一种面向传感器网络应用程序的有效测试方法

An Effective Testing Approach for Sensor Network Applications

无线传感器网络是物联网的基本组成部分.随着传感器网络的广泛应用,其软件质量的问题日益突出.传感器网络应用程序中的瞬态错误很难被发现,这是因为它们由偶然交织的事件处理逻辑所触发,而且有效的自动测试预言往往不可得.基于区间的测试方法将传感网程序的执行过程划分为若干区间,并检测包含瞬态错误的区间,但是这种方法可能产生大量的误报.文中详述了对这些误报进行深入研究的结果,并进而提出一种有效的基于区间的测试方法,用于检测传感网程序应用级组件中的瞬态错误.此方法的主要特点是采用新的区间划分策略和程序行为选择策略.这些策略用于排除被分析区间中的良性偶然交织行为.文中提出了一种区间识别算法,并在此基础上实现了该方法的一个原型工具.文中给出了一组实验来评估原型工具的效果和效率.实验结果表明,此工具能够有效而高效地检测被测程序中的瞬态错误.

Wireless Sensor Networks （WSNs） represent a fundamental building block of the Internet of Things. With the growing application of WSNs, the software-quality issues have become increasingly prominent. Transient bugs in WSN applications are difficult to be found because they are triggered by occasionally interleaved event-handling logics and an effective automated test oracle is rarely available. Interval-based testing in this area partitions a sensor＇s program execution into intervals and finds the buggy intervals, but it might report numerous false positives. In this paper, we report the results of an in-depth study of the causes of false positives that arise from interval-based testing that we performed. Based on these results, we propose an effective approach for detecting transient bugs in application-level components. Our approach featuresan interval-partitioning strategy and a program behavior-selection strategy. Both strategies aim to reduce benign occasional behaviors from those to be analyzed. We propose an interval-identification algorithm. Based on this algorithm, we developed a prototype tool that implements our interval- based testing technique, and conducted a set of experiments to evaluate its effectiveness and efficiency. The empirical studies show that our tool is both effective and efficient in detecting transient bugs for our subject programs.