Supplemental Material | Human-level Ordinal Maintainability Prediction Based on Static Code Metrics

Supplemental Material for the paper Markus Schnappinger, Arnaud Fietzke, and Alexander Pretschner. 2021. Human-level Ordinal Maintainability Prediction Based on Static Code Metrics. In Evaluation and Assessment in Software Engineering (EASE 2021). Association for Computing Machinery, New York, NY, U...

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Hauptverfasser: Schnappinger, Markus, Fietzke, Arnaud, Pretschner, Alexander
Format: Dataset
Sprache:eng
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Zusammenfassung:Supplemental Material for the paper Markus Schnappinger, Arnaud Fietzke, and Alexander Pretschner. 2021. Human-level Ordinal Maintainability Prediction Based on Static Code Metrics. In Evaluation and Assessment in Software Engineering (EASE 2021). Association for Computing Machinery, New York, NY, USA, 160–169. DOI: https://doi.org/10.1145/3463274.3463315Contents:- Complete list of all static metrics and used tools in metrics.md- Complete list of features ranked by their importance ranking (Table 2 in the paper) in ranking.csv- Exact configurations, i.e. hyper-parameters, preprocessing, selected features, used to achieve the reported results (Table 3 in the paper) in configurations.csv
DOI:10.6084/m9.figshare.14102843