7 results about "Extended finite-state machine" patented technology

The invention discloses a method and device for automatically generating task calling codes, computer equipment and a computer readable storage medium, and the method comprises the steps: determining an initial state of a task according to an overall calling process based on EFSM (Extended Finite State Machine) pre-modeling; generating a task sequence according to the initial state and the overall calling process; traversing the task sequence according to a pre-judgment code segment and a result judgment code segment of a preset calling task to generate a pre-judgment script and a result judgment script; and according to the task sequence, the pre-judgment script and the result judgment script, generating a calling process code and outputting the calling process code. According to the embodiment of the invention, the overall calling process based on EFSM pre-modeling is utilized, the dependency relationship design between execution tasks is increased through the preset pre-judgment code segment and the result judgment code segment, the change of the overall structure is better adapted, and continuous utilization is facilitated; by configuring and determining the initial state of the task, the assembly line design can adapt to different scene requirements.

The application provides a test case automatic generation system based on a probability extended finite state machine, which can improve the efficiency and quality of test case generation, and finally generates test cases through probability selection on the processed PEFSM model. The system comprises a PEFSM model construction module, a removing unfeasible path module and a test case probability generation module. The PEFSM model construction module obtains relevant data for constructing a model from a user historical operation record database according to the requirement specification and interface design of a system under test, and outputs a PEFSM model describing the behavior of the system under test. The removing unfeasible path module takes the PEFSM model as input, adopts an evaluation path feasibility measurement method to identify and remove unfeasible paths in the PEFSM model, and outputs a reliable test path set formed by a transition path set. The test case probability generation module takes the reliable test path set as input, initializes context variables, and instantiates test paths in the path set to obtain test cases of the system under test.

The invention discloses an intelligent equipment-oriented information security knowledge modeling method, which comprises the following steps of: abstracting information technology work of intelligent equipment into an information item for description, and obtaining an adjacent matrix among the information items according to a connection relationship among information technology workpieces in an information technology system of the intelligent equipment; generating an information technology system model; the method comprises the following steps of: describing an attacker authority and an attack category, generating an information security knowledge model of the intelligent equipment based on an extended finite-state machine, and generating a state set and a conversion set in the information security knowledge model based on information in a generated information technology system model, so as to complete the construction of the information security knowledge model. Based on knowledge of network attacks and intelligent equipment vulnerabilities, the intelligent equipment information security knowledge model is obtained by abstracting and modeling the intelligent equipment for security test activities, so that information such as test cases can be automatically generated during subsequent information security test, and support is provided for testers.

The application discloses a kind of information security knowledge modeling methods for intelligent device, first the information technology work of intelligent device is abstracted as an information item to describe, according to the connection between each information technology artifact in intelligent device information technology system Information item between the adjacency matrix is obtained, to generate information technology system model;The permission and attack category of attacker are described, and the information security knowledge model of intelligent device is generated based on the extended finite state machine, and the state set and conversion set in the information security knowledge model are generated based on the information in the generated information technology system model, to complete the construction of information security knowledge model.The present application is based on the knowledge of network attack and intelligent device vulnerability, and the intelligent device is abstracted and modeled for security testing activity to obtain the intelligent device information security knowledge model, to facilitate the automatic generation of test case and other information during subsequent information security testing, to provide support for tester.

The present invention discloses a method for formal expression of scenario knowledge of ship collision avoidance rules. The method includes: defining different water traffic scenarios; conducting element analysis and semantic expression on the water traffic scenarios involved in ship collision avoidance rules, and abstractly expressing the water traffic scenario as a conceptual model of a quadruple: scenario = {E, A, R, B}; that is, the water traffic scenario model includes entities E involved in the water traffic scenario, attributes A of objects, relationships R between objects, and behavioral elements B of objects; combining the structural characteristics of the water traffic scenario model in collision avoidance rules, and using the finite state machine method for extension; based on the extended finite state machine method, conducting ontology modeling on ship collision avoidance rule scenario knowledge and constructing a formal description in the form of a scenario knowledge graph. The present invention converts the scenario knowledge involved in collision avoidance rules into content recognizable and processable by a computer, forming knowledge with structured and formal expression, enabling a machine to understand the scenario knowledge through learning.

The invention discloses a C-V2X log-based vehicle-road cooperation scene data analysis method and verification system, and the method comprises the steps: S1, building an EFSM (Extended Finite State Machine) for a to-be-tested operation through employing a formalized framework, and taking the EFSM as a test criterion test oracle; s2, relevant information is extracted from a C-V2X system real-time log and sent to an EFSM model program; and S3, the EFSM performs classification processing on the received C-V2X system information, performs state transition analysis on the received C-V2X system information, and performs test analysis on potential improper behaviors in operation of the C-V2X system. The system is used for implementing the method. The method has the advantages of simple principle, wide application range, simplicity and convenience in operation and the like.

This invention proposes a collaborative service allocation method for low-Earth orbit (LEO) satellite constellations based on finite state machines, belonging to the field of LEO satellite constellation technology. First, this invention constructs an extended finite state machine spatiotemporal graph model to accurately represent on-board resources and state transitions while shielding the dynamics of LEO satellites. Then, a directed acyclic graph (DAG) model is used to represent services, establishing a graph mapping relationship between the DAG and the extended finite state machine spatiotemporal graph, and establishing a latency optimization problem. Finally, a constrained selection adaptive binary particle swarm optimization algorithm is used to solve the latency optimization problem of the graph mapping relationship, finding the mapping strategy with the lowest latency to complete the collaborative service allocation of the satellite constellation. This invention is designed for LEO satellite constellation scenarios. The service collaborative computation based on finite state machines meets the computational requirements of latency-sensitive services in these scenarios, effectively overcomes the heterogeneity of LEO satellite networks, and achieves latency optimization for LEO satellites during simultaneous transmission and computation.