1,721,163 research outputs found
ARCH-COMP24 Category Report:Continuous and Hybrid Systems with Linear Continuous Dynamics
Full text linkWe present the results of the ARCH 2024 friendly competition for formal verification of continuous and hybrid systems with linear continuous dynamics. In its eighth edition, two tools participated to solve eight different benchmark problems in the category for linear continuous dynamics (in alphabetical order): CORA and JuliaReach. This report is a snapshot of the current landscape of tools and the types of benchmarks they are particularly suited for. Due to the diversity of problems, we are not ranking tools.</p
ARCH-COMP23 category report:Continuous and hybrid systems with linear continuous dynamics
Full text linkWe present the results of the ARCH 2023 friendly competition for formal verification of continuous and hybrid systems with linear continuous dynamics. In its seventh edition, three tools participated to solve nine different benchmark problems in the category for linear continuous dynamics (in alphabetical order): CORA, JuliaReach, and Verse. This report is a snapshot of the current landscape of tools and the types of benchmarks they are particularly suited for. Due to the diversity of problems, we are not ranking tools, yet the presented results provide one of the most complete assessments of tools for the safety verification of continuous and hybrid systems with linear continuous dynamics up to this date
ARCH-COMP23 category report:Artificial intelligence and neural network control systems (AINNCS) for continuous and hybrid systems plants
Full text linkThis report presents the results of a friendly competition for formal verification of continuous and hybrid systems with artificial intelligence (AI) components. Specifically, machine learning (ML) components in cyber-physical systems (CPS), such as feedforward neural networks used as feedback controllers in closed-loop systems, are considered, which is a class of systems classically known as intelligent control systems, or in more modern and specific terms, neural network control systems (NNCS). We broadly refer to this category as AI and NNCS (AINNCS). The friendly competition took place as part of the workshop Applied Verification for Continuous and Hybrid Systems (ARCH) in 2023. In the fifth edition of this AINNCS category at ARCH-COMP, three tools have been applied to solve ten different benchmark problems, which are CORA, JuliaReach and NNV. In reusing the benchmarks from the last iteration, we demonstrate the continuous progress in developing these tools: Two out of three tools can verify more instances than in the 2022 iteration. A novelty of this year's iteration is the shared computation hardware that allows for a fairer comparison among the participants
ARCH-COMP22 category report: Continuous and hybrid systems with linear continuous dynamics
No full textWe present the results of the ARCH 2022 friendly competition for formal verification of continuous and hybrid systems with linear continuous dynamics. In its sixth edition, two tools have been applied to solve nine different benchmark problems in the category for linear continuous dynamics (in alphabetical order): CORA and JuliaReach. This report is a snapshot of the current landscape of tools and the types of benchmarks they are particularly suited for. Due to the diversity of problems, we are not ranking tools, yet the presented results provide one of the most complete assessments of tools for the safety verification of continuous and hybrid systems with linear continuous dynamics up to this date
ARCH-COMP20 Category Report: Stochastic Models
No full textThis report presents the results of a friendly competition for formal verification andpolicy synthesis of stochastic models. It also introduces new benchmarks within thiscategory, and recommends next steps for this category towards next year's edition of the competition. The friendly competition took place as part of the workshop Applied Verification for Continuous and Hybrid Systems (ARCH) in Spring/Summer 2020.Virtual/online event due to COVID-19Air Transport & Operation
ARCH-COMP21 Category Report: Stochastic Models
No full textThis report presents the results of a friendly competition for formal verification andpolicy synthesis of stochastic models. It also introduces new benchmarks within this category, and recommends next steps for this category towards next year's edition of the competition. The friendly competition took place as part of the workshop Applied Verification for Continuous and Hybrid Systems (ARCH) in Spring/Summer 2021.Air Transport & Operation
ARCH-COMP22 Category Report: Stochastic Models
No full textThis report presents the results of a friendly competition for formal verification and policy synthesis of stochastic models. It also introduces new benchmarks and their properties within this category and recommends next steps for this category towards next year’s edition of the competition. In comparison with tools on non-probabilistic models, the tools for stochastic models are at the early stages of development that do not allow full competition on a standard set of benchmarks. We report on an initiative to collect a set of minimal benchmarks that all such tools can run, thus facilitating the comparison between efficiency of the implemented techniques. The friendly competition took place as part of the workshop Applied Verification for Continuous and Hybrid Systems (ARCH) in Summer 2022.Air Transport & Operation
ARCH-COMP24 Category Report:Artificial Intelligence and Neural Network Control System (AINNCS) for Continuous and Hybrid Systems Plants
Full text linkThis report presents the results of a friendly competition for formal verification of continuous and hybrid systems with artificial intelligence (AI) components. Specifically, machine learning (ML) components in cyber-physical systems (CPS), such as feedforward neural networks used as feedback controllers in closed-loop systems, are considered, which is a class of systems classically known as intelligent control systems, or in more modern and specific terms, neural network control systems (NNCS). We broadly refer to this category as AI and NNCS (AINNCS). The friendly competition took place as part of the workshop Applied Verification for Continuous and Hybrid Systems (ARCH) in 2024. In the 8th edition of this AINNCS category at ARCH-COMP, five tools have been applied to solve 12 benchmarks, which are CORA, CROWN-Reach, GoTube, JuliaReach, and NNV. This is the year with the largest interest in the community, with two new, and three previous participants. Following last year’s trend, despite the additional challenges presented, the verification results have improved year-over-year. In terms of computation time, we can observe that the previous participants have improved as well, showing speed-ups of up to one order of magnitude, such as JuliaReach on the TORA benchmark with ReLU controller, and NNV on the TORA benchmark with both heterogeneous controllers.</p
ARCH-COMP18 Category Report: Stochastic Modelling
Full text linkThis report presents the results of a friendly competition for formal verification and policy synthesis of stochastic models. The friendly competition took place as part of the workshop Applied Verification for Continuous and Hybrid Systems (ARCH) in 2018. In this first edition, we present five benchmarks with different levels of complexities and stochastic favours. We make use of six different tools and frameworks (in alphabetical order): Barrier Certificates, FAUST2, FIRM-GDTL, Modest, SDCPN modelling & MC simulation and SReachTools; and attempt to solve instances of the five different benchmark problems. Through these benchmarks, we capture a snapshot on the current state-of the art tools and frameworks within the stochastic modelling domain. We also present the challenges encountered within this domain and highlight future plans which will push forward the development of more tools and methodologies for performing formal verification and optimal policy synthesis of stochastic processes.Air Transport & Operation
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