Codiagnosability and coobservability in discrete event systems where observations are dynamic are considered. Instead of having a fixed set of observable events, the observation of an event is dynamic (trace-dependent) in this paper. A procedure is developed to transform the problem of coobservability to the problem of codiagnosability in the context of dynamic observations. This proves that problems of coobservability are transformable to problems of codiagnosability and enables us to leverage the large literature available for codiagnosability to solve problems of coobservability. Furthermore, in the case of dynamic observations, the known polynomial-complexity tests for the property of codiagnosability based on verifier automata with fixed observable event set(s) are no longer directly applicable. A new testing procedure is developed that can handle transition-based dynamic observations and remains of polynomial complexity in the state space of the system. This new testing procedure employs a covering of the state space of the system based on cluster automata, which enhances its computational efficiency. Based on cluster automata, a new type of verifier automaton is built, called the C-VERIFIER, for verification of codiagnosability. As an application of the above mentioned transformation, the C-VERIFIER becomes a unified method for verifying both codiagnosability and coobservability.