Stochastic voting algorithms for Web services group testing

W. Tsai, Dawei Zhang, R. Paul, Yinong Chen
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引用次数: 7

Abstract

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.
Web服务组测试的随机投票算法
本文提出了一种随机投票方法,用于在组测试条件下对大量Web服务进行测试。在未来,将会有大量的WS可用,并且需要对它们进行实时测试和评估。虽然有许多测试输入生成技术可用于生成测试输入,但通常很难获得这些测试输入的oracle或预期输出。在这种情况下,获得oracle的一种方法是向多个WS提供相同的输入,并通过多数投票来建立oracle。这是基于错误WS通常不会产生一致结果的假设,因此,如果可以达到多数,则可以在统计上建立oracle。然而,即使正确的WS仍然可能产生略有不同的输出,因此必须仔细设计多数投票方案,以区分正确但略有不同的输出和真正不正确的输出。本文提出了一种基于模拟退火和多维卡方统计技术的分层分类方法来分析数据,看看是否可以达到多数。通过综合仿真数据和实际数据对算法进行了评价。数据表明,即使在WS集群产生输出集群的困难情况下,该算法也是有效的。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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