This paper addresses the modelling of requirements for a content Recommendation System (RS) for Online Social Networks (OSNs). On OSNs, a user switches roles constantly between content generator and content receiver. The goals and softgoals are different when the user is generating a post, as opposed as replying to a post. In other words, the user is generating instances of different entities, depending on the role she has: a generator generates instances of a "post", while the receiver generates instances of a "reply". Therefore, we believe that when addressing Requirements Engineering (RE) for RS, it is necessary to distinguish these roles clearly. We aim to model an essential dynamic on OSN, namely that when a user creates (posts) content, other users can ignore that content, or themselves start generating new content in reply, or react to the initial posting. This dynamic is key to designing OSNs, because it influences how active users are, and how attractive the OSN is for existing, and to new users. We apply a well-known Goal Oriented RE (GORE) technique, namely i-star, and show that this language fails to capture this dynamic, and thus cannot be used alone to model the problem domain. Hence, in order to represent this dynamic, its relationships to other OSNs' requirements, and to capture all relevant information, we suggest using another modelling language, namely Petri Nets, on top of i-star for the modelling of the problem domain. We use Petri Nets because it is a tool that is used to simulate the dynamic and concurrent activities of a system and can be used by both practitioners and theoreticians.
It is often the case that stakeholders want to strengthen weaken or otherwise change their requirements for a system-to-be when certain conditions apply at runtime. For example, stakeholders may decide that if requirement R is violated more than N times in a week, it should be relaxed to a less demanding one R-. Such evolution requirements play an important role in the lifetime of a software system in that they define possible changes to requirements, along with the conditions under which these changes apply. In this paper we focus on this family of requirements, how to model them and how to operationalize them at runtime. In addition, we evaluate our proposal with a case study adopted from the literature. Complexity is now one of the major challenges for the IT industry [1]. Systems might become too complex to be managed by humans and, thus, will have to be self-managed: Self-configure themselves for operation, self-protect from attacks, self-heal from errors and self-tune for optimal performance [2]. (Self-)Adaptive systems evaluate their own behavior and change it when the evaluation indicates that it is not accomplishing the software's purpose or when better functionality and performance are possible [3]. To that end, we need to monitor the behavior of the running system and compare it to an explicit formulation of requirements and domain assumptions [4]. Feedback loops (e.g., the MAPE loop [2]) constitute an architectural solution for this and, as proposed by past research [5], should be a first class citizen in the design of such systems. We advocate that adaptive systems should be designed this way from as early as Requirements Engineering and that reasoning over requirements is fundamental for run-time adaptation. We therefore propose an approach for the design of adaptive systems based on requirements and inspired in control theory [6]. Our proposal is goal-oriented and targets softwareintensive socio-technical systems [7], in an attempt to integrate control-loop approaches with decentralized agents inspired approaches [8]. Our final objective is a set of extensions to state-of-the-art goal-oriented modeling languages that allow practitioners to clearly specify the requirements of adaptive systems and a run-time framework that helps developers implement such requirements. In this 2-page abstract paper, we summarize this approach.