553 research outputs found
Intersection and Rotation of Assumption Literals Boosts Bug-Finding
SAT-based techniques comprise the state-of-the-art in functional verification of safety-critical hardware and software, including IC3/PDR-based model checking and Bounded Model Checking (BMC). BMC is the incontrovertible best method for unsafety checking, aka bug-finding. Complementary Approximate Reachability (CAR) and IC3/PDR complement BMC for bug-finding by detecting different sets of bugs. To boost the efficiency of formal verification, we introduce heuristics involving intersection and rotation of the assumption literals used in the SAT encodings of these techniques. The heuristics generate smaller unsat cores and diverse satisfying assignments that help in faster convergence of these techniques, and have negligible runtime overhead. We detail these heuristics, incorporate them in CAR, and perform an extensive experimental evaluation of their performance, showing a 25% boost in bug-finding efficiency of CAR.We contribute a detailed analysis of the effectiveness of these heuristics: their influence on SAT-based bug-finding enables detection of different bugs from BMCbased checking. We find the new heuristics are applicable to IC3/PDR-based algorithms as well, and contribute a modified clause generalization procedure
Advanced Symbolic Analysis Tools for Fault-Tolerant Integrated Distributed Systems
The project aims to develop advanced model-checking algorithms and tools to automate the verification of fault-tolerant distributed systems for avionics. We present a new method called Property-Directed K-Induction (PD-KIND) for synthesizing K-inductive invariants of state-transition systems. PD-KIND builds upon Satifiability Modulo Theories (SMT) to generalize Bradley's IC3 method and its variants. This method is implemented in a new tool called SALLY. Case studies show that PD-KIND can automatically verify fault-tolerant algorithms under a variety of fault models and that SALLY is competitive with other SMT-based model checkers
Leveraging Datapath Propagation in IC3 for Hardware Model Checking
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
Proceedings of the 21st Conference on Formal Methods in Computer-Aided Design – FMCAD 2021
The Conference on Formal Methods in Computer-Aided Design (FMCAD) is an annual conference on the theory and applications of formal methods in hardware and system verification. FMCAD provides a leading forum to researchers in academia and industry for presenting and discussing groundbreaking methods, technologies, theoretical results, and tools for reasoning formally about computing systems. FMCAD covers formal aspects of computer-aided system design including verification, specification, synthesis, and testing
Fast algorithm for smoothing parameter selection in multidimensional generalized P-splines
A new computational algorithm for estimating the smoothing parameters of a multidimensional penalized
spline generalized model with anisotropic penalty is presented. This new proposal is based on the mixed
model representation of a multidimensional P-spline, in which the smoothing parameter for each
covariate is expressed in terms of variance components. On the basis of penalized quasi-likelihood
methods (PQL), closed-form expressions for the estimates of the variance components are obtained. This
formulation leads to an efficient implementation that can considerably reduce the computational load. The
proposed algorithm can be seen as a generalization of the algorithm by Schall (1991) - for variance
components estimation - to deal with non-standard structures of the covariance matrix of the random
effects. The practical performance of the proposed computational algorithm is evaluated by means of
simulations, and comparisons with alternative methods are made on the basis of the mean square error
criterion and the computing time. Finally, we illustrate our proposal with the analysis of two real datasets:
a two dimensional example of historical records of monthly precipitation data in USA and a three
dimensional one of mortality data from respiratory disease according to the age at death, the year of death
and the month of deathThe authors would like to express their gratitude for the support received in the form of the Spanish Ministry of Economy and Competitiveness grants MTM2011-28285-C02-01 and MTM2011-28285-C02-02. Work of Mar a Xose Rodríguez - Alvarez was supported by grant
CA09/0053 from the Instituto de Salud Carlos III. The research of Dae-Jin Lee was funded by an NIH grant for the Superfund Metal Mixtures, Biomarkers and Neurodevelopment project 1PA2ES016454-01A
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