Microinteractions provide small details that may have a big impact on user experience of a (software) product. There are many examples of successful implementation of microinteractions in traditional software products, such as cut & paste functionality. However, the increasing popularity of mobile and wearable computing devices increases its application area and provides new opportunities to discover new microinteractions that simplify the usage of mobile and wearable devices. In this paper, we describe the concept of microinteractions and some already existing microinteractions in the domain of mobile and wearable computing. Additionally, we present how some of the presented microinteractions can be used in a new context. Finally, we present and discuss our own microinteractions addressing the development of future mobile and wearable computing applications.

Advanced asset health management solutions blend business intelligence with analytics that incorporate expert operational knowledge of industrial equipment and systems. Key challenges in developing these solutions include: streamlining the capture and prepackaging of operational experts' knowledge as analytic modules, efficiently evolving the modules as knowledge grows, adapting the analytics in the field for diverse operating circumstances and industries, and executing the analytics with high performance in industrial and enterprise software systems. A Quality Attribute Workshop (QAW) was used to elicit and analyze variability at development time and runtime for creating, integrating, evolving, and tailoring reusable analytic modules for ABB/Ventyx asset health solution offerings. Dynamic software product line (DSPL) architecture approaches were then applied in designing an analytics plug in architecture for asset health solutions. This paper describes our approach and experiences in designing the analytics product line architecture and its SME Workbench toolset, and how we achieved significant improvements in speed and flexibility of deploying industrial analytics.

Multi-core CPUs are now common in modern computers. To get access to effectively an unlimited supply of compute resources, software programs that have been highly optimized to use a single CPU need to be converted where possible to use concurrency. We have initiated our concurrency software research for performance enhancement on a large-scale system with high throughput and low latency transactions. In this paper, we report our experience, experiments, and results in various aspects of concurrency design and programming, including multi-threaded prototypes, static and dynamic concurrency analysis, future techniques and trends, concurrency experiments, and concurrency design patterns. Based on the concurrency experiments, we achieved at least 80 percent overall performance increases as measured by transaction throughput. As a result, capital expenditures for large scale deployments can be significantly reduced.