Harnessing Big Data Analytics and Deep Learning for Predictive Bug Finding and Test Automation in Complex Embedded Software Systems

Abstract

Deep learning and data large analytics form a powerful combination for predictive prediction of bugs in the complicated embedded systems and for automated test. We confirm that such approaches can achieve good accuracy and efficiency in comparison with conventional methods. This work is based on the finding of which is to encourage adoption of AI driven testing strategies that form a foundation for future software reliability and intelligent defect management innovations in safety critical and larger scale embedded applications.