Report from GI-Dagstuhl Seminar 16394: Software Performance Engineering in the DevOps World

This report documents the program and the outcomes of GI-Dagstuhl Seminar 16394 "Software Performance Engineering in the DevOps World". The seminar addressed the problem of performance-aware DevOps. Both, DevOps and performance engineering have been growing trends over the past one to two years, in no small part due to the rise in importance of identifying performance anomalies in the operations (Ops) of cloud and big data systems and feeding these back to the development (Dev). However, so far, the research community has treated software engineering, performance engineering, and cloud computing mostly as individual research areas. We aimed to identify cross-community collaboration, and to set the path for long-lasting collaborations towards performance-aware DevOps. The main goal of the seminar was to bring together young researchers (PhD students in a later stage of their PhD, as well as PostDocs or Junior Professors) in the areas of (i) software engineering, (ii) performance engineering, and (iii) cloud computing and big data to present their current research projects, to exchange experience and expertise, to discuss research challenges, and to develop ideas for future collaborations

mRUBiS: An Exemplar for Model-Based Architectural Self-Healing and Self-Optimization

Self-adaptive software systems are often structured into an adaptation engine that manages an adaptable software by operating on a runtime model that represents the architecture of the software (model-based architectural self-adaptation). Despite the popularity of such approaches, existing exemplars provide application programming interfaces but no runtime model to develop adaptation engines. Consequently, there does not exist any exemplar that supports developing, evaluating, and comparing model-based self-adaptation off the shelf. Therefore, we present mRUBiS, an extensible exemplar for model-based architectural self-healing and self-optimization. mRUBiS simulates the adaptable software and therefore provides and maintains an architectural runtime model of the software, which can be directly used by adaptation engines to realize and perform self-adaptation. Particularly, mRUBiS supports injecting issues into the model, which should be handled by self-adaptation, and validating the model to assess the self-adaptation. Finally, mRUBiS allows developers to explore variants of adaptation engines (e.g., event-driven self-adaptation) and to evaluate the effectiveness, efficiency, and scalability of the engines

Integrating IVHM and Asset Design

Integrated Vehicle Health Management (IVHM) describes a set of capabilities that enable effective and efficient maintenance and operation of the target vehicle. It accounts for the collection of data, conducting analysis, and supporting the decision-making process for sustainment and operation. The design of IVHM systems endeavours to account for all causes of failure in a disciplined, systems engineering, manner. With industry striving to reduce through-life cost, IVHM is a powerful tool to give forewarning of impending failure and hence control over the outcome. Benefits have been realised from this approach across a number of different sectors but, hindering our ability to realise further benefit from this maturing technology, is the fact that IVHM is still treated as added on to the design of the asset, rather than being a sub-system in its own right, fully integrated with the asset design. The elevation and integration of IVHM in this way will enable architectures to be chosen that accommodate health ready sub-systems from the supply chain and design trade-offs to be made, to name but two major benefits. Barriers to IVHM being integrated with the asset design are examined in this paper. The paper presents progress in overcoming them, and suggests potential solutions for those that remain. It addresses the IVHM system design from a systems engineering perspective and the integration with the asset design will be described within an industrial design process

Software test automation : a design and tool selection approach for a heterogeneous environment

textThis report describes a design approach for implementing a software test automation solution that can accommodate existing test processes in an organization. The process of implementing a software test automation solution is a large undertaking and requires careful planning to avoid unsuccessful implementations. This report outlines a design that can integrate with existing business and development processes in an organization, and recommends automation and development frameworks for achieving the test automation goals. Considerations for a heterogeneous test environment with varying types of supported operating systems, such as Windows and Linux, and multiple test execution environments, such as Java and .NET, have been made in this design and in the tool selections for the system implementation. The report also describes some of the challenges and caveats of automation in a heterogeneous environment along with recommended solutions to these challenges.Electrical and Computer Engineerin

Advanced Testing Chain Supporting the Validation of Smart Grid Systems and Technologies

New testing and development procedures and methods are needed to address topics like power system stability, operation and control in the context of grid integration of rapidly developing smart grid technologies. In this context, individual testing of units and components has to be reconsidered and appropriate testing procedures and methods need to be described and implemented. This paper addresses these needs by proposing a holistic and enhanced testing methodology that integrates simulation/software- and hardware-based testing infrastructure. This approach presents the advantage of a testing environment, which is very close to f i eld testing, includes the grid dynamic behavior feedback and is risks-free for the power system, for the equipment under test and for the personnel executing the tests. Furthermore, this paper gives an overview of successful implementation of the proposed testing approach within different testing infrastructure available at the premises of different research institutes in Europe.Comment: 2018 IEEE Workshop on Complexity in Engineering (COMPENG