TY - JOUR AB - The behaviour of gene regulatory networks (GRNs) is typically analysed using simulation-based statistical testing-like methods. In this paper, we demonstrate that we can replace this approach by a formal verification-like method that gives higher assurance and scalability. We focus on Wagner’s weighted GRN model with varying weights, which is used in evolutionary biology. In the model, weight parameters represent the gene interaction strength that may change due to genetic mutations. For a property of interest, we synthesise the constraints over the parameter space that represent the set of GRNs satisfying the property. We experimentally show that our parameter synthesis procedure computes the mutational robustness of GRNs—an important problem of interest in evolutionary biology—more efficiently than the classical simulation method. We specify the property in linear temporal logic. We employ symbolic bounded model checking and SMT solving to compute the space of GRNs that satisfy the property, which amounts to synthesizing a set of linear constraints on the weights. AU - Giacobbe, Mirco AU - Guet, Calin C AU - Gupta, Ashutosh AU - Henzinger, Thomas A AU - Paixao, Tiago AU - Petrov, Tatjana ID - 1351 IS - 8 JF - Acta Informatica SN - 00015903 TI - Model checking the evolution of gene regulatory networks VL - 54 ER - TY - JOUR AB - We define the . model-measuring problem: given a model . M and specification . ϕ, what is the maximal distance . ρ such that all models . M' within distance . ρ from . M satisfy (or violate) . ϕ. The model-measuring problem presupposes a distance function on models. We concentrate on . automatic distance functions, which are defined by weighted automata. The model-measuring problem subsumes several generalizations of the classical model-checking problem, in particular, quantitative model-checking problems that measure the degree of satisfaction of a specification; robustness problems that measure how much a model can be perturbed without violating the specification; and parameter synthesis for hybrid systems. We show that for automatic distance functions, and (a) . ω-regular linear-time, (b) . ω-regular branching-time, and (c) hybrid specifications, the model-measuring problem can be solved.We use automata-theoretic model-checking methods for model measuring, replacing the emptiness question for word, tree, and hybrid automata by the . optimal-value question for the weighted versions of these automata. For automata over words and trees, we consider weighted automata that accumulate weights by maximizing, summing, discounting, and limit averaging. For hybrid automata, we consider monotonic (parametric) hybrid automata, a hybrid counterpart of (discrete) weighted automata.We give several examples of using the model-measuring problem to compute various notions of robustness and quantitative satisfaction for temporal specifications. Further, we propose the modeling framework for model measuring to ease the specification and reduce the likelihood of errors in modeling.Finally, we present a variant of the model-measuring problem, called the . model-repair problem. The model-repair problem applies to models that do not satisfy the specification; it can be used to derive restrictions, under which the model satisfies the specification, i.e., to repair the model. AU - Henzinger, Thomas A AU - Otop, Jan ID - 1196 JF - Nonlinear Analysis: Hybrid Systems TI - Model measuring for discrete and hybrid systems VL - 23 ER - TY - CONF AB - Time-triggered switched networks are a deterministic communication infrastructure used by real-time distributed embedded systems. Due to the criticality of the applications running over them, developers need to ensure that end-to-end communication is dependable and predictable. Traditional approaches assume static networks that are not flexible to changes caused by reconfigurations or, more importantly, faults, which are dealt with in the application using redundancy. We adopt the concept of handling faults in the switches from non-real-time networks while maintaining the required predictability. We study a class of forwarding schemes that can handle various types of failures. We consider probabilistic failures. We study a class of forwarding schemes that can handle various types of failures. We consider probabilistic failures. For a given network with a forwarding scheme and a constant ℓ, we compute the {\em score} of the scheme, namely the probability (induced by faults) that at least ℓ messages arrive on time. We reduce the scoring problem to a reachability problem on a Markov chain with a "product-like" structure. Its special structure allows us to reason about it symbolically, and reduce the scoring problem to #SAT. Our solution is generic and can be adapted to different networks and other contexts. Also, we show the computational complexity of the scoring problem is #P-complete, and we study methods to estimate the score. We evaluate the effectiveness of our techniques with an implementation. AU - Avni, Guy AU - Goel, Shubham AU - Henzinger, Thomas A AU - Rodríguez Navas, Guillermo ID - 1116 SN - 03029743 TI - Computing scores of forwarding schemes in switched networks with probabilistic faults VL - 10206 ER - TY - JOUR AB - Simulation is an attractive alternative to language inclusion for automata as it is an under-approximation of language inclusion, but usually has much lower complexity. Simulation has also been extended in two orthogonal directions, namely, (1) fair simulation, for simulation over specified set of infinite runs; and (2) quantitative simulation, for simulation between weighted automata. While fair trace inclusion is PSPACE-complete, fair simulation can be computed in polynomial time. For weighted automata, the (quantitative) language inclusion problem is undecidable in general, whereas the (quantitative) simulation reduces to quantitative games, which admit pseudo-polynomial time algorithms. In this work, we study (quantitative) simulation for weighted automata with Büchi acceptance conditions, i.e., we generalize fair simulation from non-weighted automata to weighted automata. We show that imposing Büchi acceptance conditions on weighted automata changes many fundamental properties of the simulation games, yet they still admit pseudo-polynomial time algorithms. AU - Chatterjee, Krishnendu AU - Henzinger, Thomas A AU - Otop, Jan AU - Velner, Yaron ID - 1066 IS - 2 JF - Information and Computation TI - Quantitative fair simulation games VL - 254 ER - TY - CONF AB - Pushdown systems (PDSs) and recursive state machines (RSMs), which are linearly equivalent, are standard models for interprocedural analysis. Yet RSMs are more convenient as they (a) explicitly model function calls and returns, and (b) specify many natural parameters for algorithmic analysis, e.g., the number of entries and exits. We consider a general framework where RSM transitions are labeled from a semiring and path properties are algebraic with semiring operations, which can model, e.g., interprocedural reachability and dataflow analysis problems. Our main contributions are new algorithms for several fundamental problems. As compared to a direct translation of RSMs to PDSs and the best-known existing bounds of PDSs, our analysis algorithm improves the complexity for finite-height semirings (that subsumes reachability and standard dataflow properties). We further consider the problem of extracting distance values from the representation structures computed by our algorithm, and give efficient algorithms that distinguish the complexity of a one-time preprocessing from the complexity of each individual query. Another advantage of our algorithm is that our improvements carry over to the concurrent setting, where we improve the bestknown complexity for the context-bounded analysis of concurrent RSMs. Finally, we provide a prototype implementation that gives a significant speed-up on several benchmarks from the SLAM/SDV project. AU - Chatterjee, Krishnendu AU - Kragl, Bernhard AU - Mishra, Samarth AU - Pavlogiannis, Andreas ED - Yang, Hongseok ID - 1011 SN - 03029743 TI - Faster algorithms for weighted recursive state machines VL - 10201 ER -