scholarly journals An Empirical Analysis of Mobile Apps’ Popularity Metrics in Mobile Software Ecosystems

2016 ◽  
Author(s):  
Ludymila L. A. Gomes ◽  
Awdren L. Fontão ◽  
Allan J. S. Bezerra ◽  
Arilo C. Dias-Neto
Keyword(s):  
Mobile Applications ◽  
User Satisfaction ◽  
Mobile Apps ◽  
Mapping Study ◽  
Mobile Platforms ◽  
Technical Literature ◽  
Software Ecosystem ◽  
Software Ecosystems ◽  
Mobile Software

The growing of mobile platforms in the last years has changed the software development scenario and challenged developers around the world in building successful mobile applications (apps). Users are the core of a mobile software ecosystem (MSECO). Thus, the quality of an app would be related to the user satisfaction, which could be measured by its popularity in App Store. In this paper, we describe the results of a mapping study that identified and analyzed how metrics on apps’ popularity have been addressed in the technical literature. 18 metrics were identified as related to apps’ popularity (users rating and downloads the most cited). After that, we conducted a survey with 47 developers acting within the main MSECOs (Android, iOS and Windows) in order to evaluate these 18 metrics regarding their usefulness to characterize app's popularity. As results, we observed developers understand the importance of metrics to indicate popularity of apps in a different way when compared to the current research.

scholarly journals Creating the mobile apps independence rating

2018 ◽  
Vol 18 ◽  
pp. 03002
Author(s):  
Anton Kukanov ◽  
Elena Andrianova
Keyword(s):  
Mobile Applications ◽  
Mobile Apps ◽  
Test Procedures ◽  
High Quality ◽  
Quality Requirements ◽  
Mobile Software ◽  
Quality Product ◽  
High Quality Product ◽  
Independent Rating

Nowadays the mobile apps market is experiencing unprecedented growth. The quantity of mobile applications, which is proposed for installation, has exceeded 6 million. It causes, that it’s difficult for common consumers to choose a safety and high-quality product from this amount. The proposed independent rating called up for helping ordinary consumers. It is based on the special standard of mobile apps quality requirements and group of test procedures, that allow to evaluate the quality of mobile software.

Classifying Mobile Applications Using Word Embeddings

2022 ◽  
Vol 31 (2) ◽  
pp. 1-30
Author(s):  
Fahimeh Ebrahimi ◽  
Miroslav Tushev ◽  
Anas Mahmoud
Keyword(s):  
Mobile Applications ◽  
Empirical Investigation ◽  
Mobile Apps ◽  
Human Subjects ◽  
Sharing Economy ◽  
Support Vector ◽  
Word Embeddings ◽  
Mobile Software ◽  
Vector Machines ◽  
Modern Application

Modern application stores enable developers to classify their apps by choosing from a set of generic categories, or genres, such as health, games, and music. These categories are typically static—new categories do not necessarily emerge over time to reflect innovations in the mobile software landscape. With thousands of apps classified under each category, locating apps that match a specific consumer interest can be a challenging task. To overcome this challenge, in this article, we propose an automated approach for classifying mobile apps into more focused categories of functionally related application domains. Our aim is to enhance apps visibility and discoverability. Specifically, we employ word embeddings to generate numeric semantic representations of app descriptions. These representations are then classified to generate more cohesive categories of apps. Our empirical investigation is conducted using a dataset of 600 apps, sampled from the Education, Health&Fitness, and Medical categories of the Apple App Store. The results show that our classification algorithms achieve their best performance when app descriptions are vectorized using GloVe, a count-based model of word embeddings. Our findings are further validated using a dataset of Sharing Economy apps and the results are evaluated by 12 human subjects. The results show that GloVe combined with Support Vector Machines can produce app classifications that are aligned to a large extent with human-generated classifications.

Mobile Apps Threats

2019 ◽  
pp. 1021-1030
Author(s):  
Donovan Peter Chan Wai Loon ◽  
Sameer Kumar
Keyword(s):  
Mobile Devices ◽  
Mobile Applications ◽  
Mobile Apps ◽  
Mobile Platforms ◽  
Poor Risk ◽  
Current Trends ◽  
The World ◽  
Mobile Malware ◽  
Risk Communications

From adults to children, beginners to experts, and in numerous countries around the world, there is a diverse user base for mobile devices. However, the extensive use of mobile devices has also led to the proliferation and attacks of various mobile malware. The purpose of this chapter is to provide an overview of mobile malware. Subsequently, the chapter highlights the current trends and challenges posed by malicious mobile applications. The authors look into Android and iOS mobile platforms and discuss current research to detect malicious applications. Remedies for poor risk communications on Android-based devices are also suggested.

scholarly journals Reverse engineering approach for improving the quality of mobile applications

2019 ◽  
Author(s):  
Eman K. Elsayed ◽  
Kamal A. ElDahshan ◽  
Enas E. El-Sharawy ◽  
Naglaa E. Ghannam
Keyword(s):  
Reverse Engineering ◽  
Mobile Applications ◽  
Structural Design ◽  
Mobile Apps ◽  
Engineering Approach ◽  
Long Time ◽  
Android App ◽  
Android Applications ◽  
Programming Quality

Background: Portable applications (Android applications) are becoming increasingly complicated by mind-boggling programming frameworks. Applications must be produced rapidly and advance persistently in order to fit new client requirements and execution settings. However, catering to these imperatives may bring about poor outline decisions on design choices, known as anti-patterns, which may possibly corrupt programming quality and execution. Thus, the automatic detection of anti-patterns is a vital process that facilitates both maintenance and evolution tasks. Additionally, it guides developers to refactor their applications and consequently enhance their quality. Methods: We propose a reverse-engineering approach to analyze Android applications and detect the anti-patterns from mobile apps. We validate the effectiveness of our approach on a set of popular mobile apps such as YouTube, Whats App, Play Store and Twitter. The result of our approach produced an Android app with fewer anti-patterns, leading the way for perfect long-time apps and ensuring that these applications are purely valid. Results: The proposed method is a general detection method. It detected a set of semantic and structural design anti-patterns which have appeared 1262 times in mobile apps. The results showed that there was a correlation between the anti-patterns detected by an ontology editor and OntoUML editor. The results also showed that using ontology increases the detection percentage approximately 11.3%, guarantees consistency and decreases accuracy of anti-patterns in the new ontology.

scholarly journals Content Analysis of Mobile Device Applications for Artistic Creation for Children between 4 and 12 Years of Age

2021 ◽  
Vol 11 (23) ◽  
pp. 11327
Author(s):  
Sara Domínguez-Lloria ◽  
Rut Martínez López de Castro ◽  
Sara Fernández-Aguayo ◽  
Margarita Pino-Juste
Keyword(s):  
Content Analysis ◽  
Mobile Applications ◽  
Interface Design ◽  
Mobile Apps ◽  
Visual Design ◽  
Age Group ◽  
Creative Development ◽  
Device Applications ◽  
Interface Usability

This article presents the results of the content analysis of 32 painting and drawing mobile applications aimed at children between 4 and 12 years old. The characteristics of the artistic dimension were studied, such as the possibilities of drawing, color, and experimentation, as well as the characteristics of the technical dimension related to the visual design of the interface, usability, and adaptability to users. The results collected show that mobile apps offer tools that have great potential for artistic and creative development, but also reveal certain limitations and problems in the quality of the graphic tools and interface design. One of the central problems of the interfaces of these apps is related to decontextualization and the lack of attention to the diversity and the heterogeneity of users in that age group.

scholarly journals How do Technical Factors Affect Developers in Mobile Software Ecosystems

2019 ◽  
Author(s):  
Caio Steglich ◽  
Sabrina Marczak ◽  
Rodrigo Santos ◽  
Luiz Pedro Guerra ◽  
Luiz Henrique Mosmann ◽  
...  
Keyword(s):  
Literature Review ◽  
Field Study ◽  
Mobile Devices ◽  
Software Evolution ◽  
Real Life ◽  
Mobile Technologies ◽  
Software Ecosystem ◽  
Software Ecosystems ◽  
Mobile Software ◽  
Technical Factors

The Software Evolution area brings applications to the Mobile era in which users want to use these applications on their mobile devices. A Mobile Software Ecosystem (MSECO) is the kind of ecosystems in which developers build applications to attend the needs of mobile technologies users (e.g., Android and iOS). Literature explains that the capability to attracting and retaining people (i.e., developers and users) is essencial to MSECO sustainability, i.e., to the MSECO survive along the years. In a previous work, we conducted a literature review that identified 6 factors that may influence developers to participate in an MSECO. In this study, we present a Field Study aiming to understand how these 6 identified factors may have influenced practitioners in real life projects.

Characteristics and Quality of Mobile Applications for Prenatal Genetic Testing: An Assessment (Preprint)

2021 ◽  
Author(s):  
Ko-Lin Wu ◽  
Rebeca Alegria ◽  
Jazzlyn Gonzalez ◽  
Harrison Hu ◽  
Haocen Wang ◽  
...  
Keyword(s):  
Genetic Testing ◽  
Pregnant Women ◽  
Mobile Applications ◽  
Visual Information ◽  
Mobile Apps ◽  
Mobile App ◽  
Educational Tool ◽  
Prenatal Genetic Testing ◽  
Genetic Tests

BACKGROUND Prenatal genetic testing is an essential part of routine prenatal care. Yet, obstetricians often lack the time to provide comprehensive prenatal genetic testing education to their patients. Pregnant women lack prenatal genetic testing knowledge, which may hinder informed decision-making during their pregnancies. Due to the rapid growth of technology, mobile applications (apps) are a potentially valuable educational tool through which pregnant women can learn about prenatal genetic testing and improve the quality of their communication with obstetricians. The characteristics, quality, and number of available apps containing prenatal genetic testing information was, however, unknown. OBJECTIVE To conduct the first review to identify, evaluate, and summarize currently available prenatal genetic testing mobile apps using a systematic approach. METHODS We searched both the Apple App Store and Google Play to find mobile apps containing prenatal genetic testing information. The quality of apps was assessed based upon criteria adapted from two commonly used and validated mobile app scoring systems including “MARS” and “APPLICATIONS”. RESULTS Sixty-four mobile apps were identified. Of these, only two apps were developed for a specific prenatal genetic test. All other apps were either pregnancy-related (95.3%) or genetics (1.6%) apps that provided prenatal genetic testing information. The majority of the apps (76.5%) were developed by commercial companies. The mean quality assessment score of the included apps was 13.5, which was equal to the average of possible theoretical score. Overall, the main weaknesses of mobile apps in this review included the limited number of prenatal genetic tests mentioned, incomprehensiveness of testing information, unreliable and missing information sources, absence of developmental testing with users (not evidenced-based), high level of readability, and lack of visual information, customization, and a text search field. CONCLUSIONS Our findings suggest that the quality of prenatal genetic testing-related mobile apps must be improved, and that pregnant women should be cautious when utilizing these mobile apps for prenatal genetic testing information. Obstetricians should carefully examine mobile apps before referring any of them to their patients for use as an educational tool. Both improving the quality of existing mobile apps, and developing new, evidence-based, high-quality mobile apps targeting all prenatal genetic tests should be the focus of mobile app developers going forward.

Mobile Applications for Allergic Rhinitis

2018 ◽  
Vol 127 (11) ◽  
pp. 836-840 ◽  
Author(s):  
Albert H. Zhou ◽  
Varesh R. Patel ◽  
Soly Baredes ◽  
Jean Anderson Eloy ◽  
Wayne D. Hsueh
Keyword(s):  
Allergic Rhinitis ◽  
Operating Systems ◽  
Mobile Applications ◽  
Mobile Apps ◽  
Mobile App ◽  
App Store ◽  
Search Terms ◽  
Pollen Forecast ◽  
Google Play

Objective: To study and review the currently available mobile applications relating to allergic rhinitis. Methods: The Apple and Google mobile app stores were queried with search terms relating to allergic rhinitis. Apps were assigned to categories and analyzed based on description and characteristics such as popularity, reviews, cost, platform, and physician involvement in development. Results: A total of 72 apps related to allergic rhinitis were identified. Fifty-four apps were unique, with 18 apps found on both operating systems. Forty (55.5%) apps were available in the Apple App store, and 32 (44.4%) apps were available in the Google Play app store. They were grouped into the following categories: patient education (18; 25%), journals (15; 20.8%), symptom tracking (14; 19.4%), clinical/private practice (13; 18.1%), pollen forecast (7; 9.7%), medical education (4; 5.6%), and other (1; 1.4%). The majority of apps were free of charge (67; 93.1%), with paid apps ranging from $1.47 to $4.99. Apps that were reviewed had an average rating of 3.9 out of 5. Physicians were involved in the development of 37 (51.4%) apps. Conclusions: The collection of mobile apps developed for allergic rhinitis includes those for both educational and clinical use. Mobile apps may have an increasing role in otolaryngic allergy and rhinology practices in the future. Thus, continued research is warranted to determine the best way to ensure the accuracy and quality of app content as well as the extent mobile apps can benefit allergic rhinitis patients.

scholarly journals Diet-Related Mobile Apps to Promote Healthy Eating and Proper Nutrition: A Content Analysis and Quality Assessment

2021 ◽  
Vol 18 (7) ◽  
pp. 3496
Author(s):  
Jihye Choi ◽  
Chongwook Chung ◽  
Hyekyung Woo
Keyword(s):  
Quality Assessment ◽  
Mobile Applications ◽  
Rating Scale ◽  
Mobile Apps ◽  
Mobile App ◽  
Regression Analyses ◽  
Eligibility Criteria ◽  
Selection Of

Dietary mobile applications (apps) continue to hold promise for facilitating a healthy diet and managing nutrition. However, few studies have objectively evaluated the content and quality of such apps in Korea. The present study assessed the content and quality of dietary mobile apps using the Mobile App Rating Scale (MARS). We selected 29 dietary apps based on keywords and eligibility criteria for inclusion in the analyses. We conducted regression analyses to examine the association between app content and MARS scores. Most of the apps featured a tracking tool, while few featured rewards or follow-up management. Our quality assessment revealed that the top-rated apps have distinct levels of quality in terms of MARS scores. The regression analyses showed that the ways in which the apps provide information and motivate the users are statistically significant predictors of app quality. Our findings may facilitate the selection of dietary apps in Korea and provide guidelines for app developers regarding potential improvements in terms of content and quality.

scholarly journals Gamified Mobile Applications for Improving Driving Behavior: A Systematic Mapping Study

2021 ◽  
Vol 2021 ◽  
pp. 1-24
Author(s):  
Abderrahim El hafidy ◽  
Taoufik Rachad ◽  
Ali Idri ◽  
Ahmed Zellou
Keyword(s):  
Machine Learning ◽  
Mobile Applications ◽  
Mobile Apps ◽  
Driving Behavior ◽  
Machine Learning Algorithms ◽  
Machine Learning Techniques ◽  
Systematic Mapping Study ◽  
Mapping Study ◽  
Systematic Mapping ◽  
Learning Techniques

Many research works and official reports approve that irresponsible driving behavior on the road is the main cause of accidents. Consequently, responsible driving behavior can significantly reduce accidents’ number and severity. Therefore, in the research area as well as in the industrial area, mobile technologies are widely exploited in assisting drivers in reducing accident rates and preventing accidents. For instance, several mobile apps are provided to assist drivers in improving their driving behavior. Recently and thanks to mobile cloud computing, smartphones can benefit from the computing power of servers in the cloud for executing machine learning algorithms. Therefore, many mobile applications of driving assistance and control are based on machine learning techniques to adjust their functioning automatically to driver history, context, and profile. Additionally, gamification is a key element in the design of these mobile applications that allow drivers to develop their engagement and motivation to improve their driving behavior. To have an overview concerning existing mobile apps that improve driving behavior, we have chosen to conduct a systematic mapping study about driving behavior mobile apps that exist in the most common mobile apps repositories or that were published as research works in digital libraries. In particular, we should explore their functionalities, the kinds of collected data, the used gamification elements, and the used machine learning techniques and algorithms. We have successfully identified 220 mobile apps that help to improve driving behavior. In this work, we will extract all the data that seem to be useful for the classification and analysis of the functionalities offered by these applications.

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