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Detecting logic errors in discrete-event simulation: reverse engineering through event graphs

机译:在离散事件仿真中检测逻辑错误:通过事件图进行逆向工程

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Several inherent constraints remain in the model development process, even though modern enhancements to simulation environments have provided tools for code generation, debugging, and tracing. To develop a simulation model, the simulation analyst still needs to have expertise in a number of different fields, e.g., probability, statistics, design of experiments, modeling, systems engineering, software engineering, and computer programming. Although several simulation packages implement syntactic-checks and semantic-consistency-checks, typically, the simulation analyst needs to possess output-analysis-knowledge specifically aimed at verifying and checking the simulation code. Reverse engineering a graphical model, e.g., an event graph, from general purpose simulation code demonstrates an enhancement to the model development process. A reverse engineering step allows an analyst to check, both, the static and dynamic properties of the coded simulation model. Even though the reverse engineering produces an event-oriented view, the enhanced model development process provides a systematic approach for conversion from other world views. Overall, this enhanced process provides a framework which yields better analysis techniques. Better diagnostic assistance is achieved when viewing a combination of static and dynamic properties of the simulation code. Now, the analyst is able to find logical/execution errors, e.g., errors related to resource deadlocks, before running simulation experiments. Since the graphical model is generated from the simulation code, and the process combines views, the analyst also has a better framework for verifying the coded simulation model. Also, the reverse engineering step provides a structural model useful in converting between different simulation languages or systems. Improvements to the techniques for conversion between languages will facilitate reuse of existing programmed models.
机译:尽管现代的仿真环境增强功能提供了代码生成,调试和跟踪的工具,但是模型开发过程中仍然存在一些固有的约束。为了开发仿真模型,仿真分析师仍然需要在许多不同领域中具有专业知识,例如,概率,统计,实验设计,建模,系统工程,软件工程和计算机编程。尽管一些仿真程序包实现了语法检查和语义一致性检查,但是通常,仿真分析人员需要拥有专门用于验证和检查仿真代码的输出分析知识。对来自通用仿真代码的图形模型(例如事件图)进行逆向工程演示了模型开发过程的增强。逆向工程步骤使分析人员可以检查编码的仿真模型的静态和动态属性。即使逆向工程产生面向事件的视图,增强的模型开发过程也提供了一种从其他世界视图转换的系统方法。总体而言,此增强的过程提供了可产生更好分析技术的框架。查看模拟代码的静态和动态属性的组合可获得更好的诊断帮助。现在,分析人员能够在运行模拟实验之前找到逻辑/执行错误,例如与资源死锁相关的错误。由于图形模型是从仿真代码生成的,并且该过程结合了视图,因此分析人员还拥有一个更好的框架来验证编码的仿真模型。同样,逆向工程步骤提供了一种结构模型,可用于在不同的仿真语言或系统之间进行转换。语言之间转换技术的改进将促进现有编程模型的重用。

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