Statistics-based optimization strategy
Process consists of a number of phases. Each phase provides a feedback on its performance.
Instead of defining some performance threshold for each phase to start optimization at and asking ourselves “when should we start optimizing this?”, we should rather ask ourselves “which phase is to be optimized now?”. That is, we should collect all feedback, sort it and start optimizing most important phases first. Naturally, we end the process when we are not getting any visible performance gains anymore.
This strategy can be applied to dynamic programming language runtime as well as to any other controllable process.