Introducing HiveVM: tools built on modelling

HiveVM is a small family of developer tools with one idea in common: describe the model once, then generate everything that follows from it. A grammar becomes a parser. A folder of Markdown becomes a manual. A workflow definition becomes a build pipeline.

This post is a short tour of the toolkit and the thinking behind it.

One source of truth

Most toolchains drift because the same knowledge is written down in several places — once in the parser, once in the docs, once in the CI config. Each copy ages at its own pace. Modelling collapses those copies into a single declarative source.

Describe the intent once and let the tooling project it onto each target.

The three tools

The toolkit is intentionally small:

• Parser Generator — an LL(k) generator that emits a parser and a full AST for Java and C++ from one grammar.
• Manual Generator — turns a collection of CommonMark files into one coherent manual.
• Gradle Workflow — a single pipeline definition across heterogeneous build systems.

Each lives in its own public repository, so you can adopt one without the others.

A grammar, end to end

A grammar is just a declarative file. Here is a tiny expression language:

grammar Calc;

expr   : term (('+' | '-') term)* ;
term   : factor (('*' | '/') factor)* ;
factor : NUMBER | '(' expr ')' ;

NUMBER : [0-9]+ ('.' [0-9]+)? ;

Running the generator produces a parser plus AST nodes for every target you ask for:

hivevm-cc generate Calc.g --target java,cpp

That is the whole loop — edit the model, regenerate, ship. No boilerplate to keep in sync by hand.

Where to go next

Browse the repositories on GitHub or start with the parser generator. The next post digs into how LL(k) analysis actually decides what to generate.