Automatic Text Simplification (ATS) is the process of reducing a text's l inguistic complexity to improve its understandability and readability while maintaining its original information, content, and meaning. Several text transformation operations can be performed such as splitting a sentence into several sh o rt er sentences, substitution of complex elements, and reorganization. It ha s been shown that the implementation of these operations essentially at a syntactic level causes several problems that co u l d b e solved by using semantic representations. In this paper, we present GRASS (GRAph-based Semantic representation for syntactic Simplification), a rule-based automatic syntactic simplification system that uses semantic representations. The system allows the syntactic transformation of complex constructions, such as subordination clauses, appositive clauses, coordination clauses, and passive forms into simpler sentences. It is based on graph-based meaning representation of the text expressed in DMRS (Dependency Minimal Recursion Semantics) notation and it uses rewriting rules. The experimental results obtained on a reference corpus and according to specific metrics outperform the results obt a i n ed by other state of the art systems on the same reference corpus.