Comparing Maintainability Index, SIG Method, and SQALE for Technical Debt Identification
| Authors | |
|---|---|
| Year of publication | 2020 |
| Type | Article in Proceedings |
| Conference | 35th ACM/SIGAPP Symposium On Applied Computing |
| MU Faculty or unit | |
| Citation | |
| Doi | http://dx.doi.org/10.1145/3341105.3374079 |
| Keywords | Software Technical Debt; Software Maintenance; Software Quality; Maintainability Index; SIG Method; SQALE |
| Description | 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. |
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