Bob Nystrom
920b3e2a32
Add lexer support for `TOKEN_INTERPOLATION` to split string literals at interpolation points, introduce `MAX_INTERPOLATION_NESTING` limit of 8, and compile interpolated strings by emitting calls to `String.interpolate_()`. Optimize list and map literal construction with new `addCore_` primitives to reduce stack churn. Update `String`, `List`, and `Map` `toString` methods in core library to use interpolation syntax, and migrate all benchmark and test files from explicit concatenation to interpolated strings.
The benchmarks in here attempt to faithfully implement the exact same algorithm in a few different languages. We're using Lua, Python, and Ruby for comparison here because those are all in Wren's ballpark: dynamically-typed, object-oriented, bytecode-compiled.
A bit about each benchmark:
binary_trees
This benchmark stresses object creation and garbage collection. It builds a few big, deeply nested binaries and then traverses them.
fib
This is just a simple naïve Fibonacci number calculator. It was the first benchmark I wrote when Wren supported little more than function calls and arithmetic. It isn't particularly representative of real-world code, but it does stress function call and arithmetic.
for
This microbenchmark just tests the performance of for loops. Not too useful, but i used it when implementing for in Wren to make sure it wasn't too far off the mark.
method_call
This is the most useful benchmark: it tests dynamic dispatch and polymorphism. You'll note that the main iteration loop is unrolled in all of the implementations. This is to ensure that the loop overhead itself doesn't dwarf the method call time.