The paper presents a comprehensive review of the research on computational methods of style change detection methods for intrinsic plagiarism detection. We systematically evaluate and summarize 120 research papers published between 2006 and 2024. We categorize the various methods of style change detection and examine papers devoted to related problems, such as style breach detection and author diarization. By compiling and analyzing information from the articles, we provide statistics on the key aspects of the solution pipeline. The assessment of datasets used in the articles, their languages and employed methods reveals trends in the field of intrinsic plagiarism detection along with changes in language and topic diversity. By using manually labeled keywords for the articles, our review also provides the list of most frequently used features and methods. We demonstrate that intrinsic plagiarism detection and style change detection are active research fields.