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Stochastic voting algorithms for Web services group testing

机译:用于Web服务组测试的随机投票算法

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This paper proposes a stochastic voting for testing a large number of Web services (WS) under group testing. In the future, a large number of WS would be available and they need to be tested and evaluated in real time. While numerous test input generation techniques are available to generate test inputs, the oracle or the expected output of these test input is often difficult to obtain. One way to obtain the oracle in this case is to give the same input to multiple WS and to establish the oracle by a majority voting. This is based on the assumption that faulty WS often would not produce consistent results, and thus if a majority can be reached, the oracle can be established statistically. However, even correct WS may still produce slightly different outputs, and thus the majority-voting scheme must be carefully designed to distinguish correct but slightly variant output from truly incorrect output. This paper proposes a hierarchical classification based on simulated annealing and multi-dimensional Chi-square statistical techniques to analyze data to see if a majority can be reached. The algorithm is evaluated by a comprehensive simulated data as well as actual data. The data show that the proposed algorithm is effective even in a difficult situation where clusters of WS produce clusters of output.
机译:本文提出了一种随机投票,用于测试小组测试下的大量Web服务(WS)。将来,将有大量的WS可用,需要实时测试和评估。虽然有许多测试输入生成技术可用于生成测试输入,但这些测试输入的Oracle或预期输出通常很难获得。在这种情况下获取Oracle的一种方法是给予多个WS的相同输入,并通过大多数投票来建立Oracle。这是基于假设错误的WS通常不会产生一致的结果,因此如果可以达到多数,则可以在统计上建立Oracle。然而,即使是正确的WS也可能产生略微不同的输出,因此必须仔细设计大多数表决方案以区分正确但略有变体输出从真正不正确的输出。本文提出了一种基于模拟退火和多维Chi-Squard统计技术的分层分类,以分析数据,看看是否可以达到多数。该算法通过全面的模拟数据以及实际数据进行评估。数据表明,即使在WS产生输出集群的困难情况下,所提出的算法也是有效的。

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