Understanding the effects of requirements volatility in software engineering by using analytical modeling and software process simulation

This paper introduces an executable system dynamics simulation model developed to help project managers comprehend the complex impacts related to requirements volatility on a software development project. The simulator extends previous research and adds research results from an empirical survey, including over 50 new parameters derived from the associated survey data, to a base model. The paper discusses detailed results from two cases that show significant cost, schedule, and quality impacts as a result of requirements volatility. The simulator can be used as an effective tool to demonstrate the complex set of factor relationships and effects related to requirements volatility.     

Software Project Duration and Effort: An Empirical Study

Software projects frequently finish late and over budget. Much of the research to date has characterized this problem in terms of inadequate project estimation or incomplete requirements determination. In this study, we concentrate instead on understanding the relationship between project duration and project effort. Over time, a dynamic environment contributes to the expansion of project requirements, thus increasing the scope and effort required to complete the project, irrespective of initial requirements and anticipated project size. Further, frequent delays and interruptions in a project contribute to greater effort each time work is resumed. We develop and empirically evaluate a two-stage model to relate project duration and effort. Our results indicate a significant and positive relationship between project duration and effort, controlling for anticipated project size and other project characteristics. Our model also provides an estimate for the rate of environmental change while projects are in progress. We demonstrate the practical implications of our model by showing how it can be used in conjunction with time boxing techniques and new development methodologies to better scope software projects.     

元数据驱动的个性化查询工具设计与实现

传统查询定制工具只关注动态组合SQL语句,并没有关注与业务相关的实体,如用户、专业等。用户无法定制个性化的查询,企业不能对数据按专业、查询对象和用户等组织多维度、多专业的数据查询。为解决上述问题,提出了一个元数据驱动的个性化查询定制框架,用元数据描述用户需求和企业环境。用户通过个性定制工具,形成用户需求的元数据描述,查询引擎通过元数据读取用户需求,然后查询专业数据库并形成个性化界面。既有通用查询的通用数据接口,又有友好、个性化的用户接口,在油田企业信息集成中得到应用,并取得良好应用效果。     

Digital twin-driven deep reinforcement learning for adaptive task allocation in robotic construction

In order to accomplish diverse tasks successfully in a dynamic (i.e., changing over time) construction environment, robots should be able to prioritize assigned tasks to optimize their performance in a given state. Recently, a deep reinforcement learning (DRL) approach has shown potential for addressing such adaptive task allocation. It remains unanswered, however, whether or not DRL can address adaptive task allocation problems in dynamic robotic construction environments. In this paper, we developed and tested a digital twin-driven DRL learning method to explore the potential of DRL for adaptive task allocation in robotic construction environments. Specifically, the digital twin synthesizes sensory data from physical assets and is used to simulate a variety of dynamic robotic construction site conditions within which a DRL agent can interact. As a result, the agent can learn an adaptive task allocation strategy that increases project performance. We tested this method with a case project in which a virtual robotic construction project (i.e., interlocking concrete bricks are delivered and assembled by robots) was digitally twinned for DRL training and testing. Results indicated that the DRL model’s task allocation approach reduced construction time by 36% in three dynamic testing environments when compared to a rule-based imperative model. The proposed DRL learning method promises to be an effective tool for adaptive task allocation in dynamic robotic construction environments. Such an adaptive task allocation method can help construction robots cope with uncertainties and can ultimately improve construction project performance by efficiently prioritizing assigned tasks.     

Defining requirements for a standard simulation environment

A simulation environment combines the many elements of simulation into one powerful tool. A standard based on a reference model would benefit users and researchers alike. We define a reference model for general-purpose discrete-event simulation environments, as well as the associated requirements for the model's functional layers, to be used as the basis for a future standard. We characterize environments by highlighting and grouping different tasks with common traits. Each group can then be related to the other groups in a logical, structured manner to create a model for a standard environment. Functionally, the standard environment would reside between the modeler (user) and the hardware platform's operating system     

水下狭窄环境中ROV的自主返回控制

为满足缆控水下机器人（remotely operated vehicle,ROV）在水下狭窄环境中作业完毕后的顺利回收需求,研究仿真ROV的路径跟踪以及动力定位系统。基于非对称ROV构建数学模型,利用李雅普诺夫函数,采用反向递推和反馈线性化,设计了基于反步法的自适应控制器。该控制器通过反馈线性化,将已知非线性参数转化成线性参数,不确定的非线性参数应用自适应控制律进行放宽。通过仿真对该控制器应用于ROV的可行性进行验证表明:基于反步自适应控制以及视线导引的算法,ROV在水下狭窄环境中路径跟踪效果良好,动力定位稳定,鲁棒性良好,能够很好地解决ROV模型的不确定性与非线性问题。该控制器为ROV在水下狭窄环境中的回收作业提供了很好的解决方案。     

An integrated data collection and analysis framework for remote monitoring and planning of construction operations

Recent advances in data collection and operations analysis techniques have facilitated the process of designing, analyzing, planning, and controlling of engineering processes. Mathematical tools such as graphical models, scheduling techniques, operations research, and simulation have enabled engineers to create models that represent activities, resources, and the environment under which a project is taking place. Traditionally, most simulation paradigms use static or historical data to create computer interpretable representations of real engineering systems. The suitability of this approach for modeling construction operations, however, has always been a challenge since most construction projects are unique in nature as every project is different in design, specifications, methods, and standards. Due to the dynamic nature and complexity of most construction operations, there is a significant need for a methodology that combines the capabilities of traditional modeling of engineering systems and real time field data collection. This paper presents the requirements and applicability of a data-driven modeling framework capable of collecting and manipulating real time field data from construction equipment, creating dynamic 3D visualizations of ongoing engineering activities, and updating the contents of a discrete event simulation model representing the real engineering system. The developed framework can be adopted for use by project decision-makers for short-term project planning and control since the resulting simulation and visualization are completely based on the latest status of project entities.     

Virtual prototyping of mechatronic systems

Mechatronic systems abound in technological fields such as robotics and machine tools industry. Significant advances in dynamic performance of these systems can be achieved provided that mutual interactions of different domains (such as mechanics, electronics, hydraulics and control) are thoroughly understood. Virtual prototyping entails integration of multi-domain dynamic simulation in the design process, in order to reproduce and analyze the effects of design choices on the overall performance. This paper states the requirements of the modeling language and software tool for simulation of mechatronic systems and describes an experience of use of DYMOLA with Modelica language in the simulation of a complete machining center. The model has been successfully validated against experimental results collected on the real machining center.     

A high performance tool for the simulation of the dynamic pantograph–catenary interaction

In this paper a computer tool for the simulation of the dynamic pantograph–catenary interaction is presented. We model this interaction and study its behavior in the energy transmission process. The calculation of the dynamic equation of the pantograph–catenary interaction is considered from a simulation point of view by means of a high performance computing algorithm, where the amount of data and the time requirements have been dramatically reduced. Finally, the present algorithm has been used to implement an user-friendly, interactive and graphically oriented toolbox whose design is presented in this work. This tool is used for the static and dynamic analysis of a catenaries system, which is shown by means of a real case of study.     

Generating crime data using agent-based simulation

Policing plays an important role in combating street crime. Though policing actions have a dissuasive impact on criminal behavior, they can also have unpredictable and even undesirable effects such as displacement of crime hot-spots. This paper presents an agent-based simulation model that generates artificial street-crime data which can be used to test different policing strategies in a virtual environment. The model can thus evaluate the strategies’ effectiveness and collateral effects before putting them into practice and provide support for the policing decision-making process. Based on this model, a crime simulator was implemented in Repast Simphony and a series of test simulations on fictitious and real cities were carried out. The proposed formulation was successfully validated, confirming its potential as a powerful tool for the study of street crime.     

扑翼飞行器的多机协同飞行设计与实践

扑翼飞行器(flapping-wing aerial vehicle,FAV)是一种模仿动物飞行方式的新型飞行器,其具有仿生性且飞行声音小等特点,具有广泛的军事和民用前景.由于扑翼飞行器动力学模型复杂且容易受到风等环境因素的影响,目前尚无成熟稳定的控制算法可以用来控制扑翼飞行器.目前对扑翼飞行器的控制大多仍以手动控制为...     

基于Uni-Tire轮胎模型的车辆质心侧偏角估计

针对车辆质心侧偏角估计的准确性和实时性能问题,提出了车辆质心侧偏角估计的非线性全维观测器设计方法.首先基于车辆动力学模型及纵滑-侧偏联合工况下的Uni-Tire轮胎模型,利用车载传感器测量车辆状态;观测器利用这些状态估计出车辆的纵向速度、侧向速度及横摆角速度,并由此得到车辆的质心侧偏角估计.其次利用输入-状态稳定(input-to-state stability,ISS)理论对观测器的稳定性进行了分析.最后采用红旗CA7180A3E型轿车的车辆参数使用车辆仿真软件veDYNA对极限工况下的估计结果进行了离线仿真研究,并利用xPC-Target仿真环境和dSPACE实时仿真系统搭建仿真平台,对非线性全维观测器的实时性进行验证.仿真结果表明,非线性估计方法估计精度较高,实时性较好,可以满足工程应用的要求.     

战场环境的抽象化模型设计与仿真

战场环境是一个复杂、动态的信息空间,战场环境模型应能根据模拟需求,既反映战场环境的动态多变性,又具有一定的抽象性,减少计算量,满足实时性。为此以武器装备论证为仿真目的,分析了其战场环境模拟的需求,建立了关于地理环境的可视性和通行性模型、动态气象环境模型、电磁环境模型和目标运动特性模型,分析了作为仿真联邦组成的战场环境成员的内外部关系,采用基于推算定位算法（Dead Reckoning Algorithm,DR算法）的数据更新策略,调和了仿真精度和通信带宽的矛盾。     

面向功率键合图的通用仿真软件的研究

该文介绍了一种面向功率键合图的通用的系统动态性仿真软件－ＰＢＧＳＩＭ。该软件在ＭＡＴＬＡＢ平台上二次开发而成。充分发挥了功率键合图法在分析系统动态特性方面的优势,可以处理包含各种环节的复杂系统,软件从系统的键合图模型出发,自动辨错揭示、自动建立数学模型（字符型和数值型）、进行仿真计算并按要求输出仿真结果,用户可以方便地修改元件参数或模型直至得到满意结果。还可以给定 经变量,对系统的动态特性进行参数     

基于DBN的特种车辆前向防撞推理模型

针对特种车辆在动态环境中的前向碰撞风险评估问题,对特种车辆前向碰撞风险的自然因素、驾驶员行为特征等进行研究,并对固定的车辆安全防撞距离阈值进行改进,提出了一种基于动态贝叶斯网络的前向防撞推理模型。该模型将自车与周围环境的位置关系、环境关系、驾驶员行为等因素进行融合,一旦周围环境发生变化,该模型可以及时评估前向风险,并与静态贝叶斯网络的前向推理模型进行对比分析。仿真实验验证了该前向防撞推理模型的可行性和有效性。     

Component-Based Systems Reconfigurations Using Graph Transformations with <Emphasis Type="Italic">GROOVE</Emphasis>

Component-based systems permit standardisation and re-usability of code through the use of components. The architecture of component-based systems can be modified thanks to dynamic reconfigurations, which contribute to systems’ (self-)adaptation by adding or removing components without incurring any system downtime. In this context, the present article describes a formal model for dynamic reconfigurations of component-based systems. It provides a way of expressing runtime reconfigurations of a system and proving their correctness according to a static invariant for consistency constraints and/or a user-provided post-condition. Guarded reconfigurations allow us to build reconfigurations based on primitive reconfiguration operations using sequences of reconfigurations and the alternative and the repetitive constructs, while preserving configuration consistency. A practical contribution consists of the implementation of a component-based model using the GROOVE graph transformation tool. This implementation is illustrated on a cloud-based multi-tier application hosting environment managed as a component-based system. In addition, after enriching the model with interpreted configurations and reconfigurations in a consistency compatible manner, component systems’ implementations are related to their specifications by a simulation relation.     

Optimisation of construction site layout using a hybrid simulation-based system

The layout of temporary facilities for a construction project greatly impacts project performance as demonstrated in many prior studies. This paper demonstrates how the site layout process can be automated for specific types of construction. Utility tunnel construction was selected as the specialty area, for which a partially automated site layout application was built. This approach integrates general purpose simulation for modelling space, logistics and resource dynamics with genetic algorithms for optimizing the layout based on various constraints and rules. We achieve this by implementing a site layout optimisation system within a simulation environment which already models tunnel construction processes. The new modelling strategy provides a medium for seamless integration between the resulting site layout and the discrete event production simulation models. The paper describes the approach taken and the system developed, presenting a practical case study from a tunnelling project in Edmonton, Canada to illustrate the system’s performance and its validation.     

Holding time estimation for reactions in stochastic event-based simulation of complex biological systems

The complexity of biological systems motivate the use of an “in silico” stochastic discrete event simulation methodology. This method can incorporate the effects of the recently identified stochastic resonance of a biological system and is computationally capable to process the dynamic interactions of different pathways in the cell. The main requirement for this technique is the event time models for the discrete events of the biological system. Currently such models do not exist for biological functions and this paper proposes one such event model – the biochemical reactions between the molecules inside the cytoplasm of a cell where the reaction environment is highly chaotic. We present a mathematical formulation for the estimation of the reaction time between two molecules within a cell based on the discrete system states. In particular, we propose two models: (1) The reactant molecules enter the system one at a time to initiate reactions, and (2) The reactant molecules arrive in batches of a certain size. We derive expressions for the average and second moment of the time for reaction. This random time is used by our stochastic event-based simulation. Unlike rate equations, the proposed model does not require the assumption of concentration stability for multiple molecule reactions. Also the models incorporate many structural and functional parameters of the biological function, that are lacking in the currently used rate equation model. The parametric nature of the model makes it generic and useful for diverse studies.     

Knowledge-based risk assessment and cost estimation

A knowledge-based method for software project risk assessment and cost estimation has been implemented on multiple platforms. As an extension to the Constructive Cost Model (COCOMO), it aids in project planning by identifying, categorizing, quantifying and prioritizing project risks. It also detects cost estimate input anomalies and provides risk control advice in addition to conventional COCOMO cost and schedule calculation.The method has been developed in conjunction with a system dynamics model of the software development process, and serves as an intelligent front end to the simulation model. It extends previous research in the knowledge-based cost estimation domain by focusing on risk assessment, incorporating substantially more rules, going beyond standard COCOMO, performing quantitative validation, providing a user-friendly interface, and integrating it with a dynamic simulation model.Results of the validation are promising, and the method is being used at Litton Data Systems and other industrial environments. It will be undergoing further enhancement as part of an integrated capability for software engineering to assist in system acquisition, project planning and risk management.