To compile, or not to compile, that is the question: When \textquoteright tis nobler to optimize for performance. Modern compilers have many different optimizations and optimization goals. A common one is to balance between peak performance and startup time. A new ahead-of-time compiled native executable that embeds a managed runtime tries to offer both, while solidifying the notion that everything should be compiled. However, the cost of an enlarged binary size raises the question whether it is beneficial to compile everything.

In this paper, we evaluate static heuristics from classical AOT compilers as well as other techniques based on our own observations. Our goal is to identify heuristics that work in a compilation-first environment and that allow us to reduce binary size while maintaining peak performance.

We compare the different policies in a closed-world hybrid execution system for Java, based on GraalVM Native Image, on a set of 5 DaCapo and 13 Renaissance benchmarks. We find that with the best combination of heuristics we can reduce binary size by $20%$ while slowing down average performance by only $4%$, but avoiding the need for any run-time feedback or complex machine-learning-based approaches. The most promising combination for production use combines heuristics based on early returns, estimated CPU cycles, number of parameters, and whether a method is a static initializer.