1,452 research outputs found
Determining and Detecting Permission Issues of Wearable Apps
Wearable apps are becoming increasingly popular. Nevertheless, to date, very few studies have examined the issues that wearable apps face. Prior studies showed that user reviews contain a plethora of insights that can be used to understand quality issues and help developers build better quality mobile apps.
Therefore, in this thesis, we start by empirically studying user reviews to understand the user complaints about wearable apps. We manually sample and categorize 2,667 reviews from 19 Android wearable apps. Additionally, we examine the replies posted by developers in response to user complaints. This study allows us to determine the type of complaints that developers care about the most and to identify problems that, despite being important to users, do not receive a proper response from developers.
We find that the most frequent complaints are related to Functional Errors, Cost, and Lack of Functionality, whereas the most negatively impacting complaints are related to Installation Problems, Device Compatibility, and Privacy & Ethical Issues. We find that developers mostly reply to complaints related to Privacy & Ethical Issues, Performance Issues, and notification-related issues. Furthermore, we observe that when developers reply, they tend to provide a solution, request more details, or let the user know that they are working on a solution. Our results highlight the issues that users face the most, and the issues to which developers should pay additional attention to due to their negative impact.
Based on these results from the first empirical study, we investigate the most negatively impactful complaints. We observe that mainly two permission problems are a common factor to raise issues that cause these complaints -namely the permission mismatch problem and the problem of superfluous features.
As a result, we propose a technique to detect permission problems in wearable app. To operationalize our technique we developed a tool, called Permlyzer, that automatically detects these two problems from Android APKs. We then perform an empirical study on of 2,724 free wearable apps. Our findings show that the permission mismatches exist in 6.1% of released apps on the app store. Moreover, we find that 19.2% of studded wearable apps contain superfluous features
Towards Modeling Software Quality of Virtual Reality Applications from Users' Perspectives
Virtual Reality (VR) technology has become increasingly popular in recent
years as a key enabler of the Metaverse. VR applications have unique
characteristics, including the revolutionized human-computer interaction
mechanisms, that distinguish them from traditional software. Hence, user
expectations for the software quality of VR applications diverge from those for
traditional software. Investigating these quality expectations is crucial for
the effective development and maintenance of VR applications, which remains an
under-explored area in prior research.
To bridge the gap, we conduct the first large-scale empirical study to model
the software quality of VR applications from users' perspectives. To this end,
we analyze 1,132,056 user reviews of 14,150 VR applications across seven app
stores through a semiautomatic review mining approach. We construct a taxonomy
of 12 software quality attributes that are of major concern to VR users. Our
analysis reveals that the VR-specific quality attributes are of utmost
importance to users, which are closely related to the most unique properties of
VR applications like revolutionized interaction mechanisms and immersive
experiences. Our examination of relevant user complaints reveals the major
factors impacting user satisfaction with VR-specific quality attributes. We
identify that poor design or implementation of the movement mechanisms, control
mechanisms, multimedia systems, and physics, can significantly degrade the user
experience. Moreover, we discuss the implications of VR quality assurance for
both developers and researchers to shed light on future work. For instance, we
suggest developers implement sufficient accessibility and comfort options for
users with mobility limitations, sensory impairments, and other specific needs
to customize the interaction mechanisms. Our datasets and results will be
released to facilitate follow-up studies
What people complain about drone apps? a large-scale empirical study of Google play store reviews
Within the past few years, there has been a tremendous increase in the number of UAVs (Unmanned Aerial Vehicle) or drones manufacture and purchase. It is expected to proliferate further, penetrating into every stream of life, thus making its usage inevitable. The UAV’s major components are its physical hardware and programming software, which controls its navigation or performs various tasks based on the field of concern. The drone manufacturers launch the controlling app for the drones in mobile app stores. A few drone manufacturers also release development kits to aid drone enthusiasts in developing customized or more creative apps. Thus, the app stores are also expected to be flooded with drone-related apps in the near future. With various active research and studies being carried out in UAV’s hardware field, no effort is dedicated to studying/researching the software side of UAV. Towards this end, a large-scale empirical study of UAV or drone-related apps of the Google Play Store Platform is conducted. The study consisted of 1,825 UAV mobile apps, across twenty-five categories, with 162,250 reviews. Some of the notable findings of the thesis are (a) There are 27 major types of issues the drone app users complain about, (b) The top four complaints observed are Functional Error (27.9%), Device Compatibility (16.8%), Cost (16.2%) and Connection/Sync (15.6%), (c) The top four issues for which the UAV manufactures or Drone app developers provide feedback to user complaints are Functional Error (40.9%), Cost (33.3%), Device Compatibility (23.1%) and ConnectionSync (16%), (d) Developers respond to the most frequently occurring complaints rather than the most negatively impacting ones
A Review of Commercial and Medical-Grade Physiological Monitoring Devices for Biofeedback-Assisted Quality of Life Improvement Studies
With the rise in wearable technology and "health culture", we are seeing an increasing interest and affordances in studying how to not only prolong life expectancy but also in how to improve individuals' quality of life. On the one hand, this attempts to give meaning to the increasing life expectancy, as living above a certain threshold of pain and lack of autonomy or mobility is both degrading and unfair. On the other hand, it lowers the cost of continuous care, as individuals with high quality of life indexes tend to have lower hospital readmissions or secondary complications, not to mention higher physical and mental health. In this paper, we evaluate the current state of the art in physiological therapy (biofeedback) along with the existing medical grade and consumer grade hardware for physiological research. We provide a quick primer on the most commonly monitored physiologic metrics, as well as a brief discussion on the current state of the art in biofeedback-assisted medical applications. We then go on to present a comparative analysis between medical and consumer grade biofeedback devices and discuss the hardware specifications and potential practical applications of each consumer grade device in terms of functionality and adaptability for controlled (laboratory) and uncontrolled (field) studies. We end this article with some empirical observations based on our study so that readers might use take them into consideration when arranging a laboratory or real-world experience, thus avoiding costly time delays and material expenditures.info:eu-repo/semantics/publishedVersio
How do Developers Test Android Applications?
Enabling fully automated testing of mobile applications has recently become
an important topic of study for both researchers and practitioners. A plethora
of tools and approaches have been proposed to aid mobile developers both by
augmenting manual testing practices and by automating various parts of the
testing process. However, current approaches for automated testing fall short
in convincing developers about their benefits, leading to a majority of mobile
testing being performed manually. With the goal of helping researchers and
practitioners - who design approaches supporting mobile testing - to understand
developer's needs, we analyzed survey responses from 102 open source
contributors to Android projects about their practices when performing testing.
The survey focused on questions regarding practices and preferences of
developers/testers in-the-wild for (i) designing and generating test cases,
(ii) automated testing practices, and (iii) perceptions of quality metrics such
as code coverage for determining test quality. Analyzing the information
gleaned from this survey, we compile a body of knowledge to help guide
researchers and professionals toward tailoring new automated testing approaches
to the need of a diverse set of open source developers.Comment: 11 pages, accepted to the Proceedings of the 33rd IEEE International
Conference on Software Maintenance and Evolution (ICSME'17
The Online Fashion Retail Complaint Management. A Case Study @ShopeeID.
Indonesia fashion retail e-commerce is a growing phenomenon; the growth of the e-commerce application @ShopeeID show the proposition delivered to the targeted market. Nevertheless, there is a lack of research conducted to explore fashion retail e-commerce attributes. Therefore, @ShopeeID tweet for the period September 2018 extracted for further exploratory factor analysis. There is 1761 tweet in the period; the findings show that @ShopeeID utilizing the channel for promotion, delivering the price, product, and the process for transaction in Shopee. The exciting finding shows that @ShopeeID could enhance the complaint management process, promote the responsiveness for the complaint delivered. Keywords: @ShopeeID, Marketing Communication, Online Complaint DOI: 10.7176/JMCR/59-05 Publication date: August 31st 201
Enhancing Mobile App User Understanding and Marketing with Heterogeneous Crowdsourced Data: A Review
© 2013 IEEE. The mobile app market has been surging in recent years. It has some key differentiating characteristics which make it different from traditional markets. To enhance mobile app development and marketing, it is important to study the key research challenges such as app user profiling, usage pattern understanding, popularity prediction, requirement and feedback mining, and so on. This paper reviews CrowdApp, a research field that leverages heterogeneous crowdsourced data for mobile app user understanding and marketing. We first characterize the opportunities of the CrowdApp, and then present the key research challenges and state-of-the-art techniques to deal with these challenges. We further discuss the open issues and future trends of the CrowdApp. Finally, an evolvable app ecosystem architecture based on heterogeneous crowdsourced data is presented
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