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Model-based testing is a technique for automatically generating a set of test cases using models extracted from software artifacts. It is an approach that aims to improve software quality and reduce the costs inherent in the testing process. This book is intended for professionals, researchers, and students in the field of software engineering and aims to present TCG, a tool for generating and selecting functional and statistical test cases that accepts probabilistic and non-probabilistic models as input. The selection techniques provided are test purposes, random path, and most probable path. In addition, this book also presents the selection technique called minimum path probability, in which the tool selects test cases that have a probability of occurrence greater than or equal to a value specified by the user.