论文标题
确定性程序的概率输出分析 - 重用现有的非稳定分析
Probabilistic Output Analyses for Deterministic Programs --- Reusing Existing Non-probabilistic Analyses
论文作者
论文摘要
我们考虑重复使用已建立的非稳定输出分析（向前或向后），以产生程序的前图像或图像关系（例如间隔分析）的过度评价。我们假定对程序输入的概率度量，并呈现两种技术（一种用于向前的技术，另一项用于向后分析），这些技术均导致输出事件的上和较低概率边界。我们证明了最涉及的技术，即前向技术，用于两个示例，并将其结果与尖端的概率输出分析进行比较。
We consider reusing established non-probabilistic output analyses (either forward or backwards) that yield over-approximations of a program's pre-image or image relation, e.g., interval analyses. We assume a probability measure over the program input and present two techniques (one for forward and one for backward analyses) that both derive upper and lower probability bounds for the output events. We demonstrate the most involved technique, namely the forward technique, for two examples and compare their results to a cutting-edge probabilistic output analysis.
