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Leevi Rantala
Leevi Rantala
PhD Student, University of Oulu
Verified email at oulu.fi
Title
Cited by
Cited by
Year
Data balancing improves self-admitted technical debt detection
M Sridharan, M Mantyla, L Rantala, M Claes
2021 IEEE/ACM 18th International Conference on Mining Software Repositories …, 2021
122021
Predicting technical debt from commit contents: reproduction and extension with automated feature selection
L Rantala, M Mäntylä
Software Quality Journal 28, 1551-1579, 2020
92020
Prevalence, contents and automatic detection of KL-SATD
L Rantala, M Mäntylä, D Lo
2020 46th Euromicro Conference on Software Engineering and Advanced …, 2020
92020
Towards better technical debt detection with NLP and machine learning methods
L Rantala
Proceedings of the ACM/IEEE 42nd International Conference on Software …, 2020
82020
SoCCMiner: a source code-comments and comment-context miner
M Sridharan, M Mäntylä, M Claes, L Rantala
Proceedings of the 19th International Conference on Mining Software …, 2022
52022
PENTACET data--23 Million Contextual Code Comments and 500,000 SATD comments
M Sridharan, L Rantala, M Mäntylä
arXiv preprint arXiv:2303.14029, 2023
12023
Keyword-labeled self-admitted technical debt and static code analysis have significant relationship but limited overlap
L Rantala, M Mäntylä, V Lenarduzzi
Software Quality Journal, 1-39, 2023
2023
PENTACET data-23 Million Contextual Code Comments and 250,000 SATD comments
M Sridharan, L Rantala, M Mäntylä
2023 IEEE/ACM 20th International Conference on Mining Software Repositories …, 2023
2023
Developing an aspect-based sentiment lexicon for software engineering
L Rantala
L. Rantala, 2018
2018
Relationship between Self-Admitted Technical Debt and Code-level Technical Debt. An Empirical Evaluation
L Rantala, V Lenarduzzi, MV Mäntylä
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