An intelligent lighting system capable of runtime self-adaption to occupants behaviour is an example of a context-level application in which faulty operation has a strong and undesirable impact on the occupants comfort. Especially in cases where the long-term functioning of the systems is of interest, the systems quality should proof very high and therefore proper validation and verification practices are required. To our knowledge there is non an existent tool that deals with testing runtime self-adaptive systems. In this chapter we propose the implementation of a V&V framework previously introduced, by merging several already known tools. First, we give an understanding of ways to quantify and predict the reliability of large-scale distributed systems. Second, key performance indicators of the self-adaptive systems are identified from monitoring techniques and third, the test cases are formalized in a structured form. We present two test cases as examples of a system working under normal operation conditions as well as under induced conditions, based on real-life implementations. Execution of the test is lead by a test coordinator for which we used JSON notation, and then the interpretation and testing is carried out in a c++ toolbox where the monitoring and testing algorithms reside.