论文标题
随机过程代数的速率提升：利用结构特性
Rate Lifting for Stochastic Process Algebra: Exploiting Structural Properties
论文作者
论文摘要
本报告提出了一种用于确定随机过程代数模型的顺序过程中未知速率的算法，前提是给出了合并平面模型中的速率。这样的速率提升对于模型重新设计和模型维修非常有用。从技术上讲，该算法通过求解非线性方程的系统，并在必要时调整模型的同步结构而不更改其过渡系统。该报告包含算法的完整伪代码。算法采用的方法利用了随机过程代数系统的某些结构特性，这些结构特性首次在此制定，并且在其他情况下也可能非常有益。
This report presents an algorithm for determining the unknown rates in the sequential processes of a Stochastic Process Algebra model, provided that the rates in the combined flat model are given. Such a rate lifting is useful for model reengineering and model repair. Technically, the algorithm works by solving systems of nonlinear equations and, if necessary, adjusting the model`s synchronisation structure without changing its transition system. This report contains the complete pseudo-code of the algorithm. The approach taken by the algorithm exploits some structural properties of Stochastic Process Algebra systems, which are formulated here for the first time and could be very beneficial also in other contexts.
