Transparency is a requirement that denotes the communication of information that should help audience to take informed decisions. The existing research on transparency in information systems usually focuses on the party who provides transparency and its inter-relation with other requirements such as privacy, security and regulatory requirements. Engineering transparency, however, also requires the analysis of the information receivers’ situation and their transparency requirements and the medium used to communicate and present the information. A holistic consideration of transparency will enhance its management and increase its usefulness. In this paper, we provide a novel engineering framework, consisting of a modelling language and nine analytical reasonings, which is meant to represent transparency requirements and detect a set of possible side-effects. Examples of such detections include detecting information overload, information starvation, and transparency leading to biased decisions. We then evaluate the modelling language through a case study and report the results.

Adaptivity is a capability that enables a system to choose amongst various alternatives to satisfy or maintain the satisfaction of certain requirements. The criteria of requirements satisfaction could be pragmatic and context-dependent. Contextual Goal Models (CGM) capture the power of context on banning or allowing certain alternatives to reach requirements (goals) and also deciding the quality of those alternatives with regards to certain quality measures (softgoals). It is used to depict facets of the decision making strategy and rationale of an adaptive system at the preliminary level of requirements. In this paper we argue the case for pragmatic requirements and extend the CGM with additional constructs to capture them and allow their analysis. We also develop an automated analysis which aids the planning and scheduling of tasks execution to meet pragmatic goals. Moreover, we evaluate our modelling and analysis regarding correctness and performance. Such an evaluation showed the applicability of the approach and its usefulness in aiding sensible decisions. It has also shown its capability to do so in a time short enough to suit run-time adaptation decision making.