Engeln, UlrikeHerrmann, Andrea2024-02-222024-02-2220230720-8928https://dl.gi.de/handle/20.500.12116/43665Code smells are indicators for bad quality of source code. A well suited approach for the development of a smell detector are machine learning techniques that learn based on features, i.e., measurable properties of the software under investigation, e.g., code metrics. One major objective of our machine learning approach is to decide how to express information from the version history by features. we introduce a method to draw historical features that improve smell detection.encode smelldetectionversion historymachine learningcode metricsCode Smell Detection using Features from Version HistoryText/Conference Paper