Adaptive testing (AT) is a software testing approach that uses a feedback mechanism to enhance test effectiveness. Its testing strategy can be adjusted online by using the testing data collected during the software testing process. However, it requires complex parameter estimation which results in excessive computational overhead that may hinder the applicability of AT. In this paper, we propose an approach called AT based on moment estimation (AT-ME) to address this problem. The proposed approach uses moment estimation to serve as the algorithm of parameter estimation, which reduces the complexity of AT-ME. In addition, a dynamic length for testing action is set to limit the number of decisions without influencing the test effectiveness. The proposed approach has been validated on the Siemens test suite, which includes seven real programs. The experiments show that AT-ME can reduce the computational overhead of AT without compromising overall testing efficiency. Results demonstrate that AT-ME is a feasible and effective AT strategy.

中文翻译：

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基于矩估计的自适应测试

自适应测试 (AT) 是一种软件测试方法，它使用反馈机制来提高测试有效性。利用软件测试过程中收集的测试数据，可以在线调整其测试策略。然而，它需要复杂的参数估计，这会导致过多的计算开销，这可能会阻碍 AT 的适用性。在本文中，我们提出了一种称为基于矩估计的 AT（AT-ME）方法来解决这个问题。该方法采用矩估计作为参数估计的算法，降低了AT-ME的复杂度。此外，设置测试动作的动态长度以限制决策数量而不影响测试有效性。所提出的方法已在西门子测试套件上得到验证，其中包括七个实际程序。实验表明，AT-ME 可以在不影响整体测试效率的情况下减少 AT 的计算开销。结果表明 AT-ME 是一种可行且有效的 AT 策略。