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https://ruomo.lib.uom.gr/handle/7000/1561
Τίτλος: | Assessing TD Macro-Management: A Nested Modelling Statistical Approach |
Συγγραφείς: | Nikolaidis, Nikolaos Mittas, Nikolaos Ampatzoglou, Apostolos Arvanitou, Elvira-Maria Chatzigeorgiou, Alexander |
Τύπος: | Article |
Θέματα: | FRASCATI::Natural sciences::Computer and information sciences |
Λέξεις-Κλειδιά: | Technical Debt Metrics Measurement Quality Analysis and Evaluation Software maintenance |
Ημερομηνία Έκδοσης: | 23-Ιαν-2023 |
Πηγή: | IEEE Transactions on Software Engineering |
Πρώτη Σελίδα: | 1 |
Τελευταία Σελίδα: | 13 |
Επιτομή: | Quality improvement can be performed at the: (a) micro-management level: interventions applied at a fine-grained level (e.g., at a class or method level, by applying a refactoring); or (b) macro-management level: interventions applied at a large-scale (e.g., at project level, by using a new framework or imposing a quality gate). By considering that the outcome of any activity can be characterized as the product of impact and scale , in this paper we aim at exploring the impact of Technical Debt (TD) Macro-Management, whose scale is by definition larger than TD Micro-Management. By considering that TD artifacts reside at the micro-level, the problem calls for a nested model solution; i.e., modeling the structure of the problem: artifacts have some inherent characteristics (e.g., size and complexity), but obey the same project management rules (e.g., quality gates, CI/CD features, etc.). In this paper, we use the Under-Bagging based Generalized Linear Mixed Models approach, to unveil project management activities that are associated with the existence of HIGH_TD artifacts, through an empirical study on 100 open-source projects. The results of the study confirm that micro-management parameters are associated with the probability of a class to be classified as HIGH_TD, but the results can be further improved by controlling some project-level parameters. Based on the findings of our nested analysis, we can advise practitioners on macro-technical debt management approaches (such as “ control the number of commits per day ”, “ adopt quality control practices ”, and “ separate testing and development teams ”) that can significantly reduce the probability of all software artifacts to concentrate HIGH_TD. Although some of these findings are intuitive, this is the first work that delivers empirical quantitative evidence on the relation between TD values and project- or process-level metrics. |
URI: | https://doi.org/10.1109/TSE.2023.3237460 https://ruomo.lib.uom.gr/handle/7000/1561 |
ISSN: | 0098-5589 1939-3520 2326-3881 |
Αλλοι Προσδιοριστές: | 10.1109/TSE.2023.3237460 |
Εμφανίζεται στις Συλλογές: | Τμήμα Εφαρμοσμένης Πληροφορικής |
Αρχεία σε αυτό το Τεκμήριο:
Αρχείο | Περιγραφή | Μέγεθος | Μορφότυπος | |
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nikolaidis2023tse.pdf | 1,92 MB | Adobe PDF | Προβολή/Ανοιγμα |
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