HTTP Adaptive Streaming (HAS) has become the de-factor solution for multimedia delivery nowadays. Because of throughput variations, video adaptation methods are needed to avoid buffer underflows. In this context, it is also important to evaluate the overall video quality of a streaming session. Moreover, it is crucial to have a quality model that can evaluate different adaptation strategies in real time. In this talk, I will present recent developments in Quality of Experience (QoE) evaluation, modeling, and management. First I show how the quality-related histogram in a streaming session can be used to model the overall video quality. The model is devised for two cases, short videos and long videos. Then, our quality model is employed to evaluate, for the first time, the cumulative quality of typical adaptation methods in real time. Finally, I present a streaming solution, which employs a quality model in making decisions. The experiments show that this solution outperforms existing heuristic solutions for adaptive streaming.