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The applicability of Rice's theorem with respect to static analysis or abstract interpretation is more complex than you implied. First, static analysis tools are largely pattern-oriented. Pattern matching is how they sidestep undecidability. These tools have their place, but they aren't trying to be the tooling you or the parent claim. Instead, they are more useful to enforce coding style. This can be used to help with secure software development practices, but only by enforcing idiomatic style. Bounded model checkers, on the other hand, are this tooling. They don't have to disprove Rice's theorem to work. In fact, they work directly with this theorem. They transform code into state equations that are run through an SMT solver. They are looking for logic errors, use-after-free, buffer overruns, etc. But, they also fail code for unterminated execution within the constraints of the simulation. If abstract interpretation through SMT states does not complete in a certain number of steps, then this is also considered a failure. The function or subset of the program only passes if the SMT solver can't find a satisfactory state that triggers one of these issues, through any possible input or external state. These model checkers also provide the ability for user-defined assertions, making it possible to build and verify function contracts. This allows proof engineers to tie in proofs about higher level properties of code without having to build constructive proofs of all of this code. Rust has its own issues. For instance, its core library is unsafe, because it has to use unsafe operations to interface with the OS, or to build containers or memory management models that simply can't be described with the borrow checker. This has led to its own CVEs. To strengthen the core library, core Rust developers have started using Kani -- a bounded model checker like those available for C or other languages. Bounded model checking works. This tooling can be used to make either C or Rust safer. It can be used to augment proofs of theorems built in a proof assistant to extend this to implementation. The overhead of model checking is about that of unit testing, once you understand how to use it. It is significantly less expensive to teach C developers how to model check their software using CBMC than it is to teach them Rust and then have them port code to Rust. Using CBMC properly, one can get better security guarantees than using vanilla Rust. Overall, an Ada + Spark, CBMC + C, Kani + Rust strategy coupled with constructive theory and proofs regarding overall architectural guarantees will yield equivalent safety and security. I'd trust such pairings of process and tooling -- regardless of language choice -- over any LLM derived solutions. |
I have occasionally used CBMC for isolated functions, but that must already put me in the top 0.1% of formal verification users.