基于构件的软件验证最小假设生成方法的改进

Pham Ngoc Hung, Viet-Ha Nguyen, Toshiaki Aoki, T. Katayama
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引用次数: 7

摘要

最小化假设生成是假设保证验证的一种改进的最小化假设生成方法。该方法不仅适用于基于构件的软件,而且有可能解决模型检验中的状态空间爆炸问题。然而,由于生成最小假设的计算成本很高,因此该方法难以在实际中应用。为了降低优化方法的复杂性,本文将优化方法作为最小化假设生成方法的连续工作。该方法的关键思想是使用深度限制搜索策略在包含候选假设的搜索树的子树中找到较小的假设。与最小化方法相比,改进的方法可以生成更小的假设,且计算成本和内存消耗更低。在软件进化的背景下,生成的假设对于以更低的计算成本重新检查系统也是有效的。我们已经实现了一个支持改进方法的工具。给出了实验结果并进行了讨论。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
An Improvement of Minimized Assumption Generation Method for Component-Based Software Verification
The minimized assumption generation has been recognized as an improved method of the assume-guarantee verification for generating minimal assumptions. This method is not only fitted to component-based software but also has a potential to solve the state space explosion problem in model checking. However, the computational cost for generating the minimal assumption is very high so the method is difficult to be applied in practice. This paper presents an optimization as a continuous work of the minimized assumption generation method in order to reduce the complexity of the method. The key idea of this method is to find a smaller assumption in a sub-tree of the search tree containing the candidate assumptions using the depth-limited search strategy. With this approach, the improved method can generate smaller assumptions with a lower computational cost and consumption memory than the minimized method. The generated assumptions are also effective for rechecking the systems at much lower computational cost in the context of software evolution. We have implemented a tool supporting the improved method. Experimental results are also presented and discussed.
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