2,069 papers · page 17 of 104
Abstract Spot is a C++17 library for LTL and $$\omega $$ ω -automata manipulation, with command-line utilities, and Python bindings. This paper summarizes its evolution over the past six years, since the release of Spot 2.0, which was the first version to support $$\omega $$ ω -a…
Abstract Reasoning about data structures requires powerful logics supporting the combination of structural and data properties. We define a new logic called Mso-D(Monadic Second-Order logic with Data) as an extension of standard Mso on trees with predicates of the desired data lo…
Abstract Secure multi-party computation (MPC) is a promising technique for privacy-persevering applications. A number of MPC frameworks have been proposed to reduce the burden of designing customized protocols, allowing non-experts to quickly develop and deploy MPC applications. …
Abstract Compositional synthesis relies on the discovery of assumptions, i.e., restrictions on the behavior of the remainder of the system that allow a component to realize its specification. In order to avoid losing valid solutions, these assumptions should benecessaryconditions…
Abstract Existing neural network verifiers compute a proof that each input is handled correctly under a given perturbation by propagating a symbolic abstraction of reachable values at each layer. This process is repeated from scratch independently for each input (e.g., image) and…
Abstract In many synthesis problems, it can be essential to generate implementations which not only satisfy functional constraints but are also randomized to improve variety, robustness, or unpredictability. The recently-proposed framework of control improvisation (CI) provides t…
Abstract Quantified information flow (QIF) has emerged as a rigorous approach to quantitatively measure confidentiality; the information-theoretic underpinning of QIF allows the end-users to link the computed quantities with the computational effort required on the part of the ad…
Abstract We present a unified approach, implemented in the RINO tool, for the computation of inner and outer-approximations of reachable sets of discrete-time and continuous-time dynamical systems, possibly controlled by neural networks with differentiable activation functions. R…
Abstract M o G ym , is an integrated toolbox enabling the training and verification of machine-learned decision-making agents based on formal models, for the purpose of sound use in the real world. Given a formal representation of a decision-making problem in the JANI format and …
Abstract Due to the beyond-classical capability of quantum computing, quantum machine learning is applied independently or embedded in classical models for decision making, especially in the field of finance. Fairness and other ethical issues are often one of the main concerns in…
Abstract Many problems in program verification, Model Checking, and type inference are naturally expressed as satisfiability of a verification condition expressed in a fragment of First-Order Logic called Constrained Horn Clauses (CHC). This transforms program analysis and verifi…
Abstract We present the toolRankerfor complementing Büchi automata (BAs).Rankerbuilds on our previous optimizations of rank-based BA complementation and pushes them even further using numerous heuristics to produce even smaller automata. Moreover, it contains novel optimizations …
Abstract Loop invariant generation, which automates the generation of assertions that always hold at the entry of a while loop, has many important applications in program analysis and formal verification. In this work, we target an important category of while loops, namely affine…
Abstract Deep Reinforcement Learning (DRL) has demonstrated its strength in developing intelligent systems. These systems shall be formally guaranteed to be trustworthy when applied to safety-critical domains, which is typically achieved by formal verification performed after tra…
Abstract Reinforcement learning has been shown to be an effective strategy for automatically training policies for challenging control problems. Focusing on non-cooperative multi-agent systems, we propose a novel reinforcement learning framework for training joint policies that f…
Abstract Markov decision processes are a ubiquitous formalism for modelling systems with non-deterministic and probabilistic behavior. Verification of these models is subject to the famous state space explosion problem. We alleviate this problem by exploiting a hierarchical struc…
Abstract Requirements formalization has become increasingly popular in industrial settings as an effort to disambiguate designs and optimize development time and costs for critical system components. Formal requirements elicitation also enables the employment of analysis tools to…
Abstract We present LT-PDR, a lattice-theoretic generalization of Bradley’s property directed reachability analysis (PDR) algorithm. LT-PDR identifies the essence of PDR to be an ingenious combination of verification and refutation attempts based on the Knaster–Tarski and Kleene …
Abstract In this paper, we present the first fully-automated expected amortised cost analysis of self-adjusting data structures, that is, of randomised splay trees, randomised splay heaps and randomised meldable heaps, which so far have only (semi-)manually been analysed in the l…
Abstract The determinization of a nondeterministic Büchi automaton (NBA) is a fundamental construction of automata theory, with applications to probabilistic verification and reactive synthesis. The standard determinization constructions, such as the ones based on the Safra-Piter…