Very relaxed concurrency memory models, like those of the Arm-A, RISC-V and IBM Power hardware architectures, underpin much of computing but break a fundamental intuition about programs, namely that syntactic program order and the reads-from relation always both induce order in the execution. Instead, out-of-order execution is allowed except where prevented by certain pairwise dependencies, barriers, or other synchronisation. This means that there is no notion of the ‘current’ state of the program, making it challenging to design (and prove sound) syntax-directed, modular reasoning methods like Hoare logics, as usable resources cannot implicitly flow from one program point to the next. We present AxSL, a family of separation logics for relaxed hardware memory models, and instantiate it on sequential consistency and on the Arm-A memory model. The Arm-A instance captures the fine-grained reasoning underpinning the low-overhead synchronisation idioms used by high-performance systems code. We mechanise AxSL in the Iris separation logic framework, illustrate it on key examples, and prove it sound with respect to the axiomatic memory model of Arm-A. By instantiating AxSL on different memory models, we demonstrate the generality of our approach, and show that it is largely generic in the axiomatic model and in the instruction-set semantics, offering a potential way forward for compositional reasoning for other models, and for the combination of production concurrency models and full-scale ISAs.

Notions of computation can be modeled by monads. Algebraic effects offer a characterization of monads in terms of algebraic operations and equational axioms, where operations are basic programming features, such as reading or updating the state, and axioms specify observably equivalent expressions. However, many useful programming features depend on additional mechanisms such as delimited scopes or dynamically allocated resources. Such mechanisms can be supported via extensions to algebraic effects including scoped effects and parameterized algebraic theories . We present a fresh perspective on scoped effects by translation into a variation of parameterized algebraic theories. The translation enables a new approach to equational reasoning for scoped effects and gives rise to an alternative characterization of monads in terms of generators and equations involving both scoped and algebraic operations. We demonstrate the power of our approach by way of equational characterizations of several known models of scoped effects.

We present a compositional denotational semantics for a functional language with first-class parallel composition and shared-memory operations whose operational semantics follows the Release/Acquire weak memory model (RA). The semantics is formulated in Moggi’s monadic approach and is based on Brookes-style traces. To do so we adapt Brookes’s traces to view-based machine for RA by Kang et al., and supplement Brookes’s mumble and stutter closure operations with additional operations, specific to RA. The latter provides a more nuanced understanding of traces that uncouples them from operational interrupted executions. We show that our denotational semantics is adequate and use it to validate various program transformations of interest. This is the first work to put weak memory models on the same footing as many other programming effects in Moggi’s standard monadic approach.

We present a logically principled foundation for systematizing, in a way that works with any computational effect and evaluation order, SMT constraint generation seen in refinement type systems for functional programming languages. By carefully combining a focalized variant of call-by-push-value, bidirectional typing, and our novel technique of value-determined indexes, our system generates solvable SMT constraints without existential (unification) variables. We design a polarized subtyping relation allowing us to prove our logically focused typing algorithm is sound, complete, and decidable. We prove type soundness of our declarative system with respect to an elementary domain-theoretic denotational semantics. Type soundness implies, relatively simply, the total correctness and logical consistency of our system. The relative ease with which we obtain both algorithmic and semantic results ultimately stems from the proof-theoretic technique of focalization.

Formally verifying system properties is one of the most effective ways of improving system quality, but its high manual effort requirements often render it prohibitively expensive. Tools that automate formal verification by learning from proof corpora to synthesize proofs have just begun to show their promise. These tools are effective because of the richness of the data the proof corpora contain. This richness comes from the stylistic conventions followed by communities of proof developers, together with the powerful logical systems beneath proof assistants. However, this richness remains underexploited, with most work thus far focusing on architecture rather than on how to make the most of the proof data. This article systematically explores how to most effectively exploit one aspect of that proof data: identifiers. We develop the Passport approach, a method for enriching the predictive Coq model used by an existing proof-synthesis tool with three new encoding mechanisms for identifiers: category vocabulary indexing, subword sequence modeling, and path elaboration. We evaluate our approach’s enrichment effect on three existing base tools: ASTactic, Tac, and Tok. In head-to-head comparisons, Passport automatically proves 29% more theorems than the best-performing of these base tools. Combining the three tools enhanced by the Passport approach automatically proves 38% more theorems than combining the three base tools. Finally, together, these base tools and their enhanced versions prove 45% more theorems than the combined base tools. Overall, our findings suggest that modeling identifiers can play a significant role in improving proof synthesis, leading to higher-quality software.

Safely writing high-performance concurrent programs is notoriously difficult. To aid developers, we introduce Armada, a language and tool designed to formally verify such programs with relatively little effort. Via a C-like language and a small-step, state-machine-based semantics, Armadagives developers the flexibility to choose arbitrary memory layout and synchronization primitives so that they are never constrained in their pursuit of performance. To reduce developer effort, Armadaleverages SMT-powered automation and a library of powerful reasoning techniques, including rely-guarantee, TSO elimination, reduction, and pointer analysis. All of these techniques are proven sound, and Armadacan be soundly extended with additional strategies over time. Using Armada, we verify five concurrent case studies and show that we can achieve performance equivalent to that of unverified code.

Blockchain platforms are coming into use for processing critical transactions among participants who have not established mutual trust. Many blockchains are programmable, supporting smart contracts , which maintain persistent state and support transactions that transform the state. Unfortunately, bugs in many smart contracts have been exploited by hackers. Obsidian is a novel programming language with a type system that enables static detection of bugs that are common in smart contracts today. Obsidian is based on a core calculus, Silica, for which we proved type soundness. Obsidian uses typestate to detect improper state manipulation and uses linear types to detect abuse of assets. We integrated a permissions system that encodes a notion of ownership to allow for safe, flexible aliasing. We describe two case studies that evaluate Obsidian’s applicability to the domains of parametric insurance and supply chain management, finding that Obsidian’s type system facilitates reasoning about high-level states and ownership of resources. We compared our Obsidian implementation to a Solidity implementation, observing that the Solidity implementation requires much boilerplate checking and tracking of state, whereas Obsidian does this work statically.

We present a precise correspondence between separation logic and a simple notion of predicate BI, extending the earlier correspondence given between part of separation logic and propositional BI. Moreover, we introduce the notion of a BI hyperdoctrine, show that it soundly models classical and intuitionistic first- and higher-order predicate BI, and use it to show that we may easily extend separation logic to higher-order . We also demonstrate that this extension is important for program proving, since it provides sound reasoning principles for data abstraction in the presence of aliasing.

We introduce Kleene algebra with tests, an equational system for manipulating programs. We give a purely equational proof, using Kleene algebra with tests and commutativity conditions, of the following classical result: every while program can be simulated by a while program with at most one while loop. The proof illustrates the use of Kleene algebra with tests and commutativity conditions in program equivalence proofs.