SBST in the Age of Machine Learning Systems - Challenges Ahead

摘要

Machine Learning, and especially Deep Neural Network (DNN), is being rapidly adopted by various software systems, including applications in safety-critical systems such as autonomous driving and medical imaging. This calls for an urgent need to test these AI/ML techniques as part of larger systems. However, this task can be very different from testing of traditional software systems. We will briefly examine the fundamentals of software testing as well as the state of the art in Search Based Software Testing (SBST), and try to outline the challenges ahead while highlighting areas where SBST can shine.