• Corpus ID: 239050099

Part-X: A Family of Stochastic Algorithms for Search-Based Test Generation with Probabilistic Guarantees

@article{Pedrielli2021PartXAF,
  title={Part-X: A Family of Stochastic Algorithms for Search-Based Test Generation with Probabilistic Guarantees},
  author={Giulia Pedrielli and Tanmay Kandhait and Surdeep Chotaliya and Quinn Thibeault and Hao Huang and Mauricio Castillo-Effen and Georgios Fainekos},
  journal={ArXiv},
  year={2021},
  volume={abs/2110.10729}
}
Requirements driven search-based testing (also known as falsification) has proven to be a practical and effective method for discovering erroneous behaviors in Cyber-Physical Systems. Despite the constant improvements on the performance and applicability of falsification methods, they all share a common characteristic. Namely, they are best-effort methods which do not provide any guarantees on the absence of erroneous behaviors (falsifiers) when the testing budget is exhausted. The absence of… 
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References

SHOWING 1-10 OF 61 REFERENCES
Falsification of cyber-physical systems with robustness-guided black-box checking
TLDR
This work employs Black-box checking (BBC), which is a combination of automata learning and model checking, and enhances BBC using the robust semantics of STL formulas, which is the essential gadget in falsification.
Falsification of Cyber-Physical Systems with Robustness Uncertainty Quantification Through Stochastic optimization with Adaptive Restart
TLDR
This work proposes the use of a stochastic search method that mixes global and local search for system test case generation and shows improved finite time performance, i.e., quick identification of falsification behaviors, over current search-based test casegeneration methods.
Robustness-guided temporal logic testing and verification for Stochastic Cyber-Physical Systems
TLDR
A framework for automatic specification-guided testing for Stochastic Cyber-Physical Systems (SCPS) using the theory of robustness of Metric Temporal Logic (MTL) specifications to quantify how robustly an SCPS satisfies a specification in MTL.
Analyzing Neighborhoods of Falsifying Traces in Cyber-Physical Systems
TLDR
This work poses the problem of analyzing falsifying traces of cyber-physical systems as one of finding a neighborhood of inputs that contains the falsifying counterexample in question, such that each point in this neighborhood corresponds to a falsifying input with a high probability.
Efficient Guiding Strategies for Testing of Temporal Properties of Hybrid Systems
TLDR
This paper presents an approach that uses the rapidly exploring random trees (RRT) technique to explore the state-space of a CPS, and shows that it scales to industrial-scale CPSs by demonstrating its efficacy on an automotive powertrain control system.
Probabilistic Temporal Logic Falsification of Cyber-Physical Systems
TLDR
This work presents a Monte-Carlo optimization technique for finding system behaviors that falsify a metric temporal logic (MTL) property and shows that using this framework can help automatically falsify properties with more consistency as compared to other means, such as uniform sampling.
Hybrid System Falsification Under (In)equality Constraints via Search Space Transformation
TLDR
This article proposes a falsification approach that performs the search over the unconstrained space, guided by the robustness of the mapped points in the constrained space, and outperforms state-of-the-art constrained falsification approaches.
Approximation-Refinement Testing of Compute-Intensive Cyber-Physical Models: An Approach Based on System Identification
TLDR
This work proposes a novel approach, namely ARIsTEO, to enable effective and efficient testing of CI-CPS models, and compares it with S-Taliro, an open-source and industry-strength tool for testing CPS models.
Two-Layered Falsification of Hybrid Systems Guided by Monte Carlo Tree Search
TLDR
A two-layered optimization framework that uses Monte Carlo tree search (MCTS), a popular machine learning technique with solid mathematical and empirical foundations, that guides the lower layer of local hill-climbing optimization, thus balancing exploration and exploitation in a disciplined manner.
Verifying Controllers Against Adversarial Examples with Bayesian Optimization
TLDR
This paper presents an active-testing framework based on Bayesian Optimization that specifies safety constraints using logic and exploit structure in the problem in order to test the system for adversarial counter examples that violate the safety specifications.
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