Software-Engineering Process Simulation (SEPS) model

The Software Engineering Process Simulation (SEPS) model is described which was developed at JPL. SEPS is a dynamic simulation model of the software project development process. It uses the feedback principles of system dynamics to simulate the dynamic interactions among various software life cycle development activities and management decision making processes. The model is designed to be a planning tool to examine tradeoffs of cost, schedule, and functionality, and to test the implications of different managerial policies on a project's outcome. Furthermore, SEPS will enable software managers to gain a better understanding of the dynamics of software project development and perform postmodern assessments

Feedback methods for inverse simulation of dynamic models for engineering systems applications

Inverse simulation is a form of inverse modelling in which computer simulation methods are used to find the time histories of input variables that, for a given model, match a set of required output responses. Conventional inverse simulation methods for dynamic models are computationally intensive and can present difficulties for high-speed applications. This paper includes a review of established methods of inverse simulation,giving some emphasis to iterative techniques that were first developed for aeronautical applications. It goes on to discuss the application of a different approach which is based on feedback principles. This feedback method is suitable for a wide range of linear and nonlinear dynamic models and involves two distinct stages. The first stage involves design of a feedback loop around the given simulation model and, in the second stage, that closed-loop system is used for inversion of the model. Issues of robustness within closed-loop systems used in inverse simulation are not significant as there are no plant uncertainties or external disturbances. Thus the process is simpler than that required for the development of a control system of equivalent complexity. Engineering applications of this feedback approach to inverse simulation are described through case studies that put particular emphasis on nonlinear and multi-input multi-output models

ANANAS - A Framework For Analyzing Android Applications

Android is an open software platform for mobile devices with a large market share in the smartphone sector. The openness of the system as well as its wide adoption lead to an increasing amount of malware developed for this platform. ANANAS is an expandable and modular framework for analyzing Android applications. It takes care of common needs for dynamic malware analysis and provides an interface for the development of plugins. Adaptability and expandability have been main design goals during the development process. An abstraction layer for simple user interaction and phone event simulation is also part of the framework. It allows an analyst to script the required user simulation or phone events on demand or adjust the simulation to his needs. Six plugins have been developed for ANANAS. They represent well known techniques for malware analysis, such as system call hooking and network traffic analysis. The focus clearly lies on dynamic analysis, as five of the six plugins are dynamic analysis methods.Comment: Paper accepted at First Int. Workshop on Emerging Cyberthreats and Countermeasures ECTCM 201

Dynamic wetting for continuum hydrodynamics with multi-component Lattice Boltzmann equation simulation method

This paper was presented at the 2nd Micro and Nano Flows Conference (MNF2009), which was held at Brunel University, West London, UK. The conference was organised by Brunel University and supported by the Institution of Mechanical Engineers, IPEM, the Italian Union of Thermofluid dynamics, the Process Intensification Network, HEXAG - the Heat Exchange Action Group and the Institute of Mathematics and its Applications.We present methodological innovations to the multi-component lattice Boltzmann equation simulation method which allow for the simulation of dynamic contact lines in the continuum approximation. The improvements are set-out and verified by quantitative results. They allow the simulator access to an expanded range of simulation parameters like viscosity, viscosity contrast and interfacial tensions, and to obtain data with low levels of interfacial micro-current activity in the region of the dynamic contact line

Probabilistic simulation for the certification of railway vehicles

The present dynamic certification process that is based on experiments has been essentially built on the basis of experience. The introduction of simulation techniques into this process would be of great interest. However, an accurate simulation of complex, nonlinear systems is a difficult task, in particular when rare events (for example, unstable behaviour) are considered. After analysing the system and the currently utilized procedure, this paper proposes a method to achieve, in some particular cases, a simulation-based certification. It focuses on the need for precise and representative excitations (running conditions) and on their variable nature. A probabilistic approach is therefore proposed and illustrated using an example. First, this paper presents a short description of the vehicle / track system and of the experimental procedure. The proposed simulation process is then described. The requirement to analyse a set of running conditions that is at least as large as the one tested experimentally is explained. In the third section, a sensitivity analysis to determine the most influential parameters of the system is reported. Finally, the proposed method is summarized and an application is presented

Using simulation to evaluate investment projects

The goal of this paper is to show how the system dynamics simulation can be applied to incorporate in the evaluation process of various investment projects the interactions between market demand and financial health of the firm. Through simulation, a more accurate representation of the variability and uncertainty of business proposals or strategies can be obtained.simulation, system dynamic, investment decision

A dynamic contagion process and an application to credit risk

We introduce a new point process, the dynamic contagion process, by gener- alising the Hawkes process and the Cox process with shot noise intensity. Our process includes both self-excited and externally excited jumps, which could be used to model the dynamic contagion impact from endogenous and exoge- nous factors of the underlying system. We have systematically analysed the theoretical distributional properties of this new process, based on the piece- wise deterministic Markov process theory developed by Davis (1984), and the extension of the martingale methodology used by Dassios and Jang (2003). The analytic expressions of the Laplace transform of the intensity process and the probability generating function of the point process have been de- rived. An explicit example of specified jumps with exponential distributions is also given. The object of this study is to produce a general mathemati- cal framework for modelling the dependence structure of arriving events with dynamic contagion, which has the potential to be applicable to a variety of problems in economics, finance and insurance. We provide an application of this process to credit risk, and the simulation algorithm for further industrial implementation and statistical analysis

Support for energy-oriented design in the Australian context

There is a need for decision support tools that integrate energy simulation into early design in the context of Australian practice. Despite the proliferation of simulation programs in the last decade, there are no ready-to-use applications that cater specifically for the Australian climate and regulations. Furthermore, the majority of existing tools focus on achieving interaction with the design domain through model-based interoperability, and largely overlook the issue of process integration. This paper proposes an energy-oriented design environment that both accommodates the Australian context and provides interactive and iterative information exchanges that facilitate feedback between domains. It then presents the structure for DEEPA, an openly customisable system that couples parametric modelling and energy simulation software as a means of developing a decision support tool to allow designers to rapidly and flexibly assess the performance of early design alternatives. Finally, it discusses the benefits of developing a dynamic and concurrent performance evaluation process that parallels the characteristics and relationships of the design process