User permission isolation model based on finite state machine

2013 ◽  
Vol 33 (1) ◽  
pp. 149-152
Author(s):  
Jianjun LI ◽  
Yixiang JIANG ◽  
Jie QIAN ◽  
Wei LI ◽  
Yu LI
Keyword(s):  
Finite State Machine ◽  
State Machine ◽  
Model Based ◽  
Finite State

scholarly journals Research on the Modeling and Transition Algorithm of a Novel Wall-Climbing Robot

2011 ◽  
Vol 2-3 ◽  
pp. 340-345
Author(s):  
Zhen Hui Li ◽  
Hong Guang Wang ◽  
Yue Chao Wang ◽  
Ai Hua Liu ◽  
Wei Guang Dong
Keyword(s):  
Finite State Machine ◽  
State Machine ◽  
Logical Reasoning ◽  
Planning Model ◽  
Climbing Robot ◽  
Gait Planning ◽  
Model Based ◽  
Inclined Surfaces ◽  
Hybrid Mechanism ◽  
Finite State

This paper presents a modeling and transition algorithm of a novel wall-climbing robot with biped-wheel hybrid mechanism. In order to realize robot transitions between inclined surfaces, the robot’s locomotion gait is analyzed and a locomotion gait planning model based on Finite State Machine (FSM) is established. Moreover a transition algorithm between inclined surfaces is proposed based on multi-sensors data fusions and logical reasoning networks. The results of simulations and experiments show that the model and algorithm are valid and can be applied for the wall-climbing robot’s transition between the concave surfaces.

Model Based Protocol Conformance Test Study

2015 ◽  
Vol 713-715 ◽  
pp. 466-470
Author(s):  
Guo Li Deng ◽  
Tao He ◽  
Yong Wei ◽  
Hua Zhong Li ◽  
Shou Xiang Xu ◽  
...  
Keyword(s):  
Finite State Machine ◽  
State Machine ◽  
Test Method ◽  
Conformance Test ◽  
Testing Method ◽  
Model Based ◽  
Test Study ◽  
Model Based Testing ◽  
Finite State ◽  
Protocol Conformance Testing

This paper puts forwards the problems during the process of conformance test based on the enhanced finite state machine and looks for the description method of the state machine for protocol. Through the analysis of model based on test principle, the protocol conformance testing will be applied based on the enhanced finite state machine test. Through comparing with the traditional test method, study how to design model for protocol, and through executing model produced test, verify the advantage and applicability of model based testing method by testing cases.

scholarly journals Model-Based Testing for MQTT Applications

2020 ◽  
pp. 47-59
Author(s):  
Kotaro Tanabe ◽  
Yoshinori Tanabe ◽  
Masami Hagiya
Keyword(s):  
Finite State Machine ◽  
State Machine ◽  
Test Cases ◽  
Testing Framework ◽  
Model Based ◽  
Model Based Testing ◽  
Finite State ◽  
Long Time ◽  
Virtual Time ◽  
The Internet Of Things

Abstract Model-based testing is a widely-used vital technique for testing software running in a complex environment. In this paper, we propose extensions to existing model-based tools to apply this technique to software that employs the MQ Telemetry Transport (MQTT) protocol for transmitting messages, commonly used in the Internet of Things (IoT) environment. First, in the finite state machine used for generating test cases in a model-based testing framework, we introduce a type of transition that is triggered when receiving MQTT messages. Second, we extend the finite-state machine so that it produces test cases that reflect the characteristics of IoT software – a large number of relatively simple devices communicate with servers. Third, the concept of time is introduced into the finite state machine. Naturally, this is necessary for verifying the properties of software that runs for a long time. Moreover, to facilitate such verification, both real-time and virtual time are introduced. We implemented these extensions into a model-based testing tool, Modbat, and conducted a small experiment to confirm the feasibility, gaining positive results.

MARKOV MATHEMATICAL MODEL OF DYNAMIC ADAPTIVE TESTING OF AN ACTIVE AGENT

2018 ◽  
pp. 29-35
Author(s):  
N. V. Brovka ◽  
P. P. Dyachuk ◽  
M. V. Noskov ◽  
I. P. Peregudova
Keyword(s):  
Mathematical Model ◽  
Finite State Machine ◽  
Active Agent ◽  
Adaptive Testing ◽  
State Machine ◽  
Learning Activities ◽  
Independent Learning ◽  
Complex Object ◽  
Total Reward ◽  
Finite State

The problem and the goal.The urgency of the problem of mathematical description of dynamic adaptive testing is due to the need to diagnose the cognitive abilities of students for independent learning activities. The goal of the article is to develop a Markov mathematical model of the interaction of an active agent (AA) with the Liquidator state machine, canceling incorrect actions, which will allow mathematically describe dynamic adaptive testing with an estimated feedback.The research methodologyconsists of an analysis of the results of research by domestic and foreign scientists on dynamic adaptive testing in education, namely: an activity approach that implements AA developmental problem-solving training; organizational and technological approach to managing the actions of AA in terms of evaluative feedback; Markow’s theory of cement and reinforcement learning.Results.On the basis of the theory of Markov processes, a Markov mathematical model of the interaction of an active agent with a finite state machine, canceling incorrect actions, was developed. This allows you to develop a model for diagnosing the procedural characteristics of students ‘learning activities, including: building axiograms of total reward for students’ actions; probability distribution of states of the solution of the problem of identifying elements of the structure of a complex object calculate the number of AA actions required to achieve the target state depending on the number of elements that need to be identified; construct a scatter plot of active agents by target states in space (R, k), where R is the total reward AA, k is the number of actions performed.Conclusion.Markov’s mathematical model of the interaction of an active agent with a finite state machine, canceling wrong actions allows you to design dynamic adaptive tests and diagnostics of changes in the procedural characteristics of educational activities. The results and conclusions allow to formulate the principles of dynamic adaptive testing based on the estimated feedback.

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