I agree, that if you want to write a production grade parser, this is probably the best way to go. I also agree that parsing is not a solved problem for all cas

I agree, that if you want to write a production grade parser, this is probably the best way to go. I also agree that parsing is not a solved problem for all cases. But that is the case with many more problems. However, for many cases it is a solved problem and that often it is not the first thing you should focus on to optimize. If you teach a course about compiler construction, I think it might be better to teach your students how to write a grammar for some language and use some interactive parser that can parse some input according to the grammar (and visualize the AST). See for example: [1] and [2] (Even if you feed it the C grammar, it succeeds parsing thousands of lines (preprocessed) C code at every keystroke. This interpreting parser is written in JavaScript and uses a simple caching strategy for performance improvement.) For the scripting language [3] in some of the Bizzdesigns modeling tools, a similar interactive parser was used (implemented in C++). This scripting language is also internally used for implementing the various meta-models. These scripts are parsed once, cached, and interpreted often. I think it is also true for many domain-specific languages (DSL). [1] https://info.itemis.com/demo/agl/editor https://info.itemis.com/demo/agl/editor [2] https://fransfaase.github.io/MCH2022ParserWorkshop/IParseStudio.html https://fransfaase.github.io/MCH2022ParserWorkshop/IParseStu... [3] https://help.bizzdesign.com/articles/#!horizzon-help/the-scripting-language https://help.bizzdesign.com/articles/#!horizzon-help/the-scr...