12,247 research outputs found
Software for Wearable Devices: Challenges and Opportunities
Wearable devices are a new form of mobile computer system that provides
exclusive and user-personalized services. Wearable devices bring new issues and
challenges to computer science and technology. This paper summarizes the
development process and the categories of wearable devices. In addition, we
present new key issues arising in aspects of wearable devices, including
operating systems, database management system, network communication protocol,
application development platform, privacy and security, energy consumption,
human-computer interaction, software engineering, and big data.Comment: 6 pages, 1 figure, for Compsac 201
SysMART Indoor Services: A System of Smart and Connected Supermarkets
Smart gadgets are being embedded almost in every aspect of our lives. From
smart cities to smart watches, modern industries are increasingly supporting
the Internet of Things (IoT). SysMART aims at making supermarkets smart,
productive, and with a touch of modern lifestyle. While similar implementations
to improve the shopping experience exists, they tend mainly to replace the
shopping activity at the store with online shopping. Although online shopping
reduces time and effort, it deprives customers from enjoying the experience.
SysMART relies on cutting-edge devices and technology to simplify and reduce
the time required during grocery shopping inside the supermarket. In addition,
the system monitors and maintains perishable products in good condition
suitable for human consumption. SysMART is built using state-of-the-art
technologies that support rapid prototyping and precision data acquisition. The
selected development environment is LabVIEW with its world-class interfacing
libraries. The paper comprises a detailed system description, development
strategy, interface design, software engineering, and a thorough analysis and
evaluation.Comment: 7 pages, 11 figur
Translating Video Recordings of Mobile App Usages into Replayable Scenarios
Screen recordings of mobile applications are easy to obtain and capture a
wealth of information pertinent to software developers (e.g., bugs or feature
requests), making them a popular mechanism for crowdsourced app feedback. Thus,
these videos are becoming a common artifact that developers must manage. In
light of unique mobile development constraints, including swift release cycles
and rapidly evolving platforms, automated techniques for analyzing all types of
rich software artifacts provide benefit to mobile developers. Unfortunately,
automatically analyzing screen recordings presents serious challenges, due to
their graphical nature, compared to other types of (textual) artifacts. To
address these challenges, this paper introduces V2S, a lightweight, automated
approach for translating video recordings of Android app usages into replayable
scenarios. V2S is based primarily on computer vision techniques and adapts
recent solutions for object detection and image classification to detect and
classify user actions captured in a video, and convert these into a replayable
test scenario. We performed an extensive evaluation of V2S involving 175 videos
depicting 3,534 GUI-based actions collected from users exercising features and
reproducing bugs from over 80 popular Android apps. Our results illustrate that
V2S can accurately replay scenarios from screen recordings, and is capable of
reproducing 89% of our collected videos with minimal overhead. A case
study with three industrial partners illustrates the potential usefulness of
V2S from the viewpoint of developers.Comment: In proceedings of the 42nd International Conference on Software
Engineering (ICSE'20), 13 page
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