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Finding satisfying global states: all for one and one for all

机译:寻找令人满意的全球状态:一劳永逸,一劳永逸

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Summary form only given. Given a distributed computation and a global predicate, predicate detection involves determining whether there exists at least one consistent cut (or global state) of the computation that satisfies the predicate. On the other hand, computation slicing is concerned with computing the smallest sub-computation - with the least number of consistent cuts - that contains all consistent cuts of the computation satisfying the predicate. We investigate the relationship between predicate detection and computation slicing and show that the two problems are equivalent. Specifically, given an algorithm to detect a predicate b in a computation C, we derive an algorithm to compute the slice of C with respect to b. The time-complexity of the (derived) slicing algorithm is O(n|E|) times the time-complexity of the detection algorithm, where n is the number of processes and E is the set of events. We discuss how the "equivalence " result can be utilized to derive a faster algorithm for solving the general predicate detection problem. Slicing algorithms described in our earlier papers are all off-line in nature. We also give an online algorithm for computing the slice for a predicate that can be detected efficiently. The amortized time-complexity of the algorithm is O(n(c + n)) times the time-complexity of the detection algorithm, where c is the average concurrency in the computation.
机译:仅提供摘要表格。给定分布式计算和全局谓词,谓词检测包括确定是否存在满足谓词的计算的至少一个一致割(或全局状态)。另一方面,计算切片涉及计算最小的子计算-一致割的数量最少-包含满足谓词的计算的所有一致割。我们研究了谓词检测与计算切片之间的关系,并证明这两个问题是等效的。具体来说,给定一种在计算C中检测谓词b的算法,我们导出一种算法来计算相对于b的C切片。 (派生的)切片算法的时间复杂度是O(n | E |)乘以检测算法的时间复杂度,其中n是进程数,E是事件集。我们讨论了如何利用“等效性”结果来推导更快的算法来解决一般谓词检测问题。我们早期论文中描述的切片算法本质上都是离线的。我们还提供了一种在线算法,用于计算可有效检测到的谓词的切片。该算法的摊销时间复杂度是O(n(c + n))乘以检测算法的时间复杂度,其中c是计算中的平均并发性。

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