MPLR 2021: Proceedings of the 18th ACM SIGPLAN International Conference on Managed Programming Languages and Runtimes
Sprache des Tagungstitel:
Englisch
Original Kurzfassung:
Programmers can use various data types when developing software. However, if the program is compiled to machine code, most of this type information is lost. If analysis of a compiled program is necessary, the lost data types have to be recovered again, to make the code understandable. Existing approaches for the type recovery problem require detailed knowledge about the CPU architecture in question. An architecture-agnostic approach is missing so far.
This work focuses on a truly architecture-agnostic type recovery algorithm, implemented in a dynamic analysis system. It can recover data types using minimal knowledge about the CPU architecture, therefore, making it easy to support many different CPU architectures in the analysis system.
Forschungs-