Integrated Model-based Testing of Continuously Evolving Software Product Lines (IMoTEP 2)

正如工业4.0宣言所指出的那样，今天的自动化工程师面临着关于现代生产系统的开发和维护的新挑战。这包括维护通常寿命很长、对安全至关重要的实时控制软件，这些软件的分布程度在快速增长，并且在设计和运行时具有可变性和适应性。动态软件产品线（DSPL）工程与基于模型的测试（MBT）技术相结合，是有效开发此类软件的一个有前途的范例；DSPL工程支持（自）适应软件系统家族的开发，而MBT为系统地从测试模型和相关覆盖标准中派生测试套件提供了适当的方法。在IMoTEP项目的第一个资助阶段，我们为全面的变量感知MBT方法奠定了概念基础，并取得了重大成就，例如，为DSPL测试套件生成目的而适应模型检查技术，在工具框架中集成特定于领域的建模语言，基于delta的SPL演化场景处理，以及使用多目标优化技术来选择测试用例和最小化测试套件。在第二个资助阶段，我们将把我们用于SPL版本演进的基于增量的技术及其相关的测试用例与我们用于DSPL测试套件的基于模型的生成的变量感知方法集成在一起，该DSPL测试套件特别关注于运行时重构活动。由此产生的工具辅助方法将为所有DSPL测试工件和回归测试策略的增量共同演化提供统一的支持，以掌握长期存在的DSPL的预期和非预期更改。基于我们对来自工业合作伙伴的真实案例研究的经验，以及SPP的PPU案例研究，我们将开发自动化和应用特定领域（模型）覆盖以及基于突变的测试选择标准，以提高生成测试套件的效率和有效性。此外，开发的DSPL测试套件维护方法将被扩展到考虑分布式组件正常和重新配置行为的实时约束的场景。IMoTEP工具将相应地扩展，依赖于元建模、模型转换技术，从而集成自动化工程领域中使用的整个范围的可变性和建模语言。此外，我们将继续努力为我们的DSPL测试套件生成和维护目的选择和采用先进的模型检查技术和工具。最后但并非最不重要的是，我们将继续努力在上述两个案例研究的背景下应用开发的方法，并辅以研究开发方法可用性的对照实验。

Todays automation engineers are faced with new challenges concerning the development and maintenance of modern production systems as, e.g., pointed out in the Industry 4.0 manifesto. This includes the maintenance of often very long living, safety-critical, real-time control software with a rapidly growing degree of distribution as well as variability and adaptability at design and runtime. A promising paradigm for developing this type of software efficiently is Dynamic Software Product Line (DSPL) engineering combined with model-based testing (MBT) techniques; DSPL engineering supports the development of families of (self-)adaptive software systems, whereas MBT offers the appropriate means for systematically deriving test suites from test models and related coverage criteria. In the first funding period of the IMoTEP project, we laid the conceptual foundation for a comprehensive variant-aware MBT methodology with significant achievements concerning, e.g., the adaptation of model-checking techniques for DSPL test suite generation purposes, the integration of domain-specific modeling languages in a tooling framework, the delta-based handling of SPL evolution scenarios, and the usage of multi-objective optimization techniques for test case selection and test suite minimization purposes. In the second funding phase we will integrate our delta-based techniques for the evolution of SPL versions and their related test cases with our variant-aware approach for the model-based generation of a DSPL test suite that puts specific focus on runtime reconfiguration activities. The resulting tool-assisted methodology will offer unified support for the incremental co-evolution of all DSPL testing artifacts and regression testing strategies for mastering anticipated and unanticipated changes of a long-living DSPL. Based on our experiences with a real-world case study from an industrial partner and the PPU case study of the SPP we will develop automation and application domain-specific (model) coverage and mutation-based test selection criteria in order to increase the efficiency and effectiveness of generated test suites. Furthermore, the developed DSPL test suite maintenance methodology will be extended to take scenarios of distributed components with real-time constraints for their normal and reconfiguration behavior into account. The IMoTEP tooling will be extended accordingly, relying on meta-modeling, model transformation techniques in turn for the integration of a whole range of variability and modeling languages used in the automation engineering domain. In addition, we will continue our efforts to select and adapt advanced model-checking techniques and tools for our DSPL test suite generation and maintenance purposes. Last but not least we will continue our efforts to apply the developed methodology in the context of the above mentioned two case studies, complemented by controlled experiments studying the usability of the developed approach.