6 results about "Robustness testing" patented technology

This invention discloses a photovoltaic power prediction simulation platform based on fitting correction and digital twins, comprising modules such as a hybrid data source, scheme configuration and comparison, a digital twin simulation engine, scenario scripts, and robustness testing. The method of this invention constructs a forward simulation path through triple fitting correction (meteorological data correction, power conversion correction, and scheduling standard evaluation); and utilizes the results of the third evaluation correction to form a feedback signal, dynamically adjusting the feature weighting and power calibration parameters in the forward path to form a closed-loop simulation; the digital twin engine integrates long-cycle factors such as component aging and a sudden event injection mechanism to simulate a high-fidelity dynamic environment. This invention enables dynamic evaluation of the adaptive learning capability of prediction schemes, robustness and resilience testing under extreme conditions, and provides a fair comparison environment and refined error attribution analysis, significantly improving the efficiency and depth of photovoltaic power prediction system research and development and verification.

The application discloses a kind of based on the robustness test method, device, computer equipment and medium of ceph's storage system, belong to computer technology field.The robustness test method based on the ceph's storage system includes: mounting ceph storage system directory or volume on test press, calling storage test tool vdbench runs storage service test script, simulates business pressure;Set fault simulation operation related parameters in configuration file and parse configuration file;According to the analysis result of configuration file, simulate the corresponding fault test scene;Monitoring storage service test script running output log, and record current key information when detecting that exception occurs;And read current key information and analyze, and output robustness test summary result.The test method can realize the various fault scenes and associated tests of ceph storage system automatically, improve test efficiency and accuracy.

This invention provides a robustness testing method and system for the kernel interface of an airborne real-time operating system. It employs a multi-dimensional equivalence class partitioning model for parameter classification, systematically enumerating six categories—legal values, boundary values, illegal values, null pointers, extreme values, and permission exceptions—based on two dimensions: data type and semantic role. This avoids the problem of overlooking exception categories in manual, experience-based design. Orthogonal lists are used for parameter combination, ensuring that any equivalence class combination between any two parameters is tested at least once. At the test execution level, four mechanisms are deployed: watchdog deadlock detection, memory sentinel out-of-bounds detection, kernel panic callback capture, and non-volatile progress marker restart detection, making result determination independent of the API return value itself. The structured test report generated by this invention includes coverage statistics, detailed abnormal test cases, and defect location information, serving as objective evidence of DO-178C robustness testing activities and meeting the airworthiness certification requirements for test sufficiency and traceability.

The application provides a kind of robustness test and device of code agent, and it relates to artificial intelligence technical field.The method comprises: obtaining original instance from original test data set;The original instance includes code repository, problem description, test case and reference repair patch;According to the reference repair patch, determine target file from the corresponding original instance;Based on the target file, carry out repository layer disturbance to the original instance, obtain disturbance instance, to obtain robustness test data set according to the disturbance instance;Run the code agent on the robustness test data set to carry out robustness test, can comprehensively reflect the robustness of code agent when facing real code repository.

The application discloses a text reasoning chain credibility evaluation method and system, which comprises receiving a text reasoning chain to be evaluated; constructing a logical dependency graph based on the text reasoning chain; performing verification interaction based on the graph; and generating an evaluation result based on feedback, so that deep analysis of the internal structure of the reasoning chain is realized through structured logical dependency and multi-round verification interaction, and problems such as insufficient verification depth, dependence on an external knowledge base, lack of robustness testing, poor interpretability and the like in the prior art are solved, and the credibility evaluation can be deep, fine-grained, interpretable and robust.

This invention relates to 3D point cloud intelligent perception security testing technology, specifically a method and system for adversarial robustness testing of LiDAR point cloud target detection models. The method includes the following steps: acquiring point cloud scene data to be evaluated; calling the victim point cloud target detection model to obtain a baseline detection output; establishing a constraint set consistent with the LiDAR sampling mechanism, and generating local perturbation patterns that satisfy the constraint set; optimizing the injection position of the local perturbation patterns as a continuous decision-making process, iteratively updating the injection parameters; injecting the local perturbation patterns into the point cloud scene to form adversarial test samples, obtaining the test output of the victim point cloud target detection model; calculating robustness indices and determining failure types based on the baseline detection output and test output, and generating a security assessment report. This invention does not require access to the victim model's structure, parameters, or gradient information; robustness evaluation can be completed solely based on the inference output.