Domain-specific languages (DSLs) are frequently used in software engineering. In contrast to general-purpose languages, DSLs are designed for a special purpose in a particular domain. Due to volatile user requirements and new technologies DSLs, similar to the software systems they describe or produce, are subject to continuous evolution. This work explores existing research on DSL evolution to summarize, structure and analyze this area of research, and to identify trends and open issues. We conducted a systematic mapping study and identified 98 papers as potentially relevant for our study. By applying inclusion and exclusion criteria we selected a set of 34 papers relevant for DSL evolution. We classified and analyzed these papers to create a map of the research field. We conclude that DSL evolution is a topic of increasing relevancy. However, research on language evolution so far did not focus much on the characteristics DSLs exhibit. Also, there are not many cross-references between our primary studies meaning researchers are often not aware of potentially useful work. Our study results help researchers and practitioners working on DSL-based approaches to get an overview of existing research on DSL evolution and open challenges.

Information Extraction (IE)-the problem of extracting structured information from unstructured text - has become the key enabler for many enterprise applications such as semantic search, business analytics and regulatory compliance. While rule-based IE systems are widely used in practice due to their well-known "explainability," developing high-quality information extraction rules is known to be a labor-intensive and time-consuming iterative process.