BioDefect First Dataset Defect Detection is a B.Tech project topic for Biotechnology & Biomedical Engineering. It gives students a clear starting point for research, implementation planning, and documentation.
BioDefect First Dataset Defect Detection Project Details
| Abstract |
The detection of software defects is a significant challenge in software engineering as a whole. While this issue is critical, previous studies have not examined the specific challenges related to defect detection within bioinformatics. The current datasets are not suitable for this domain, which limits their usefulness for constructing defect detection models. This paper presents BioDefect, the first dataset created to assist in defect detection for bioinformatics software. Additionally, BioDefect improves upon other datasets because it includes entire source code repositories. Other datasets typically include only code fragments, failing to provide the contextual information necessary for identifying defects in real-life contexts. BioDefect solves prevalent data quality problems, such as inconsistent
labeling and data leakage, which increases the reliability of experiments. The performance of BioDefect has been tested against nine different language models, including DeepSeek-R1. The results show that BioDefect significantly improves defect detection in bioinformatics software. Across all tested models, the average F1-score increased between 29.61% and 38.04%, demonstrating that BioDefect has great potential in this area.
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| Reference Paper |
BioDefect: The First Dataset for Defect Detection in Bioinformatics Software |
| Domain |
Biotechnology & Biomedical Engineering |
| Sub-Domain |
Bioinformatics Projects |
| PDF Download |
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| Get Help |
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