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Katarina-Glorija Grujić

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  1. Automatic detection of code smells using metrics and CodeT5 embeddings: a case study in C#

    2022

    Code smells are code structures that harm the software’s quality. An obstacle to developing automatic detectors is the available datasets’ limitations. Furthermore, researchers developed many solutions for Java while neglecting other programming languages. Recently, we …

  2. Semi-supervised detection of Long Method and God Class code smells

    2022

    Code smells are poorly designed parts of code whose removal is essential for sustainable software development. However, recognizing code smells in practice is challenging. Machine Learning (ML)-based code smell detectors could solve this problem. Current …