Partitioning Interpolant-Based Verificationfor effective Unbounded Model Checking

Interpolant-based model checking has been shown to be effective on large verification instances, as it efficiently combines automated abstraction and reachability fixed-point checks. On the other hand, methods based on variable quantification have proved their ability to remove free inputs, thus projecting the search space over state variables. In this paper we propose an integrated approach which combines the abstraction power of interpolation with techniques that rely on AIG and/or BDD representations of states, directly supporting variable quantification and fixed-point checks. The underlying idea of this combination is to adopt AIG- or BDD-based quantifications to limit and restrict the search space and the complexity of the interpolant-based approach. The exploited strategies, most of which are individually well-known, are integrated with a new flavor, specifically designed to improve their effectiveness on difficult verification instances. Experimental results, specifically oriented to hard-to-solve verification problems, show the robustness of our approach

Automated abstraction by incremental refinement in interpolant-based model checking

Abstract—This paper addresses the field of Unbounded Model Checking (UMC) based on SAT engines, where Craig interpolants have recently gained wide acceptance as an automated abstraction technique. We start from the observation that interpolants can be quite effective on large verification instances. As they operate on SAT-generated refutation proofs, interpolants are very good at automatically abstract facts that are not significant for proofs. In this work, we push forward the new idea of generating abstractions without resorting to SAT proofs, and to accept (reject) abstractions whenever they (do not) fulfill given adequacy constraints. We propose an integrated approach smoothly combining the capabilities of interpolation with abstraction and over-approximation techniques, that do not directly derive from SAT refutation proofs. The driving idea of this combination is to incrementally generate, by refinement, an abstract (over-approximate) image, built up from equivalences, implications, ternary and localization abstraction, then (eventually) from SAT refutation proofs. Experimental results, derived from the verification of hard problems, show the robustness of our approach

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

p130Cas is an essential transducer element in ErbB2 transformation

The ErbB2 oncogene is often overexpressed in breast tumors and associated with poor clinical outcome. p130Cas represents a nodal scaffold protein regulating cell survival, migration, and proliferation in normal and pathological cells. The functional role of p130Cas in ErbB2-dependent breast tumorigenesis was assessed by its silencing in breast cancer cells derived from mouse mammary tumors overexpressing ErbB2 (N202-1A cells), and by its reexpression in ErbB2-transformed p130Cas-null mouse embryonic fibroblasts. We demonstrate that p130Cas is necessary for ErbB2-dependent foci formation, anchorage-independent growth, and in vivo growth of orthotopic N202-1A tumors. Moreover, intranipple injection of p130Cas-stabilized siRNAs in the mammary gland of Balbc-NeuT mice decreases the growth of spontaneous tumors. In ErbB2-transformed cells, p130Cas is a crucial component of a functional molecular complex consisting of ErbB2, c-Src, and Fak. In human mammary cells, MCF10A.B2, the concomitant activation of ErbB2, and p130Cas overexpression sustain and strengthen signaling, leading to Rac1 activation and MMP9 secretion, thus providing invasive properties. Consistently, p130Cas drives N202-1A cell in vivo lung metastases colonization. These results demonstrate that p130Cas is an essential transducer in ErbB2 transformation and highlight its potential use as a novel therapeutic target in ErbB2 positive human breast cancers.-Cabodi, S., Tinnirello, A., Bisaro, B., Tornillo, G., Camacho-Leal, M. P., Forni, G., Cojoca, R., Iezzi, M., Amici, A., Montani, M., Eva, A., Di Stefano, P., Muthuswamy, S. K., Tarone, G., Turco, E., Defilippi, P. p130Cas is an essential transducer element in ErbB2 transformation

More Scalable LTL Model Checking via Discovering Design-Space Dependencies (D3)

Modern system design often requires comparing several models over a large design space. Different models arise out of a need to weigh different design choices, to check core capabilities of versions with varying features, or to analyze a future version against previous ones. Model checking can compare different models; however, applying model checking off-the-shelf may not scale due to the large size of the design space for today’s complex systems. We exploit relationships between different models of the same (or related) systems to optimize the model-checking search. Our algorithm, D3 , preprocesses the design space and checks fewer model-checking instances, e.g., using nuXmv. It automatically prunes the search space by reducing both the number of models to check, and the number of LTL properties that need to be checked for each model in order to provide the complete model-checking verdict for every individual model-property pair. We formalize heuristics that improve the performance of D3 . We demonstrate the scalability of D3 by extensive experimental evaluation, e.g., by checking 1,620 real-life models for NASA’s NextGen air traffic control system. Compared to checking each model-property pair individually, D3 is up to 9.4 × faster

Androgen-Induced Cell Migration: Role of Androgen Receptor/Filamin A Association

Background: Androgen receptor (AR) controls male morphogenesis, gametogenesis and prostate growth as well as development of prostate cancer. These findings support a role for AR in cell migration and invasiveness. However, the molecular mechanism involved in AR-mediated cell migration still remains elusive. Methodology/Principal Findings: Mouse embryo NIH3T3 fibroblasts and highly metastatic human fibrosarcoma HT1080 cells harbor low levels of transcriptionally incompetent AR. We now report that, through extra nuclear action, AR triggers migration of both cell types upon stimulation with physiological concentrations of the androgen R1881. We analyzed the initial events leading to androgen-induced cell migration and observed that challenging NIH3T3 cells with 10 nM R1881 rapidly induces interaction of AR with filamin A (FlnA) at cytoskeleton. AR/FlnA complex recruits integrin beta 1, thus activating its dependent cascade. Silencing of AR, FlnA and integrin beta 1 shows that this ternary complex controls focal adhesion kinase (FAK), paxillin and Rac, thereby driving cell migration. FAK-null fibroblasts migrate poorly and Rac inhibition by EHT impairs motility of androgen-treated NIH3T3 cells. Interestingly, FAK and Rac activation by androgens are independent of each other. Findings in human fibrosarcoma HT1080 cells strengthen the role of Rac in androgen signaling. The Rac inhibitor significantly impairs androgen-induced migration in these cells. A mutant AR, deleted of the sequence interacting with FlnA, fails to mediate FAK activation and paxillin tyrosine phosphorylation in androgen-stimulated cells, further reinforcing the role of AR/FlnA interaction in androgen-mediated motility. Conclusions/Significance: The present report, for the first time, indicates that the extra nuclear AR/FlnA/integrin beta 1 complex is the key by which androgen activates signaling leading to cell migration. Assembly of this ternary complex may control organ development and prostate cancer metastasis