Papers for

formal verification engineers

Papers whose findings have a practical use for this group, as judged from the abstract. Open a paper to read what it means in practice.

New proof simplifies weak normalization for propositional logic

Simplified proofs of Weak Normalization for propositional logic

Abstract: We present a new proof of weak normalization for intuitionistic natural deduction. The distinguishing features of this proof are that it works only with cuts rather than cut segments, provides explicit local rules for determining whether to contract a whole proof or reduce one of its subproofs, and in the latter case, which subproof to reduce. We also discuss a formalization of the entire proof in Lean, and present a deterministic algorithm for weak normalization.

Sun 13 SeptLogic in Computer Science
The gist
Logic proofs can sometimes get complicated, especially when trying to simplify or 'normalize' them. The authors found an easier way to show that any proof in a certain style of logic can be simplified. They do this by focusing on entire parts of the proof, rather than breaking them into smaller segments. They also created clear rules and a step-by-step method for this simplification, and showed it works by programming it in a computer language called Lean.
Open 2609.14314v1

Warrant theory explains how propositions gain logical acceptance

Warrant Theory

Abstract: In this paper, we develop warrant theory as a philosophical discipline concerned with the inferential legitimacy of propositions within logical analysis. Warrant theory reconceptualises logic as a normative framework governing the conditions under which propositions may be introduced, accepted, rejected, and inferentially employed. Warrant is understood as inferential entitlement and is distinguished from truth, belief, and other psychological attitudes, while its relation to inferential use and meaning is examined. Warrant-theoretic analysis is then developed as a systematic method for investigating how propositions acquire inferential standing, how that standing develops, and how inferential positions interact through relations of dependence, compatibility, incompatibility, and exclusion. Acceptance and rejection provide the bilateral vocabulary for representing positive and negative inferential positions and the consequences and commitments associated with them. Finally, these elements are brought together in a warrant-theoretic definition of logic as the formal and normative study of the conditions under which propositions may be legitimately accepted or rejected and of the inferential transitions that such legitimacy warrants. On this account, logical consequence and logical failure are understood through the presence, preservation, or absence of inferential entitlement, thus locating the philosophical subject matter of logic in the systematic governance of inferential legitimacy.

Thu 10 SeptLogic in Computer ScienceArtificial Intelligence
The gist
Logic is about when it’s right to accept or reject statements, but this paper looks at that from a new angle called warrant theory. Warrant means having good reasons to use statements in arguments, different from just believing something is true. The authors study how statements earn this right to be used logically and how accepting or rejecting them works together. They explain logic as the rules for when it’s proper to accept ideas and how those ideas connect or conflict with each other through reasoning.
Open 2609.11667v1

Optimising metamath proofs reduces human memory demand during checking

Optimising Metamath Proofs for Human Working Memory

Abstract: Mathematical proofs vary in legibility. While most proof optimisation techniques seek to minimise proof size, the strategic reordering of inferences can reduce the working memory demand of proof checking without altering overall size. Metamath serves as a prime case study for this approach: its verification architecture requires proof steps to be ordered in a manner that prioritises algorithmic efficiency over readability. In this paper, we introduce algorithms to minimise both peak and cumulative memory consumption, applying the latter as a novel proxy for sustained human cognitive effort. We achieve this by representing proofs as directed acyclic graphs and modelling their execution as a pebbling game. Finding an optimal ordering via brute force is computationally infeasible, so we use heuristics to provide approximations. We apply these algorithms across Metamath's ZFC set theory library and present case studies demonstrating how automated reordering systematically improves the presentation of formal mathematics.

Mon 7 SeptLogic in Computer Science
The gist
Mathematical proofs can be hard to follow, especially when checking each step. The authors focus on Metamath, a system where proofs are arranged mainly for quick computer checking, not human understanding. They created methods to reorder proof steps to lower the mental effort needed to follow them, without changing the proof size. Their approach models proofs as graphs and uses clever heuristics to find better step orders, improving readability while keeping proofs valid.
Open 2609.07097v1