International audienceThis paper presents a non-intrusive method for Objective Caml code coverage analysis. While classic methods rewrite the source code to an instrumented version that will produce traces at runtime, our approach chooses not to rewrite the source code. Instead, we use a virtual machine to monitor instructions execution and produce traces. These low-level traces are used to create a machine code coverage report. Combined with control-flow debug information, they can be analyzed to produce a source code coverage report. The purpose of this approach is to make available a method to generate code coverage analysis with the same binary for testing and for production. Our customized virtual machine respects the same semantics as the original virtual machine; one of its original aspects is that it is implemented in the Objective Caml, the very language we build the tool for.This work is part of the Coverage project, which aims to develop open source tools for safety-critical embedded applications and their code generators
Objective Caml is a famous dialect of the ML family languages. It is well-known for its performance as a compiled programming language, notably thanks to its incremental generational automatic memory collection. However, for historical reasons, the latter was built for monocore processors. One consequence is the runtime library assumes there is effectively no more than one thread running at a time, which allows many optimisations for monocore architectures: very few thread mutexes are sufficient to prevent more than a single thread to run at a time. This makes memory allocation and collection quite easier. The way it was built makes it not possible to take advantage of now widespread multicore CPU architectures. This paper presents our feedback on removing Objective Caml's garbage collector and designing a "Stop-The-World Stop&Copy" garbage collector to permit threads to take advantage of multicore architectures.
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