HCOct 10, 2018

The Hidden Cost of Window Management

arXiv:1810.04673v14 citations
Originality Synthesis-oriented
AI Analysis

This addresses the efficiency of multitasking for knowledge workers, but it is incremental as it builds on existing window management analysis.

The paper tackled the problem of limited understanding of how users perform task switching with window management systems, finding that task switching is time-intensive and identifying dominant actions contributing to switch time.

Most window management systems support multitasking by allowing users to open, resize, position, and switch between application windows. Although multitasking has become a way of life for most knowledge workers, our current understanding of how users use window management features to switch between multiple tasks---which may comprise multiple application windows---is limited. In this paper, we present a study providing an in-depth analysis of how task switching is supported in Windows 7. As part of analysis, we developed an interface-agnostic classification of common task switching operations supported by window managers which can be used to quantify the time spent on each constituting action. Our study shows that task switching is a time intensive activity and highlights the dominant actions that contribute to task switch time. Furthermore, our classification highlights the specific operations that are optimized by more recent and experimental window managers and allows identifying opportunities for design that could further reduce the overhead of switching between tasks.

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