During model-based systems engineering or software engineering activities, diagrams representing use cases (sequence diagrams) and diagrams representing object behaviors (state machine diagrams or statecharts) can conflict with each other in what is called an inconsistency. Detecting these inconsistencies is crucial to check if a given specification is realizable through the behavior that was conceived to meet it. This paper provides a systematic literature review of inconsistency detection methods for UML state machine diagrams and sequence diagrams. The selection process is aided by an open-source machine-learning tool, and resulted in the qualitative synthesis of 27 works. The included publications offer methods to tackle the detection of horizontal-semantic behavior inconsistencies.