Trust and Reputation Systems (TRSs) represent a significant trend in decision support for Internet-based interactions. They help users to decide whom to trust and how much to trust a transaction. They are also an effective mechanism to encourage honesty and cooperation among users, resulting in healthy online markets or communities. The basic idea is to let parties rate each other so that new public knowledge can be created from personal experiences. The major difficulty in designing a reputation system is making it robust against malicious attacks. Our contribution in this paper is twofold. Firstly, we combine multiple research agendas into a holistic approach to building a robust TRS. Secondly, we focus on one TRS component which is the reputation computing engine and provide a novel investigation into an implementation of the engine proposed in [7].