AUTOMATIC CODE SMELL DETECTION BASED ON INFORMATION EXTRACTED FROM THE TEXTUAL CONTENT OF THE CODE
DOI:
https://doi.org/10.24867/11BE01GrujicKeywords:
Natural language process, embedding, bert, word2vec, code smellsAbstract
Researches in the field of the automatic detection of code smells already exist. However, these researches generally take into account only a few types of code smells, and their detection is highly dependent on the programming language within which they are detected. In addition, most papers rely on structural metrics, and therefore it is necessary to define various thresholds in order to detect the code smells. Therefore, the results may vary on the projects over which it is detected for the reason that the threshold of these metrics must be defined separately for each project. In this paper, code smells is detected exclusively by information obtained from textual content - code. If used alone in the application, there is no need to define thresholds for various metrics, because the processing is done over natural language for each project separately.
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