The book presents the theoretical foundations of the study of discrete computing systems using information methods. Based on the introduced information assessments and the developed method for information decomposition, the quality of computing structures and the efficiency of the computing process in them are determined. Information models of the main components of discrete computing systems, memories, and processors are proposed. An entropy balance of the computing process is proposed, which establishes a relationship between the parameters of the computing algorithm and the structure that implements it. With the help of statistical data from tested programs, the hypotheses based on information analysis about the relationships between operators, operands, length, execution time, and energy efficiency of programs are confirmed. The concluding part shows applications of the theoretical and informational approach presented for evaluating the size of integrated circuits according to a given description, the efficiency of microcontroller architectures, programming languages, and topologies of multiprocessor systems. The proposed definition of information in intuitionistic fuzzy processes is used to implement a method for load balancing in cloud computing. The book is of interest to scientists and doctoral students dealing with the problems of discrete computational processes and systems.