University of Oulu

L. Rantala, M. Mäntylä and D. Lo, "Prevalence, Contents and Automatic Detection of KL-SATD," 2020 46th Euromicro Conference on Software Engineering and Advanced Applications (SEAA), Portoroz, Slovenia, 2020, pp. 385-388, doi: 10.1109/SEAA51224.2020.00069

Prevalence, contents and automatic detection of KL-SATD

Saved in:
Author: Rantala, Leevi1; Mäntylä, Mika1; Lo, David2
Organizations: 1ITEE, M3S, University of Oulu, Oulu, Finland
2Information Systems, Singapore Management University, Singapore, Singapore
Format: article
Version: accepted version
Access: open
Online Access: PDF Full Text (PDF, 0.1 MB)
Persistent link:
Language: English
Published: Institute of Electrical and Electronics Engineers, 2020
Publish Date: 2020-12-01


When developers use different keywords such as TODO and FIXME in source code comments to describe self-admitted technical debt (SATD), we refer it as Keyword-Labeled SATD (KL-SATD). We study KL-SATD from 33 software repositories with 13,588 KL-SATD comments. We find that the median percentage of KL-SATD comments among all comments is only 1,52%. We find that KL-SATD comment contents include words expressing code changes and uncertainty, such as remove, fix, maybe and probably. This makes them different compared to other comments. KL-SATD comment contents are similar to manually labeled SATD comments of prior work. Our machine learning classifier using logistic Lasso regression has good performance in detecting KL-SATD comments (AUC-ROC 0.88). Finally, we demonstrate that using machine learning we can identify comments that are currently missing but which should have a SATD keyword in them. Automating SATD identification of comments that lack SATD keywords can save time and effort by replacing manual identification of comments. Using KL-SATD offers a potential to bootstrap a complete SATD detector.

see all

ISBN: 978-1-7281-9532-2
ISBN Print: 978-1-7281-9533-9
Pages: 385 - 388
DOI: 10.1109/SEAA51224.2020.00069
Host publication: 2020 46th Euromicro Conference on Software Engineering and Advanced Applications (SEAA)
Conference: Euromicro Conference on Software Engineering and Advanced Applications
Type of Publication: A4 Article in conference proceedings
Field of Science: 113 Computer and information sciences
Copyright information: © 2020 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.