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@inproceedings{1594140,
author = {Strečanský, Peter and Chren, Stanislav and Rossi, Bruno},
address = {Brno, Czech Republic},
booktitle = {35th ACM/SIGAPP Symposium On Applied Computing},
doi = {http://dx.doi.org/10.1145/3341105.3374079},
keywords = {Software Technical Debt; Software Maintenance; Software Quality; Maintainability Index; SIG Method; SQALE},
howpublished = {tištěná verze "print"},
language = {eng},
location = {Brno, Czech Republic},
isbn = {978-1-4503-6866-7},
pages = {121-124},
publisher = {ACM},
title = {Comparing Maintainability Index, SIG Method, and SQALE for Technical Debt Identification},
year = {2020}
}
TY - JOUR
ID - 1594140
AU - Strečanský, Peter - Chren, Stanislav - Rossi, Bruno
PY - 2020
TI - Comparing Maintainability Index, SIG Method, and SQALE for Technical Debt Identification
PB - ACM
CY - Brno, Czech Republic
SN - 9781450368667
KW - Software Technical Debt
KW - Software Maintenance
KW - Software Quality
KW - Maintainability Index
KW - SIG Method
KW - SQALE
N2 - Many techniques have emerged to evaluate software Technical Debt (TD). However, differences in reporting TD are not yet studied widely, as they can give different perceptions about the evolution of TD in projects. The goal of this paper is to compare three TD identification techniques: i. Maintainability Index (MI), ii. SIG TD models and iii. SQALE analysis. Considering 17 large open source Python libraries, we compare TD measurements time series in terms of trends in different sets of releases (major, minor, micro). While all methods report generally growing trends of TD over time, MI, SIG TD, and SQALE all report different patterns of TD evolution.
ER -
STREČANSKÝ, Peter, Stanislav CHREN a Bruno ROSSI. Comparing Maintainability Index, SIG Method, and SQALE for Technical Debt Identification. In \textit{35th ACM/SIGAPP Symposium On Applied Computing}. Brno, Czech Republic: ACM, 2020, s.~121-124. ISBN~978-1-4503-6866-7. Dostupné z: https://dx.doi.org/10.1145/3341105.3374079.
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