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Exploring State Machine CECA Model

机译:探索状态机CECA模型

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It was shown during TRIZ Future 2018 conference, that a diagram resulting from Cause-Effect Chains Analysis (CECA) might be transformed into a state machine model. Although the conversion was described with a set of rules, no specific benefits of switching to a state machine approach were presented then. This paper focuses on enhancing the conversion and exploring the possibilities to simplify the output model without losing its information content. It briefly shows relations between the state machines and the formal grammars, proposes regular expressions as a compressed representation of the processes producing target disadvantages and provides SWOT-like analysis of the behavioral state machine CECA model with respect to the classic structural CECA model. It also shows the similarity of the state machine model to hardware-software approach.
机译:在TRIZ Future 2018大会上显示,因果链分析(CECA)产生的图表可能会转换为状态机模型。尽管使用一组规则描述了该转换,但是当时并没有提供切换到状态机方法的特定好处。本文着重于增强转换并探索在不损失其信息内容的情况下简化输出模型的可能性。它简要显示了状态机和形式语法之间的关系,提出了正则表达式作为产生目标劣势的过程的压缩表示,并提供了相对于经典结构CECA模型的行为状态机CECA模型的SWOT式分析。它还显示了状态机模型与硬件-软件方法的相似性。

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