Proving Hypersafety Compositionally

Hypersafety properties of arity $n$ are program properties that relate $n$ traces of a program (or, more generally, traces of $n$ programs). Classic examples include determinism, idempotence, and associativity. A number of relational program logics have been introduced to target this class of properties. Their aim is to construct simpler proofs by capitalizing on structural similarities between the $n$ related programs. We propose an unexplored, complementary proof principle that establishes hyper-triples (i.e. hypersafety judgments) as a unifying compositional building block for proofs, and we use it to develop a Logic for Hyper-triple Composition (LHC), which supports forms of proof compositionality that were not achievable in previous logics. We prove LHC sound and apply it to a number of challenging examples.Comment: 44 pages. Extended version of the OOPSLA'22 paper with the same title. Includes full proofs and case studies in appendix. v2 fixes typos in a derivatio

Outcome Logic: A Unifying Foundation for Correctness and Incorrectness Reasoning

Program logics for bug-finding (such as the recently introduced Incorrectness Logic) have framed correctness and incorrectness as dual concepts requiring different logical foundations. In this paper, we argue that a single unified theory can be used for both correctness and incorrectness reasoning. We present Outcome Logic (OL), a novel generalization of Hoare Logic that is both monadic (to capture computational effects) and monoidal (to reason about outcomes and reachability). OL expresses true positive bugs, while retaining correctness reasoning abilities as well. To formalize the applicability of OL to both correctness and incorrectness, we prove that any false OL specification can be disproven in OL itself. We also use our framework to reason about new types of incorrectness in nondeterministic and probabilistic programs. Given these advances, we advocate for OL as a new foundational theory of correctness and incorrectness

Strong Logic for Weak Memory: Reasoning About Release-Acquire Consistency in Iris (Artifact)

This artifact provides the soundness proofs for the encodings in Iris the RSL and GPS logics, as well as the verification for all standard examples known to be verifiable in those logics. All of these proofs are formalized in Coq, which is the main content of this artifact. The formalization is provided in a virtual machine for the convenience of testing, but can also be built from source

Logical Step-Indexed Logical Relations

Appel and McAllester's "step-indexed" logical relations have proven to be a simple and effective technique for reasoning about programs in languages with semantically interesting types, such as general recursive types and general reference types. However, proofs using step-indexed models typically involve tedious, error-prone, and proof-obscuring step-index arithmetic, so it is important to develop clean, high-level, equational proof principles that avoid mention of step indices. In this paper, we show how to reason about binary step-indexed logical relations in an abstract and elegant way. Specifically, we define a logic LSLR, which is inspired by Plotkin and Abadi's logic for parametricity, but also supports recursively defined relations by means of the modal "later" operator from Appel, Melli\`es, Richards, and Vouillon's "very modal model" paper. We encode in LSLR a logical relation for reasoning relationally about programs in call-by-value System F extended with general recursive types. Using this logical relation, we derive a set of useful rules with which we can prove contextual equivalence and approximation results without counting steps

BDNF signaling in the VTA links the drug-dependent state to drug withdrawal aversions

Drug administration to avoid unpleasant drug withdrawal symptoms has been hypothesized to be a crucial factor that leads to compulsive drug-taking behavior. However, the neural relationship between the aversive motivational state produced by drug withdrawal and the development of the drug-dependent state still remains elusive. It has been observed that chronic exposure to drugs of abuse increases brain-derived neurotrophic factor (BDNF) levels in ventral tegmental area (VTA) neurons. In particular, BDNF expression is dramatically increased during drug withdrawal, which would suggest a direct connection between the aversive state of withdrawal and BDNF-induced neuronal plasticity. Using lentivirus-mediated gene transfer to locally knock down the expression of the BDNF receptor tropomyosin-receptor-kinase type B in rats and mice, we observed that chronic opiate administration activates BDNF-related neuronal plasticity in the VTA that is necessary for both the establishment of an opiate-dependent state and aversive withdrawal motivation. Our findings highlight the importance of a bivalent, plastic mechanism that drives the negative reinforcement underlying addiction