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https://ruomo.lib.uom.gr/handle/7000/1561
Πλήρης εγγραφή μεταδεδομένων
Πεδίο DC | Τιμή | Γλώσσα |
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dc.contributor.author | Nikolaidis, Nikolaos | - |
dc.contributor.author | Mittas, Nikolaos | - |
dc.contributor.author | Ampatzoglou, Apostolos | - |
dc.contributor.author | Arvanitou, Elvira-Maria | - |
dc.contributor.author | Chatzigeorgiou, Alexander | - |
dc.date.accessioned | 2023-02-01T13:40:02Z | - |
dc.date.available | 2023-02-01T13:40:02Z | - |
dc.date.issued | 2023-01-23 | - |
dc.identifier | 10.1109/TSE.2023.3237460 | en_US |
dc.identifier.issn | 0098-5589 | en_US |
dc.identifier.issn | 1939-3520 | en_US |
dc.identifier.issn | 2326-3881 | en_US |
dc.identifier.uri | https://doi.org/10.1109/TSE.2023.3237460 | en_US |
dc.identifier.uri | https://ruomo.lib.uom.gr/handle/7000/1561 | - |
dc.description.abstract | 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. | en_US |
dc.language.iso | en | en_US |
dc.source | IEEE Transactions on Software Engineering | en_US |
dc.subject | FRASCATI::Natural sciences::Computer and information sciences | en_US |
dc.subject.other | Technical Debt | en_US |
dc.subject.other | Metrics | en_US |
dc.subject.other | Measurement | en_US |
dc.subject.other | Quality Analysis and Evaluation | en_US |
dc.subject.other | Software maintenance | en_US |
dc.title | Assessing TD Macro-Management: A Nested Modelling Statistical Approach | en_US |
dc.type | Article | en_US |
dc.contributor.department | Τμήμα Εφαρμοσμένης Πληροφορικής | en_US |
local.identifier.firstpage | 1 | en_US |
local.identifier.lastpage | 13 | en_US |
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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