Bytecode-to-Source Mapping
This article explains the technical implementation of bytecode-to-source mapping in virtual machines. It details how to optimize memory usage when tracking source line numbers for debugging purposes using run-length encoding.
Why it matters
Understanding efficient data structures for bytecode mapping is essential for developers building compilers, interpreters, and virtual machines.
I encountered this problem while working through the challenges in chapter 14 of Robert Nystrom’s Crafting Interpreters .
Note: Production VMs are more sophisticated, though I’ll share how this is similar to other VMs like JVM and Lua at the end of this post .
The first half of the book implements a toy language, jlox, from the top down, starting with lexing and parsing to build an AST and then interpreting it. The second half re-implements the same language but from the bottom up, beginning with the bytecode structure.
It stores bytecode in a chunk , which contains a sequence of bytes. Each byte is either an opcode or an operand belonging to an opcode. Instructions can therefore occupy different numbers of bytes. For example, OP_RETURN is a single byte, while OP_CONSTANT is followed by an operand containing an index into the chunk’s constant pool:
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