IC3 is a famous bit-level framework for safety verification. By incorporating datapath abstraction, a notable enhancement in the efficiency of hardware verification can be achieved. However, datapath abstraction entails a coarse level of abstraction where all datapath operations are approximated as uninterpreted functions. This level of abstraction, albeit useful, can lead to an increased computational burden during the verification process as it necessitates extensive exploration of redundant abstract state space. In this paper, we introduce a novel approach called datapath propagation. Our method involves leveraging concrete constant values to iteratively compute the outcomes of relevant datapath operations and their associated uninterpreted functions. Meanwhile, we generate potentially useful datapath propagation lemmas in abstract state space and tighten the datapath abstraction. With this technique, the abstract state space can be reduced, and the verification efficiency is significantly improved. We implemented the proposed approach and conducted extensive experiments. The results show promising improvements of our approach compared to the state-of-the-art verifiers.

Automatically verifying multi-threaded programs is difficult because of the vast number of thread interleavings, a problem aggravated by weak memory consistency. Partial orders can help with verification because they can represent many thread interleavings concisely. However, there is no dedicated decision procedure for solving partial-order constraints. In this article, we propose a novel ordering consistency theory for concurrent program verification that is applicable not only under sequential consistency, but also under the TSO and PSO weak memory models. We further develop an efficient theory solver, which checks consistency incrementally, generates minimal conflict clauses, and includes a custom propagation procedure. We have implemented our approach in a tool, called Zord , and have conducted extensive experiments on the SV-COMP 2020 ConcurrencySafety benchmarks. Our experimental results show a significant improvement over the state-of-the-art.

Concurrent program verification is challenging due to a large number of thread interferences. A popular approach is to encode concurrent programs as SMT formulas and then rely on off-the-shelf SMT solvers to accomplish the verification. In most existing works, an SMT solver is simply treated as the backend. There is little research on improving SMT solving for concurrent program verification.

Abstract is an SMT-based multi-threaded program verification tool. It is built on top of (front-end) and (back-end). The basic idea of is to integrate into the SMT solver an ordering consistency theory that handles ordering relations over the shared variable accesses in the program. The front-end encodes the input program into an extended propositional formula that contains ordering constraints. The back-end is reinforced with a solver for the ordering consistency theory. This paper presents the basic idea, architecture, installation, and usage of .

The happens-before orders have been widely adopted to model thread interleaving behaviors of concurrent programs. A dedicated ordering theory solver, usually composed of theory propagation, consistency checking, and conflict clause generation, plays a central role in concurrent program verification. We propose a novel preventive reasoning approach that automatically preserves the ordering consistency and makes consistency checking and conflict clause generation omissible. We implement our approach in a prototype tool and conduct experiments on credible benchmarks; results reveal a significant improvement over existing state-of-the-art concurrent program verifiers.

Analyzing multi-threaded programs is hard due to the number of thread interleavings. Partial orders can be used for modeling and analyzing multi-threaded programs. However, there is no dedicated decision procedure for solving partial-order constraints. In this paper, we propose a novel ordering consistency theory for multi-threaded program verification under sequential consistency, and we elaborate its theory solver, which realizes incremental consistency checking, minimal conflict clause generation, and specialized theory propagation to improve the efficiency of SMT solving. We conducted extensive experiments on credible benchmarks; the results show significant promotion of our approach.

Patients of depression often have lower performance in perception, planning, and execution in cognition, compared to healthy controls. Depression has been reported to be associated with functional alterations in the resting state connectivity in the brain. This study investigates whether there are differences in neural dynamics measured by mental arithmetic tasks (MAT) between depressed and healthy subjects. To this end, this study employed an ROI-based functional connectivity analysis, within-condition interregional covariance analysis (WICA), to explore the correlates of the brain deactivation regions. Results of this study showed that the corresponding emotional loop is inhibited in healthy subjects and show the control loops of attention and emotion is inhibited in depressed subjects during MAT, and the patients with depression may produce a stronger stress response than the healthy subjects during the MAT. This may be the key reason for that the mathematical abilities of the depression subjects were inferior to that of the healthy subjects.