PLA-based runtime dynamism in support of privacy-enhanced web personalization

Software product line architectures (PLAs) have been widely recognized as a successful approach in industrial software development for improving productivity, software quality and time-to-market. In this paper, we focus on the usage of a PLA for a quite different purpose, namely, handling privacy constraints in web personalization. To provide personalized services such as customized recommendations, a personalized website collects users' personal data, which raises various privacy concerns. We aim at reconciling the benefits of web personalization with privacy constraints that come from users themselves as well as from privacy legislations and regulations that apply to a given user. We propose a dynamic, privacyenabling personalization infrastructure and conceive it as a PLA. This infrastructure allows for dynamically selecting and instantiating personalization architectures that provide personalized services to each individual user and comply with the prevailing privacy constraints.