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An AST is technically not sufficient for adding support for a new language / file format in SemanticDiff. ASTs often store information in an abstract format (e.g. a boolean to indicate whether a function is async) and don't expose which token in the text leads to this interpretation. We therefore work with Concrete Syntax Trees (CST), which have a 1:1 mapping for each input token to a corresponding node in the tree.
I glanced over the linked parser and it seems that it uses an AST and stores the location information only on a line-number granularity. This would not be sufficient for SemanticDiff. We would probably need a different parser to add support.
This use case has a potential market that goes beyond coding and programmers, but any organisation or individual working with documents.
They probably won't use VS Code or a GitHub App and we would need to provide a completely different frontend for such an audience 😉️.
Just out of curiosity, what is your use case for AsciiDoc?
I am pretty frustrated with standard document workflows involving PDF and MS Word.
It would be beyond amazing to be able to work in a documents-as-code fashion using AsciiDoc + SemanticDiff + MergeBoard, especially now that AsciiDoc is being standardised under the Eclipse Foundation.
This use case has a potential market that goes beyond coding and programmers, but any organisation or individual working with documents.
I hope it is feasible and not too difficult to implement; there are already parsers that produce the AST of an AsciiDoc file.
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