Domain-spanning Maintainability Estimation of Information and Manufacturing Automation Systems

信息系统和制造自动化系统在进化方面面临着非常相似的挑战。两者都在努力应对随着时间的推移而不断变化的需求和架构。通常，信息系统以及制造自动化系统在运行数十年的同时不断修改。修改可以包括系统的校正、改进或适应其环境的变化（例如，硬件或软件平台、技术以及用户属性）和需求。因此，可维护性是一个重要的质量方面，特别是对于长寿命系统。因此，提高可维护性方法的研究具有科学意义，例如DFG未来管理软件演化优先程序设计（SPP 1593）。然而，如果没有明确的案例研究，维修性改善措施的效果不能科学地进行实证验证。SPP 1593涉及两个案例研究，即CoCoME和PPU。本提案旨在支持SPP 1593背景下案例研究的发展，并使用这些案例研究为SPP 1593项目提供服务。这种支持是以科学工作方案的形式提供的，该方案与两个案例研究相结合。拟议项目的目的是探讨和发展一种方法，通过从结构描述中得出维修任务清单，即需要进行的具体更改，来分析软件密集型系统的维修性。为了评估一个系统架构，任务列表是应用于作出估计的可维护性的建议系统设计，具有很高的实际重要性。使用任务列表，可以比较多个体系结构备选方案，并通过比较来识别变更工作。在与SPP 1593背景下的研究人员的采访中，我们首先分析了需求，并指定可维护性的情况下，我们准备的CoCoME和PPU的演变场景的基础上。我们提出元模型，以反映特定领域的结构。此外，作为信息系统和制造自动化系统是丰富的变量，我们研究如何模型的系统可变性可用于可维护性估计。基于元模型，我们提出了一个新的过程，以确定信息系统和制造自动化系统的变更工作的可维护性估计。该程序考虑了过程和系统之间的相互关系，以及它们对维修性估计的影响，同时跨越系统的所有生命阶段。

Information systems and manufacturing automation systems face very similar challenges with respect to evolution. Both struggle with changing requirements and architectures that have grown over time. Frequently, information systems as well as manufacturing automation systems are in operation over decades while they are continuously modified. Modifications may include corrections, improvements, or adaptations of the system to changes in its environment (e.g., hardware or software platform, technology, as well as user properties) and in requirements. Thus, maintainability is an important quality aspect, especially for long-living systems. Accordingly, research in methods to improve maintainability are of scientific interest, e.g. in the DFG Priority Program Design for Future -- Managed Software Evolution (SPP 1593). However, the effect of maintainability improving actions cannot be scientifically empirically validated without the explicit use of case studies. There are two case studies involved in SPP 1593, namely CoCoME and PPU. This proposal has been set up to support the evolution of the case studies in the context of SPP 1593 and to provide service to SPP 1593 projects using these case studies. This support is given in form of a scientific work programme that is superimposed with both case studies. The proposed project targets at the exploration and development of a method to analyse maintainability of software-intensive systems by deriving maintenance task lists, i.e. specific changes to be performed, from architecture descriptions. For assessing a systems architecture, the task list is applied to make estimations about the maintainability of the proposed system design that are of high practical importance. Using the task lists, multiple architecture alternatives can be compared and, by that, change efforts can be identified. In interviews with researchers of the context of SPP 1593, we first analyse requirements and specify maintainability scenarios based on which we prepare evolution scenarios of CoCoME and PPU. We propose meta-models to reflect domain-specific constructs. Moreover, as information systems and manufacturing automation systems are variant-rich, we investigate how models of a systems variability can be used for maintainability estimation. Based on the meta-models, we come up with a novel procedure to maintainability estimation by identifying change efforts for information systems and manufacturing automation systems. The procedure considers the interrelations between processes and the system as well as their effects on maintainability estimation while spanning over all life-phases of the system.