Object-Oriented Metrics in Practice - Using Software Metrics to Characterize, Evaluate, and Improve the Design of Object-Oriented Systems

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Metamodel Adaptation and Model Co-adaptation (2007, background): “How does structure smell? Works on object-oriented metrics [37,38,39] might be a good starting point for further research.”
On the diffuseness and the impact on maintainability of code smells: a large scale empirical investigation (2017, methodology): “Such tools exploitdifferenttypesofapproaches, including metrics-based detection (Lanza and Marinescu 2010; Moha et al. 2010; Marinescu 2004; Munro 2005), graph-based techniques (Tsantalis and Chatzigeorgiou 2009), mining of code changes (Palomba et al. 2015a), textual analysis of source code…”
When and Why Your Code Starts to Smell Bad (and Whether the Smells Go Away) (2017, positive): “Lanza and Marinescu [44] showed how to exploit quality metrics to identify “disharmony patterns” in code by deﬁning a set of thresholds based on the measurement of the exploited metrics in real software systems.”
An Empirical Study of Code Smells in Transformer-based Code Generation Techniques (2022, background): “Lanza and Marinescu [52] proposed a metric-based detection strategy to detect code smells.”