Cause–effect graphing is a well-known requirement-based and systematic testing method with a heuristic approach. Since it was introduced by Myers in 1979, there have not been any sufficiently comprehensive studies to generate test inputs from these graphs. However, there exist several methods for test input generation from Boolean expressions. Cause–effect graphs can be more convenient for a wide variety of users compared to Boolean expressions. Moreover, they can be used to enforce common constraints and rules on the system variables of different expressions of the system. This study proposes a new mutant-based test input generation method, Spectral Testing for Boolean specification models based on spectral analysis of Boolean expressions using mutations of the original expression. Unlike Myers’ method, Spectral Testing is an algorithmic and deterministic method, in which we model the possible faults systematically. Furthermore, the conversion of cause–effect graphs between Boolean expressions is explored so that the existing test input generation methods for Boolean expressions can be exploited for cause–effect graphing. A software is developed as an open-source extendable tool for generating test inputs from cause–effect graphs by using different methods and performing mutation analysis for quantitative evaluation on these methods for further analysis and comparison. Selected methods, MI, MAX-A, MUTP, MNFP, CUTPNFP, MUMCUT, Unique MC/DC, and Masking MC/DC are implemented together with Myers’ technique and the proposed Spectral Testing in the developed tool. For mutation testing, 9 common fault types of Boolean expressions are modeled, implemented, and generated in the tool. An XML-based standard on top of GraphML representing a cause–effect graph is proposed and is used as the input type to the approach. An empirical study is performed by a case study on 5 different systems with various requirements, including the benchmark set from the TCAS-II system. Our results show that the proposed XML-based cause–effect graph model can be used to represent system requirements. The developed tool can be used for test input generation from proposed cause–effect graph models and can perform mutation analysis to distinguish between the methods with respect to the effectiveness of test inputs and their mutant kill scores. The proposed Spectral Testing method outperforms the state-of-the-art methods in the context of critical systems, regarding both the effectiveness and mutant kill scores of the generated test inputs, and increasing the chances of revealing faults in the system and reducing the cost of testing. Moreover, the proposed method can be used as a separate or complementary method to other well-performing test input generation methods for covering specific fault types.

因果图是一种众所周知的基于需求的系统测试方法，采用启发式方法。自 1979 年由 Myers 引入以来，还没有任何足够全面的研究来从这些图表中生成测试输入。但是，存在多种从布尔表达式生成测试输入的方法。与布尔表达式相比，因果图对于各种用户来说更加方便。此外，它们可用于对系统不同表达式的系统变量强制执行通用约束和规则。本研究提出了一种新的基于突变的测试输入生成方法，即布尔规范模型的谱测试，该方法基于使用原始表达式突变的布尔表达式的谱分析。与迈尔斯的方法不同，频谱测试是一种算法和确定性方法，我们在其中系统地对可能的故障进行建模。此外，探索了布尔表达式之间因果图的转换，以便可以利用现有的布尔表达式测试输入生成方法进行因果图。一种软件被开发为一种开源可扩展工具，用于通过使用不同的方法从因果图中生成测试输入，并执行突变分析以对这些方法进行定量评估，以进行进一步的分析和比较。选定的方法 MI、MAX-A、MUTP、MNFP、CUTPNFP、MUMCUT、Unique MC/DC 和掩蔽 MC/DC 与 Myers 的技术和建议的光谱测试一起实施在开发的工具中。对于突变测试，在工具中建模、实现和生成了 9 种常见故障类型的布尔表达式。提出了一种基于 GraphML 的基于 XML 的标准来表示因果图，并将其用作该方法的输入类型。实证研究是通过对具有不同要求的 5 个不同系统的案例研究进行的，包括来自 TCAS-II 系统的基准集。我们的结果表明，所提出的基于 XML 的因果图模型可用于表示系统需求。开发的工具可用于从提议的因果图模型中生成测试输入，并可以执行突变分析以区分测试输入有效性及其突变杀死分数方面的方法。建议的光谱测试方法在关键系统的上下文中优于最先进的方法，在生成的测试输入的有效性和突变杀死分数方面，并增加了揭示系统故障的机会并降低了测试成本。此外，所提出的方法可以用作其他性能良好的测试输入生成方法的单独或补充方法，以覆盖特定的故障类型。