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

今天的自动化工程师面临着与现代生产系统的开发和维护有关的新挑战，例如，在工业4.0宣言中指出。这包括维护通常寿命很长的、安全关键的、实时的控制软件，这些软件在设计和运行时具有快速增长的分布度以及可变性和适应性。动态软件产品线（DSPL）工程与基于模型的测试（MBT）技术相结合，是一个有前途的范例，有效地开发这种类型的软件; DSPL工程支持（自）自适应软件系统的家庭的发展，而MBT提供了适当的手段，系统地从测试模型和相关的覆盖标准派生测试套件。在IMoTEP项目的第一个资助期，我们为全面的变体感知MBT方法奠定了概念基础，并取得了重大成就，例如，DSPL测试套件生成目的的模型检查技术的适应，在工具框架中集成特定领域的建模语言，SPL演化场景的基于增量的处理，以及测试用例选择和测试套件最小化目的的多目标优化技术的使用。在第二个融资阶段，我们将整合我们的三角洲为基础的技术的SPL版本及其相关的测试用例的演变与我们的变量感知方法的DSPL测试套件的基于模型的生成，把具体的重点放在运行时重新配置活动。由此产生的工具辅助的方法将提供统一的支持，增量共同发展的所有DSPL测试工件和回归测试策略，掌握预期和未预料到的变化，一个长寿的DSPL。根据我们在一个工业合作伙伴的真实案例研究和SPP的PPU案例研究中的经验，我们将开发自动化和应用程序特定领域（模型）覆盖率以及基于突变的测试选择标准，以提高生成的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扩展到考虑到分布式组件的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，进而集成自动化工程领域中使用的整个可变性和建模语言。此外，我们将继续努力选择和调整先进的模型检查技术和工具，用于我们的DSPL测试套件生成和维护目的。最后但并非最不重要的是，我们将继续努力，应用开发的方法在上述两个案例研究的背景下，辅以对照实验研究的可用性开发的方法。

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.