最优细化比例抽样测试策略的有效性研究

STEP '99. Proceedings Ninth International Workshop Software Technology and Engineering Practice Pub Date : 1999-08-30 DOI:10.1109/STEP.1999.798483

F. Chan, I. K. Mak, T. Chen, S. M. Shen

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引用次数: 5

摘要

近年来，人们对子域测试和随机测试的有效性进行了分析研究。T.Y. Chen和Y.T. Yu(1994)发现，对于不相交的子域，只要从每个子域中选择的测试用例的数量与其大小成正比(比例抽样策略)，使用子域测试发现至少一个失败的概率不小于使用随机测试的概率。本文研究了最优细化比例抽样(ORPS)策略的有效性，该策略是比例抽样策略的一种特殊情况。ORPS策略在概念上很简单，实现成本通常很低。对已发表的带有种子错误的程序样本进行了实证研究。该策略的性能优于随机测试。

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On the effectiveness of the optimally refined proportional sampling testing strategy

Recently, the effectiveness of subdomain testing and random testing has been studied analytically. T.Y. Chen and Y.T. Yu (1994) found that, for the case of disjoint subdomains, as long as the number of test cases selected from each subdomain is proportional to its size (the proportional sampling strategy), the probability of revealing at least one failure using subdomain testing is not less than that using random testing. This paper investigates the effectiveness of the optimally refined proportional sampling (ORPS) strategy, which is a special case of the proportional sampling strategy. The ORPS strategy is simple in concept, and the implementation cost is usually low. An empirical study has been conducted for a sample of published programs with seeded errors. The performance of this strategy was found to be better than random testing.

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STEP '99. Proceedings Ninth International Workshop Software Technology and Engineering Practice

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