Due to the huge size of modeling initiatives in practice, many companies struggle with assuring the quality of their process model collections. While many model properties can already be checked automatically, there is a notable gap concerning techniques for checking linguistic aspects such as naming conventions for process model elements. In this chapter, we aim at closing this gap by introducing techniques for automatically detecting and correcting linguistic guideline violations. The presented approaches build on the parsing techniques defined in the last chapter and facilitate a reliable and flexible detection and correction of guideline violations.