processing to Automatically Detect Self-Admitted Technical Debt.
Abstract
The metaphor of technical debt was introduced to express the trade off between productivity and quality, i.e., when developers take shortcuts or perform quick hacks. More recently, our work has shown that it is possible to detect technical debt using source code comments (i.e., self-admitted technical debt), and that the most common types of self-admitted technical debt are design and requirement ...
Year
DOI
Venue
2017
10.1109/TSE.2017.2654244
IEEE Transactions on Software Engineering
Keywords
Field
DocType
Software,Natural language processing,Manuals,Entropy,Unified modeling language,Java,Structured Query Language
Unified Modeling Language,Source code,Computer science,Software,Natural language processing,Artificial intelligence,Technical debt,Empirical research,SQL,Software engineering,Hibernation (computing),Debt,Database
Journal
Volume
Issue
ISSN
43
11
0098-5589
Citations 
PageRank 
References 
44
1.04
39
Authors
3
Name
Order
Citations
PageRank
Everton da S. Maldonado1692.14
Emad Shihab2122954.74
Nikolaos Tsantalis374332.14