Since it revolves around algorithms, model complexity ... focuses primarily on automated machine learning and deep learning, covering IoT, network optimization, fraud detection, NLP, computer ...

We present a convolutional neural network model that can successfully identify bugs in C code. We trained our model using two complementary datasets: a machine-labeled dataset ... us to specialize and ...

His expertise includes deploying AI/ML models using frameworks ... with advanced threat detection measures. Padamati's prowess in automated machine learning techniques is critical to his advanced ...

Microsoft researchers have been working on a deep-learning model that was ... "In our case, we aim to train a bug detection model without using training data from real-life bugs," they note ...

In testing where the automated testing model would revert ... The development of machine learning systems in the QA process makes such early detection and bug fixing more streamlined and effective ...

Abstract: Duplicate Bug ... bug detection an important one in Software Engineering domain. However, an automated solution for the same is not quite accurate yet in practice, in spite of many reported ...