Many concurrent or parallel programming languages rely on runtime checking to ensure safety. To implement such a language on a virtual machine (VM), such runtime checks are often implemented in a VM-independent way, using source-to-source translation or bytecode instrumentation. This approach avoids modifying complex VM components like the just-in-time (JIT) compiler and offers great portability. However, obtaining good performance is challenging, as the approach cannot profit from custom JIT optimizations to eliminate redundant checks.

In this paper, we present and evaluate two techniques to make the VM-independent approach efficient, using the example of a parallel programming language called Rolez. To guarantee that concurrent threads do not interfere, Rolez relies heavily on runtime checks: for every field access, the runtime system checks that the state of the target object currently permits this operation (unless the check is optimized away). The Rolez compiler we present here generates standard Java source code and the runtime system is implemented as a Java library. Nevertheless, many Rolez programs deliver performance roughly on par with manually synchronized Java implementations, which is achieved using these two techniques: 1) code-managed runtime data, which improves runtime check efficiency by passing performance-critical information from method to method, and 2) an interprocedural but modular concurrency analysis, which eliminates many runtime checks that are actually redundant.