Text simplification is a Natural Language Processing (NLP) task whose aim is to reduce the complexity of the text while preserving its semantic content in order to facilitate the readers' comprehension. This task is relevant to many applications. For instance, it is beneficial to a broader range of readers like language learners, children, and people with cognitive disabilities. It can also be used as a preprocessing step for other NLP tasks such as parsing, semantic role labeling, machine translation, and summarization. Text simplification may manipulate several linguistic layers such as syntax, lexical, etc. and multiple researches are done regarding each aspect consequently. In this talk, I will outline how text simplification has developed over recent years and the major subjects that are of relevance in this topic.