A storm is Coming: A Modern Probabilistic Model Checker
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Abstract (arXiv)
We launch the new probabilistic model checker storm. It features the analysis of discrete- and continuous-time variants of both Markov chains and MDPs. It supports the PRISM and JANI modeling languages, probabilistic programs, dynamic fault trees and generalized stochastic Petri nets. It has a modular set-up in which solvers and symbolic engines can easily be exchanged. It offers a Python API for rapid prototyping by encapsulating storm's fast and scalable algorithms. Experiments on a variety of benchmarks show its competitive performance.
Key facts. Cited by 34 papers in the map (data through 7 Oct 2026). First posted on arXiv 14 Feb 2017.
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Citing papers per year: 2021: 9; 2022: 6; 2023: 4; 2024: 2; 2025: 5; 2026: 8.
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- 2022COOL-MC: A Comprehensive Tool for Reinforcement Learning and Model Checkingcited by 19
- 2022Online Shielding for Reinforcement Learningcited by 19
- 2021dtControl 2.0: Explainable Strategy Representation via Decision Tree Learning Steered by Expertscited by 14
- 2021Convex Optimization for Parameter Synthesis in MDPscited by 8
- 2023Bayesian Learning for the Robust Verification of Autonomous Robotscited by 6
- 2022Algebraically Explainable Controllers: Decision Trees and Support Vector Machines Join Forcescited by 5
- 2026Verified Detection and Prevention of Concurrency Anomalies in Multi-Agent Large Language Model Systemscited by 5
- 2022PAC Statistical Model Checking of Mean Payoff in Discrete- and Continuous-Time MDPcited by 4
- 2021Fine-Tuning the Odds in Bayesian Networkscited by 3
- 2021Dependability Analysis of Deep Reinforcement Learning based Robotics and Autonomous Systems through Probabilistic Model Checkingcited by 3
- 2023Data-driven abstractions via adaptive refinements and a Kantorovich metric [extended version]cited by 3
- 2023Stopping Criteria for Value Iteration on Stochastic Games with Quantitative Objectivescited by 3
22 more
- 2021Inductive Synthesis for Probabilistic Programs Reaches New Horizonscited by 2
- 2021Lifted Model Checking for Relational MDPscited by 2
- 2021Active Learning of Markov Decision Processes using Baum-Welch algorithm (Extended)cited by 2
- 2026TriCEGAR: A Trace-Driven Abstraction Mechanism for Agentic AIcited by 2
- 2026Measuring the Unmeasurable: Markov Chain Reliability for LLM Agentscited by 2
- 2026Robust Probabilistic Shielding for Safe Offline Reinforcement Learningcited by 2
- 2021An Abstraction-based Method to Check Multi-Agent Deep Reinforcement-Learning Behaviorscited by 1
- 2022SOCKS: A Stochastic Optimal Control and Reachability Toolbox Using Kernel Methodscited by 1
- 2024Formally Verified Approximate Policy Iterationcited by 1
- 2025Explaining Control Policies through Predicate Decision Diagramscited by 1
- 2025Are Agents Probabilistic Automata? A Trace-Based, Memory-Constrained Theory of Agentic AIcited by 1
- 2021Adversarial Robustness Verification and Attack Synthesis in Stochastic Systemscited by 0
- 2022Bayesian Statistical Model Checking for Multi-agent Systems using HyperPCTL*cited by 0
- 2023MM Algorithms to Estimate Parameters in Continuous-time Markov Chainscited by 0
- 2024Probabilistic ML Verification via Weighted Model Integrationcited by 0
- 2025Analyzing Value Functions of States in Parametric Markov Chainscited by 0
- 2025Verification-Guided Falsification for Safe RL via Explainable Abstraction and Risk-Aware Explorationcited by 0
- 2025BayesL: a Logical Framework for the Verification of Bayesian Networkscited by 0
- 2026Robustness Analysis of POMDP Policies to Observation Perturbationscited by 0
- 2026Value Functions as Supermartingale Certificatescited by 0
- 2026Leveraging System-Level Observations to Inform Bayesian Learning of Model Parameters for Quantitative Verificationcited by 0
- 2026SoK: Formal Methods for Fact-Checking and Information Integritycited by 0
- 2026SoK: Formal Methods for Fact-Checking and Information Integrity19 Sep 2026
- 2026Leveraging System-Level Observations to Inform Bayesian Learning of Model Parameters for Quantitative Verification4 Aug 2026
- 2026Verified Detection and Prevention of Concurrency Anomalies in Multi-Agent Large Language Model Systems15 Jun 2026
- 2026Value Functions as Supermartingale Certificates29 May 2026
- 2026Robust Probabilistic Shielding for Safe Offline Reinforcement Learning11 May 2026
- 2026Measuring the Unmeasurable: Markov Chain Reliability for LLM Agents27 Apr 2026
- 2026Robustness Analysis of POMDP Policies to Observation Perturbations23 Apr 2026
- 2026TriCEGAR: A Trace-Driven Abstraction Mechanism for Agentic AI30 Jan 2026
- 2025Are Agents Probabilistic Automata? A Trace-Based, Memory-Constrained Theory of Agentic AI27 Oct 2025
- 2025BayesL: a Logical Framework for the Verification of Bayesian Networks30 Jun 2025
- 2025Verification-Guided Falsification for Safe RL via Explainable Abstraction and Risk-Aware Exploration4 Jun 2025
- 2025Analyzing Value Functions of States in Parametric Markov Chains23 Apr 2025
22 more
- 2025Explaining Control Policies through Predicate Decision Diagrams9 Mar 2025
- 2024Formally Verified Approximate Policy Iteration11 Jun 2024
- 2024Probabilistic ML Verification via Weighted Model Integration7 Feb 2024
- 2023Stopping Criteria for Value Iteration on Stochastic Games with Quantitative Objectives19 Apr 2023
- 2023Data-driven abstractions via adaptive refinements and a Kantorovich metric [extended version]30 Mar 2023
- 2023Bayesian Learning for the Robust Verification of Autonomous Robots15 Mar 2023
- 2023MM Algorithms to Estimate Parameters in Continuous-time Markov Chains16 Feb 2023
- 2022Online Shielding for Reinforcement Learning4 Dec 2022
- 2022COOL-MC: A Comprehensive Tool for Reinforcement Learning and Model Checking15 Sep 2022
- 2022Bayesian Statistical Model Checking for Multi-agent Systems using HyperPCTL*6 Sep 2022
- 2022Algebraically Explainable Controllers: Decision Trees and Support Vector Machines Join Forces26 Aug 2022
- 2022PAC Statistical Model Checking of Mean Payoff in Discrete- and Continuous-Time MDP3 Jun 2022
- 2022SOCKS: A Stochastic Optimal Control and Reachability Toolbox Using Kernel Methods12 Mar 2022
- 2021Active Learning of Markov Decision Processes using Baum-Welch algorithm (Extended)6 Oct 2021
- 2021Adversarial Robustness Verification and Attack Synthesis in Stochastic Systems5 Oct 2021
- 2021Dependability Analysis of Deep Reinforcement Learning based Robotics and Autonomous Systems through Probabilistic Model Checking14 Sep 2021
- 2021Convex Optimization for Parameter Synthesis in MDPs30 Jun 2021
- 2021Lifted Model Checking for Relational MDPs22 Jun 2021
- 2021Fine-Tuning the Odds in Bayesian Networks29 May 2021
- 2021An Abstraction-based Method to Check Multi-Agent Deep Reinforcement-Learning Behaviors2 Feb 2021
- 2021Inductive Synthesis for Probabilistic Programs Reaches New Horizons29 Jan 2021
- 2021dtControl 2.0: Explainable Strategy Representation via Decision Tree Learning Steered by Experts15 Jan 2021
- 2026Verified Detection and Prevention of Concurrency Anomalies in Multi-Agent Large Language Model Systemscited by 5
- 2026TriCEGAR: A Trace-Driven Abstraction Mechanism for Agentic AIcited by 2
- 2026Measuring the Unmeasurable: Markov Chain Reliability for LLM Agentscited by 2
- 2025Are Agents Probabilistic Automata? A Trace-Based, Memory-Constrained Theory of Agentic AIcited by 1
- 2026Verified Detection and Prevention of Concurrency Anomalies in Multi-Agent Large Language Model Systems15 Jun 2026
- 2026Measuring the Unmeasurable: Markov Chain Reliability for LLM Agents27 Apr 2026
- 2026TriCEGAR: A Trace-Driven Abstraction Mechanism for Agentic AI30 Jan 2026
- 2025Are Agents Probabilistic Automata? A Trace-Based, Memory-Constrained Theory of Agentic AI27 Oct 2025
- 2022COOL-MC: A Comprehensive Tool for Reinforcement Learning and Model Checkingcited by 19
- 2022Online Shielding for Reinforcement Learningcited by 19
- 2021dtControl 2.0: Explainable Strategy Representation via Decision Tree Learning Steered by Expertscited by 14
- 2021Convex Optimization for Parameter Synthesis in MDPscited by 8
- 2023Bayesian Learning for the Robust Verification of Autonomous Robotscited by 6
- 2022Algebraically Explainable Controllers: Decision Trees and Support Vector Machines Join Forcescited by 5
- 2022PAC Statistical Model Checking of Mean Payoff in Discrete- and Continuous-Time MDPcited by 4
- 2021Fine-Tuning the Odds in Bayesian Networkscited by 3
- 2021Dependability Analysis of Deep Reinforcement Learning based Robotics and Autonomous Systems through Probabilistic Model Checkingcited by 3
- 2023Data-driven abstractions via adaptive refinements and a Kantorovich metric [extended version]cited by 3
- 2023Stopping Criteria for Value Iteration on Stochastic Games with Quantitative Objectivescited by 3
- 2021Inductive Synthesis for Probabilistic Programs Reaches New Horizonscited by 2
12 most cited of 29 All 29 (JSON)
- 2026SoK: Formal Methods for Fact-Checking and Information Integrity19 Sep 2026
- 2026Leveraging System-Level Observations to Inform Bayesian Learning of Model Parameters for Quantitative Verification4 Aug 2026
- 2026Value Functions as Supermartingale Certificates29 May 2026
- 2026Robustness Analysis of POMDP Policies to Observation Perturbations23 Apr 2026
- 2025BayesL: a Logical Framework for the Verification of Bayesian Networks30 Jun 2025
- 2025Verification-Guided Falsification for Safe RL via Explainable Abstraction and Risk-Aware Exploration4 Jun 2025
- 2025Analyzing Value Functions of States in Parametric Markov Chains23 Apr 2025
- 2025Explaining Control Policies through Predicate Decision Diagrams9 Mar 2025
- 2024Formally Verified Approximate Policy Iteration11 Jun 2024
- 2024Probabilistic ML Verification via Weighted Model Integration7 Feb 2024
- 2023Stopping Criteria for Value Iteration on Stochastic Games with Quantitative Objectives19 Apr 2023
- 2023Data-driven abstractions via adaptive refinements and a Kantorovich metric [extended version]30 Mar 2023
12 newest of 29 All 29 (JSON)