Software engineering phases and approaches have always targeted to deliver high-performance software designed to fulfill a certain task while optimizing criteria such as length and price. In this ...

Software testing is crucial for delivering high-quality software. Early identification of defects minimizes costs and reduces risks associated with late-stage detection. Software Defect Prediction ...

Model Training: Train the selected machine learning models on the preprocessed data to learn patterns and relationships between features and software defects. Model Evaluation: Assess the performance ...

When a customer uses the software, then it is possible to occur defects that can be removed in the updated versions of the software. Hence, in the present work, a robust examination of cross-project ...

In fact, early forms of machine learning have been used in metrology and inspection in fabs since the 1990s to pinpoint defects in chips and even predict problems using pattern-matching techniques.

Then, the software classified the defects into pre-defined categories, which were learned from training samples, according to IBM. The system, however, wasn’t fast enough, and it did not have enough ...

Researchers use machine learning to detect defects in additive manufacturing. ScienceDaily. Retrieved June 2, 2025 from www.sciencedaily.com / releases / 2024 / 06 / 240604132239.htm.

Abstract: Software engineering phases and approaches have always targeted to deliver high-performance software designed to fulfill a certain task while optimizing criteria such as length and price. In ...