Engineering Software Systems with Self-Adaptation and Machine Learning KU Leuven
Modern software systems are often deployed in dynamic and uncertain environments, where the operating conditions of the system are difficult to predict before the system is in operation. Not attending to these uncertainties may jeopardize the system's goals. To mitigate such uncertainties, self-adaptation presents a consolidated approach that adapts software systems to changing operating conditions. With the increasing complexity of modern ...