Abstract

Stipulations on the correctness of proofs produced in a formal system include that the axioms and proof rules are the intended ones and that the proof has been properly constructed (i.e. it is a correct instantiation of the axioms and proof rules.) In software implementations of formal systems, correctness additionally depends both on the correctness of the program implementing the system and on the hardware it is executed on. Once we implement a system in software and execute it on a computer, we have moved from the abstract world of mathematics into the physical world; absolute correctness can never be achieved here. We can only strive to increase our confidence that the system is producing correct results. In the process of creating proofs, foundational systems like Nuprl construct formal proof objects. These proof objects can be independently checked to verify they are correct instantiations of the axioms and proof rules thereby increasing confidence that the putative proof object faithfully represents a proof in the formal system. Note that this kind of proof checking does not address issues related to the models of the proof system, it simply provides more evidence that a proof has been correctly constructed. The Nuprl implementation consists of more than 100K lines of Lisp and tactic code implemented in ML. Although parts of the system consist of legacy codes going as far back as the late 1970's (Edinburgh LCF), and even though the Nuprl system has been extensively used since 1986 in formalizing a significant body of mathematics, the chances that the implementation is correct are slim. Verifying the system itself is infeasible, instead we propose to increase confidence in Nuprl proofs by independently checking them in ACL2. In this paper...

Citations