Search Results for author:
Found 2 papers, 2 papers with code
Deep State Inference: Toward Behavioral Model Inference of Black-box Software Systems
Many software engineering tasks, such as testing, and anomaly detection can benefit from the ability to infer a behavioral model of the software. Most existing inference approaches assume access to code to collect execution sequences.
Hybrid Deep Neural Networks to Infer State Models of Black-Box Systems
Our comparison with several traditional time series change point detection techniques showed that our approach improves their performance by up to 102%, in terms of finding state change points, measured by F1 score.
Cannot find the paper you are looking for? You can
Submit a new open access paper.
