23 research outputs found

    On Relaxing Metric Information in Linear Temporal Logic

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    Metric LTL formulas rely on the next operator to encode time distances, whereas qualitative LTL formulas use only the until operator. This paper shows how to transform any metric LTL formula M into a qualitative formula Q, such that Q is satisfiable if and only if M is satisfiable over words with variability bounded with respect to the largest distances used in M (i.e., occurrences of next), but the size of Q is independent of such distances. Besides the theoretical interest, this result can help simplify the verification of systems with time-granularity heterogeneity, where large distances are required to express the coarse-grain dynamics in terms of fine-grain time units.Comment: Minor change

    On Relaxing Metric Information in Linear Temporal Logic

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    This paper studies the equi-satisfiability of metric linear temporal logic (LTL) and its qualitative subset. Metric LTL formulas rely on the next operator to encode distances, whereas qualitative LTL formulas use only the until modality. The paper shows how to transform any metric LTL formula M into a qualitative one Q, such that Q and M are equi-satisfiable over words with variability bounded with respect to the largest distances used in M (i.e., occurrences of next), but the size of Q is independent of such distances. Besides the theoretical interest, these results may help simplify the verification of systems with time-granularity heterogeneity, where large distances are required to express the coarse-grain dynamic

    Robust Linear Temporal Logic

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    Although it is widely accepted that every system should be robust, in the sense that "small" violations of environment assumptions should lead to "small" violations of system guarantees, it is less clear how to make this intuitive notion of robustness mathematically precise. In this paper, we address this problem by developing a robust version of Linear Temporal Logic (LTL), which we call robust LTL and denote by rLTL. Formulas in rLTL are syntactically identical to LTL formulas but are endowed with a many-valued semantics that encodes robustness. In particular, the semantics of the rLTL formula φ⇒ψ\varphi \Rightarrow \psi is such that a "small" violation of the environment assumption φ\varphi is guaranteed to only produce a "small" violation of the system guarantee ψ\psi. In addition to introducing rLTL, we study the verification and synthesis problems for this logic: similarly to LTL, we show that both problems are decidable, that the verification problem can be solved in time exponential in the number of subformulas of the rLTL formula at hand, and that the synthesis problem can be solved in doubly exponential time

    Improving explicit model checking for Petri nets

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    Model checking is the automated verification that systematically checks if a given behavioral property holds for a given model of a system. We use Petri nets and temporal logic as formalisms to describe a system and its behavior in a mathematically precise and unambiguous manner. The contributions of this thesis are concerned with the improvement of model checking efficiency both in theory and in practice. We present two new reduction techniques and several supplementary strength reduction techniques. The thesis also enhances partial order reduction for certain temporal logic classes

    Being correct is not enough: efficient verification using robust linear temporal logic

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    While most approaches in formal methods address system correctness, ensuring robustness has remained a challenge. In this paper we present and study the logic rLTL which provides a means to formally reason about both correctness and robustness in system design. Furthermore, we identify a large fragment of rLTL for which the verification problem can be efficiently solved, i.e., verification can be done by using an automaton, recognizing the behaviors described by the rLTL formula φ\varphi, of size at most O(3∣φ∣)\mathcal{O} \left( 3^{ |\varphi|} \right), where ∣φ∣|\varphi| is the length of φ\varphi. This result improves upon the previously known bound of O(5∣φ∣)\mathcal{O}\left(5^{|\varphi|} \right) for rLTL verification and is closer to the LTL bound of O(2∣φ∣)\mathcal{O}\left( 2^{|\varphi|} \right). The usefulness of this fragment is demonstrated by a number of case studies showing its practical significance in terms of expressiveness, the ability to describe robustness, and the fine-grained information that rLTL brings to the process of system verification. Moreover, these advantages come at a low computational overhead with respect to LTL verification.Comment: arXiv admin note: text overlap with arXiv:1510.08970. v2 notes: Proof on the complexity of translating rLTL formulae to LTL formulae via the rewriting approach. New case study on the scalability of rLTL formulae in the proposed fragment. Accepted to appear in ACM Transactions on Computational Logi

    Formal Methods for Autonomous Systems

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    Formal methods refer to rigorous, mathematical approaches to system development and have played a key role in establishing the correctness of safety-critical systems. The main building blocks of formal methods are models and specifications, which are analogous to behaviors and requirements in system design and give us the means to verify and synthesize system behaviors with formal guarantees. This monograph provides a survey of the current state of the art on applications of formal methods in the autonomous systems domain. We consider correct-by-construction synthesis under various formulations, including closed systems, reactive, and probabilistic settings. Beyond synthesizing systems in known environments, we address the concept of uncertainty and bound the behavior of systems that employ learning using formal methods. Further, we examine the synthesis of systems with monitoring, a mitigation technique for ensuring that once a system deviates from expected behavior, it knows a way of returning to normalcy. We also show how to overcome some limitations of formal methods themselves with learning. We conclude with future directions for formal methods in reinforcement learning, uncertainty, privacy, explainability of formal methods, and regulation and certification

    Towards the Correctness of Software Behavior in UML: A Model Checking Approach Based on Slicing

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    Embedded systems are systems which have ongoing interactions with their environments, accepting requests and producing responses. Such systems are increasingly used in applications where failure is unacceptable: traffic control systems, avionics, automobiles, etc. Correct and highly dependable construction of such systems is particularly important and challenging. A very promising and increasingly attractive method for achieving this goal is using the approach of formal verification. A formal verification method consists of three major components: a model for describing the behavior of the system, a specification language to embody correctness requirements, and an analysis method to verify the behavior against the correctness requirements. This Ph.D. addresses the correctness of the behavioral design of embedded systems, using model checking as the verification technology. More precisely, we present an UML-based verification method that checks whether the conditions on the evolution of the embedded system are met by the model. Unfortunately, model checking is limited to medium size systems because of its high space requirements. To overcome this problem, this Ph.D. suggests the integration of the slicing (reduction) technique
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