Real-time embedded software testing method based on extended finite state machine

The reliability of real-time embedded software directly determines the reliability of the whole real-time embedded sys- tem, and the effective software testing is an important way to ensure software quality and reliability. Based on the analysis of the characteristics of real-time embedded software, the formal method is introduced into the real-time embedded software testing field and the real-time extended finite state machine （RT-EFSM） model is studied firstly. Then, the time zone division method of real-time embedded system is presented and the definition and description methods of time-constrained transition equivalence class （timeCTEC） are presented. Furthermore, the approaches of the testing sequence and test case generation are put forward. Finally, the proposed method is applied to a typical avionics real- time embedded software testing practice and the examples of the timeCTEC, testing sequences and test cases are given. With the analysis of the testing result, the application verification shows that the proposed method can effectively describe the real-time embedded software state transition characteristics and real-time requirements and play the advantages of the formal methods in accuracy, effectiveness and the automation supporting. Combined with the testing platform, the real-time, closed loop and automated simulation testing for real-time embedded software can be realized effectively.

Intrusion Detection for Wireless Mesh Networks using Finite State Machine

Wireless Mesh Networks is vulnerable to attacks due to the open medium, dynamically changing network topology, cooperative algorithms, Lack of centralized monitoring and management point. The traditional way of protecting networks with firewalls and encryption software is no longer suffi- cient and effective for those features. In this paper, we propose a distributed intrusion detection ap- proach based on timed automata. A cluster-based detection scheme is presented, where periodically a node is elected as the monitor node for a cluster. These monitor nodes can not only make local intrusion detection decisions, but also cooperatively take part in global intrusion detection. And then we con- struct the Finite State Machine （FSM） by the way of manually abstracting the correct behaviors of the node according to the routing protocol of Dynamic Source Routing （DSR）. The monitor nodes can verify every node＇s behavior by the Finite State Ma- chine （FSM）, and validly detect real-time attacks without signatures of intrusion or trained data.Compared with the architecture where each node is its own IDS agent, our approach is much more efficient while maintaining the same level of effectiveness. Finally, we evaluate the intrusion detection method through simulation experiments.

Artificial emotional model based on finite state machine

According to the basic emotional theory, the artificial emotional model based on the finite state machine（FSM） was presented. In finite state machine model of emotion, the emotional space included the basic emotional space and the multiple emotional spaces. The emotion-switching diagram was defined and transition fimction was developed using Markov chain and linear interpolation algorithm. The simulation model was built using Stateflow toolbox and Simulink toolbox based on the Matlab platform. And the model included three subsystems： the input one, the emotion one and the behavior one. In the emotional subsystem, the responses of different personalities to the external stimuli were described by defining personal space. This model takes states from an emotional space and updates its state depending on its current state and a state of its input （also a state-emotion）. The simulation model realizes the process of switching the emotion from the neutral state to other basic emotions. The simulation result is proved to correspond to emotion-switching law of human beings.

POWER OPTIMIZATION OF FINITE STATE MACHINE BASED ON GENETIC ALGORITHM

Using state assignment to minimize power dissipation and area for finite state ma-chines is computationally hard. Most of published results show that the reduction of switchingactivity often trades with area penalty. In this paper, a new approach is proposed. Experimentalresults show a significant reduction of switching activity without area penalty compared withprevious publications.

Global Control Simulation of Electric Vehicle Based on Finite State Machine Theory

Finite state machine theory (FSM) is introduced and applied to global control of electric vehicle. Theoretical adaptation for application of FSM in control of electric vehicle is analyzed. Global control logic for parts of electric vehicle is analyzed and built based on FSM. Using Matlab/Simulink, BJD6100-HEV global control algorithm is modeled and prove validity by simulation.

Semantic Sentence Similarity Using Finite State Machine

In this paper, a finite state machine approach is followed in order to find the semantic similarity of two sentences. The approach exploits the concept of bi-directional logic along with a semantic ordering approach. The core part of this approach is bi-directional logic of artificial intelligence. The bi-directional logic is implemented using Finite State Machine algorithm with slight modification. For finding the semantic similarity, keyword has played climactic importance. With the help of the keyword approach, it can be found easily at the sentence level according to this algorithm. The algorithm is proposed especially for Nepali texts. With the polarity of the individual keywords, the finite state machine is made and its final state determines its polarity. If two sentences are negatively polarized, they are said to be coherent, otherwise not. Similarly, if two sentences are of a positive nature, they are said to be coherence. For measuring the coherence (similarity), contextual concept is taken into consideration. The semantic approach, in this research, is a totally contextual based method. Two sentences are said to be semantically similar if they bear the same context. The total accuracy obtained in this algorithm is 90.16%.

Test Selection on Extended Finite State Machines with Provable Guarantees

Building high confidence regression test suites to validate new system versions is a challenging problem. A modelbased approach to build a regression test suite from a given test suite is described. The generated test suite includes every test that will traverse a change performed to produce the new version, and consists of only such tests to reduce the testing costs. Finite state machines extended with typed variables (EFSMs) are used to model systems and system changes are mapped to EFSM transition changes adding/deleting/replacing EFSM transitions and states. Tests are a sequence of input and expected output messages with concrete parameter values over the supported data types. An invariant is formulated to characterize tests whose runtime behavior can be accurately predicted by analyzing their descriptions along with the model. Incremental procedures to efficiently evaluate the invariant and to select tests for regression are developed. Overlaps among the test descriptions are exploited to extend the approach to simultaneously select multiple tests to reduce the test selection costs. Effectiveness of the approach is demonstrated by applying it to several protocols, Web services, and model programs extracted from a popular testing benchmark. Our experimental results show that the proposed approach is economical for regression test selection in all these examples. For all these examples, the proposed approach is able to identify all tests exercising changes more efficiently than brute-force symbolic evaluation.

Intelligent decision-making method for vehicles in emergency conditions based on artificial potential fields and finite state machines

This study aims to propose a decision-making method based on artificial potential fields(APFs)and finite state machines(FSMs)in emergency conditions.This study presents a decision-making method based on APFs and FSMs for emergency conditions.By modeling the longitudinal and lateral potential energy fields of the vehicle,the driving state is identified,and the trigger conditions are provided for path planning during lane changing.In addition,this study also designed the state transition rules based on the longitudinal and lateral virtual forces.It established the vehicle decision-making model based on the finite state machine to ensure driving safety in emergency situations.To illustrate the performance of the decision-making model by considering APFs and finite state machines.The version of the model in the co-simulation platform of MATLAB and CarSim shows that the developed decision model in this study accurately generates driving behaviors of the vehicle at different time intervals.The contributions of this study are two-fold.A hierarchical vehicle state machine decision model is proposed to enhance driving safety in emergency scenarios.Mathematical models for determining the transition thresholds of lateral and longitudinal vehicle states are established based on the vehicle potential field model,leading to the formulation of transition rules between different states of autonomous vehicles(AVs).

Verifying the accuracy of interlocking tables for railway signalling systems using abstract state machines

Railway transportation system is a critical sector where design methods and techniques are defined by international standards in order to reduce possible risks to an acceptable minimum level. CENELEC 50128 strongly recommends the utilization of finite state machines during system modelling stage and formal proof methods during the verifi- cation and testing stages of control algorithms. Due to the high importance of interlocking table at the design state of a sig- nalization system, the modelling and verification of inter- locking tables are examined in this work. For this purpose, abstract state machines are used as a modelling tool. The developed models have been performed in a generalized structure such that the model control can be done automatically for the interlocking systems. In this study, NuSMV is used at the verification state. Also, the consistency of the developed models has been supervised through fault injection. The developed models and software components are applied on a real railway station operated by Metro Istanbul Co.

Web Testing Generation: A Stream <i>X-Machine</i>Based Approach

To ensure the quality of Web applications, Web testing is one of the effective methods. The testing is a process of revealing errors that is used to give confidence that the implementation of a Web application meets its original specification. This work proposes a Web testing framework based on Stream X-Machines (SXMs), which provides a way to derive test cases for a Web application. It starts from constructing the SXM model, from which a test translator is employed to extract the test paths and then translates them into an XML-style test specification, which is the input of test engine. The test engine generates test cases and then executes them, and finally produces test report. This testing method is a significant contribution to informed research.

基于Stateflow的焊接机器人协同规划策略

为了减少多焊接机器人协同规划过程的时间以及算力需求,提出了基于有限状态机理论的多焊接机器人协同规划方法。以汽车侧围总成为焊接对象,使用混合遗传-引力搜索算法(Genetic Algorithm-Gravitational Search Algorithm,GA-GSA)求解工作单元中各焊接机器人焊点分配问题,完成焊接路径规划。确认焊接过程中各焊接机器人间碰撞区域,以精确建立互斥区域,使用Stateflow工具对多焊接机器人系统进行建模与仿真。根据实际工况设置系统中各焊接机器人优先级输入以及每个焊点完成焊接任务所需时间,可得该工况下系统中焊接机器人动作最优调整方案。通过2个仿真案例验证了该方法的可行性与有效性,结果表明该方法可以快速有效地完成多焊接机器人协同规划。

Application of Finite State Machine Theory to the Simulation of Reversed Non-Linear Hysteretic Relationships

This paper presents the application of finite state machine (FSM) theory to the programming of nonlinear hysteretic model simulation for both known and newly created rules. The complicated reversed internal paths involved in the nonlinear relationship which not only depend on material properties, but also on load history, often confuse rule creators and scholars. In this paper, we first describe the development of past hysteretic models. Then we introduce the FSM theory conceptually, and explain how it is applied to reversed and diverse routes. Next, state definitions and procedures are explained with a specific data example using the bilinear model. Finally, the successful application to UC-win/FRAME (3D) is described and several characteristics are summarized. By using FSM’s states and the linkages to represent a hysteresis model, we can quickly realize the programming of the defined complex model rules, and the nonlinear modeling becomes more efficient and feasible.

A matrix-based static approach to analysis of finite state machines

Traditional matrix-based approaches in the field of finite state machines construct state transition matrices,and then use the powers of the state transition matrices to represent corresponding dynamic transition processes,which are cornerstones of system analysis.In this study,we propose a static matrix-based approach that revisits a finite state machine from its structure rather than its dynamic transition process,thus avoiding the“explosion of complexity”problem inherent in the existing approaches.Based on the static approach,we reexamine the issues of closed-loop detection and controllability for deterministic finite state machines.In addition,we propose controllable equivalent form and minimal controllable equivalent form concepts and give corresponding algorithms.

Aspect-Oriented Modeling and Verification with Finite State Machines

Aspect-oriented programming modularizes crosscutting concerns into aspects with the advice invoked at the specified points of program execution. Aspects can be used in a harmful way that invalidates desired properties and even destroys the conceptual integrity of programs. To assure the quality of an aspect-oriented system, rigorous analysis and design of aspects are highly desirable. In this paper, we present an approach to aspect-oriented modeling and verification with finite state machines. Our approach provides explicit notations （e.g., pointcut, advice and aspect） for capturing crosscutting concerns and incremental modification requirements with respect to class state models. For verification purposes, we compose the aspect models and class models in an aspect-oriented model through a weaving mechanism. Then we transform the woven models and the class models not affected by the aspects into FSP （Finite State Processes）, which are to be checked by the LTSA （Labeled Transition System Analyzer） model checker against the desired system properties. We have applied our approach to the modeling and verification of three aspect-oriented systems. To further evaluate the effectiveness of verification, we created a large number of flawed aspect models and verified them against the system requirements. The results show that the verification has revealed all flawed models. This indicates that our approach is effective in quality assurance of aspect-oriented state models. As such, our approach can be used for model-checking state-based specification of aspect-oriented design and can uncover some system design problems before the system is implemented.

Design and Realization of Rotating Machinery Conditions Monitoring System Based on LabVIEW

Nonlinear dynamic analysis of rotating machinery system has always been the hot spot of the rotational dynamics re-search. This article sets up a rotating machinery condition monitoring system to realize the measurement of system dynamic charac-teristic parameters based on NI(National Instruments) virtual instruments technology. The measurement of vibration signal of rotating machinery system is achieved by using NI company general data acquisition module of NI Company. Meanwhile, by analyzing and processing the acquired data using LabVIEW 2012, the dynamic characteristics, such as .the speed of the rotating machinery system, the axis trajectory, spectrum parameters, are attained. The measurement results show that the rotating machinery condition monitor-ing system based on LabVIEW is easy to operate, easy to realize the function extension and maintenance, and that it can be used in the industrial engineering projects with rotation characteristics. LabVIEW as the development tools used by virtual instrument func-tion is very powerful data acquisition software products support is one of the features of it, so using LabVIEW programming and data acquisition is simple and convenient.

Modeling and TOPSIS-GRA Algorithm for Autonomous Driving Decision-Making Under 5G-V2X Infrastructure

This paper is to explore the problems of intelligent connected vehicles(ICVs)autonomous driving decision-making under a 5G-V2X structured road environment.Through literature review and interviews with autonomous driving practitioners,this paper firstly puts forward a logical framework for designing a cerebrum-like autonomous driving system.Secondly,situated on this framework,it builds a hierarchical finite state machine(HFSM)model as well as a TOPSIS-GRA algorithm for making ICV autonomous driving decisions by employing a data fusion approach between the entropy weight method(EWM)and analytic hierarchy process method(AHP)and by employing a model fusion approach between the technique for order preference by similarity to an ideal solution(TOPSIS)and grey relational analysis(GRA).The HFSM model is composed of two layers:the global FSM model and the local FSM model.The decision of the former acts as partial input information of the latter and the result of the latter is sent forward to the local pathplanning module,meanwhile pulsating feedback to the former as real-time refresh data.To identify different traffic scenarios in a cerebrum-like way,the global FSM model is designed as 7 driving behavior states and 17 driving characteristic events,and the local FSM model is designed as 16 states and 8 characteristic events.In respect to designing a cerebrum-like algorithm for state transition,this paper firstly fuses AHP weight and EWM weight at their output layer to generate a synthetic weight coefficient for each characteristic event;then,it further fuses TOPSIS method and GRA method at the model building layer to obtain the implementable order of state transition.To verify the feasibility,reliability,and safety of theHFSMmodel aswell as its TOPSISGRA state transition algorithm,this paper elaborates on a series of simulative experiments conducted on the PreScan8.50 platform.The results display that the accuracy of obstacle detection gets 98%,lane line prediction is beyond 70 m,the speed of collision avoidance is higher than 45 km/h,the distance of collision avoidance is less than 5 m,path planning time for obstacle avoidance is averagely less than 50 ms,and brake deceleration is controlled under 6 m/s2.These technical indexes support that the driving states set and characteristic events set for the HFSM model as well as its TOPSIS-GRA algorithm may bring about cerebrum-like decision-making effectiveness for ICV autonomous driving under 5G-V2X intelligent road infrastructure.

机耕道自动驾驶农机局部路径规划

针对机耕道场景下自动驾驶农机行驶的安全性、平稳性与规划实时性的实际需求,该研究提出了一种基于二次规划的局部路径规划方法。首先基于有限状态机构建农机机耕道行驶模式,其次采用横纵向解耦的方法,通过改进状态栅格法分别对农机速度行为和轨迹行为进行决策,随后利用二次规划方法生成满足多目标、多约束条件的农机轨迹和速度,得到最优路径,最后在多种行驶环境中进行仿真和实车试验,行驶参考速度为2 m/s。实车试验结果表明,在绕行静态障碍物场景中,规划轨迹的平均绝对曲率为0.021 m^(-1),最大绝对曲率为0.056 m^(-1),平均绝对横向误差为3.23 cm,最大绝对横向误差为8.69 cm,农机与障碍物外轮廓的距离大于0.76 m;在规避相向行驶、同向行驶和横穿机耕道的动态障碍物场景中,规划速度的平均绝对速度误差为0.08~0.12 m/s,绝对速度误差小于0.38 m/s,加速度变化范围为-0.38~0.44 m/s^(2)。在规划周期为200 ms的仿真试验中,该文算法平均耗时48 ms,最大耗时75 ms,相比采用静态状态栅格法平均耗时减少38 ms,算法效率提升44%。研究结果可为机耕道场景下的农机局部路径规划提供技术支持。

无人驾驶车辆路径跟踪混合控制策略研究

针对单一控制算法无法同时满足无人驾驶车辆对路径跟踪精度和控制器求解速度需求的问题,提出一种基于线性二次型调节器(LQR)和模型预测控制(MPC)的混合控制策略。该策略在低速工况下使用线性二次型调节器、在高速工况下使用模型预测控制算法进行路径跟踪控制,在此基础上设计基于有限状态机(FSM)的控制算法切换机制,并通过遗传算法(GA)对控制参数进行优化,基于CarSim和MATLAB/Simulink仿真平台对混合控制策略进行仿真验证,并进一步完成了实车试验。试验结果表明,所设计的混合控制策略能够在提高跟踪精度的基础上缩短计算时间,与单一控制算法相比,平均横向误差和平均航向误差分别减小了26.3%和39.6%,平均计算时间缩短了10.9%。

基于FPGA的TANGRAM分组密码算法实现

TANGRAM系列分组密码算法是一种采用比特切片方法,适合多种软硬件平台的系列分组密码算法。针对TANGRAM-128/128算法,使用Verilog HDL对该算法进行FPGA实现并提出设计方案。首先,介绍了TANGRAM密码算法的特点和流程,提出了针对TANGRAM密码算法进行44轮加/解密迭代计算的方案,该方案采取有限状态机的方法有效降低了资源消耗;其次,基于国产高云云源平台,完成了基于高云FPGA的算法工程实现,以及功能仿真和数据的正确性验证,同时在QuartusⅡ13.1.0平台上也进行了相关测试,用以比较。测试结果表明,TANGRAM系列分组密码算法基于Altera公司的CycloneⅣE系列EP4CE40F29C6芯片进行工程实现,最大时钟频率为138.64 MHz,加/解密速率为403.30 Mbps;基于高云半导体GW2A-55系列芯片的最大时钟频率为96.537 MHz,加/解密速率为280.80 Mbps。

程序调试中的数据结构演变可视化方法

数据结构是程序执行时的重要信息载体,其演变过程往往较为复杂和抽象。针对程序设计初学者较难理解数据结构演变过程的问题,提出一种面向程序调试中的数据结构演变可视化方法。在调试开始时,首先使用组件表达式表示数据结构,然后通过配置表以及布局函数将组件表达式生成可视化视图。在进行单步调试后,通过对比单步调试前后的可视化数据方式生成组件演变行为,运用有限状态机理论构建数据结构演变模型,该模型的执行使得组件发生演变,同时生成可视化动作。使用动画单元执行可视化动作,实现数据结构演变的可视化呈现,帮助初学者理解数据结构相关程序的执行过程。实验结果表明,将该方法应用于1个数据结构演变可视化框架StructV,并应用于1个在线可视化编程实训云平台的研发,可有效降低初学者理解数据结构演变过程的难度,并提升编程实训时的程序调试效率。