scholarly journals Automated Bidirectional Languages Localization Testing for Android Apps with Rich GUI

2016 ◽  
Vol 2016 ◽  
pp. 1-13 ◽  
Author(s):  
Aiman M. Ayyal Awwad ◽  
Wolfgang Slany

Mobile apps are everywhere. The release of apps on a worldwide scale requires them to be made available in many languages, including bidirectional languages. Developers and translators are usually different persons. While automatic testing by itself is important in general in order to be able to develop high quality software, such automatic tests become absolutely essential when developers that do not possess enough knowledge about right-to-left languages need to maintain code that is written for bidirectional languages. A few bidirectional localization tests of mobile applications exist. However, their functionality is limited since they only cover translations and adoption of locales. In this paper we present our approach for automating the bidirectional localization testing for Android applications with a complete consideration for BiDi-languages issues. The objective is to check for any localization defects in the product. The proposed methods are used to test issues of bidirectional apps in general and specifically for the Arabic language. The results show that the methods are able to effectively reveal deficiencies in the app’s design, ensure that the localized app matches all expectations of local users, and guarantee that the product is culturally congruent to local conventions.

2021 ◽  
Vol 26 (4) ◽  
Author(s):  
Jordan Samhi ◽  
Kevin Allix ◽  
Tegawendé F. Bissyandé ◽  
Jacques Klein

AbstractDue to the convenience of access-on-demand to information and business solutions, mobile apps have become an important asset in the digital world. In the context of the COVID-19 pandemic, app developers have joined the response effort in various ways by releasing apps that target different user bases (e.g., all citizens or journalists), offer different services (e.g., location tracking or diagnostic-aid), provide generic or specialized information, etc. While many apps have raised some concerns by spreading misinformation or even malware, the literature does not yet provide a clear landscape of the different apps that were developed. In this study, we focus on the Android ecosystem and investigate Covid-related Android apps. In a best-effort scenario, we attempt to systematically identify all relevant apps and study their characteristics with the objective to provide a first taxonomy of Covid-related apps, broadening the relevance beyond the implementation of contact tracing. Overall, our study yields a number of empirical insights that contribute to enlarge the knowledge on Covid-related apps: (1) Developer communities contributed rapidly to the COVID-19, with dedicated apps released as early as January 2020; (2) Covid-related apps deliver digital tools to users (e.g., health diaries), serve to broadcast information to users (e.g., spread statistics), and collect data from users (e.g., for tracing); (3) Covid-related apps are less complex than standard apps; (4) they generally do not seem to leak sensitive data; (5) in the majority of cases, Covid-related apps are released by entities with past experience on the market, mostly official government entities or public health organizations.


2019 ◽  
Author(s):  
José Javier Flors-Sidro ◽  
Mowafa Househ ◽  
Alaa Abd-Alrazaq ◽  
Josep Vidal-Alaball ◽  
Luis Fernandez-Luque ◽  
...  

BACKGROUND Mobile health has become a major channel for the support of people living with diabetes. Accordingly, the availability of diabetes mobile apps has been steadily increasing. Most of the previous reviews of diabetes apps have focused on the apps’ features and their alignment with clinical guidelines. However, there is a lack of knowledge on the actual compliance of diabetes apps with privacy and data security aspects. OBJECTIVE The aim of this study was to assess the level of privacy of diabetes mobile applications to contribute to raising the awareness of final users, developers and data-protection governmental regulators towards privacy issues. METHODS A web scraper capable of retrieving Android apps’ privacy-related information, particularly the dangerous permissions required by the apps, was developed with the aim of analyzing privacy aspects related to diabetes apps. Following the research selection criteria, the original 882 apps were narrowed down to 497 apps, which were finally included in the analysis. RESULTS 60% of diabetes apps may request dangerous permissions, which poses a significant risk for the users’ data privacy. In addition, 30% of the apps do not return their privacy policy website. Moreover, it was found that 40% of apps contain advertising, and that some apps that declared not to contain it actually had ads. 95.4% of the apps were free of cost, and those belonging to the Medical and Health and Fitness categories were the most popular. However, final users do not always realize that the free-apps’ business model is largely based on advertising, and consequently, on sharing or selling their private data, either directly or indirectly, to unknown third-parties. CONCLUSIONS The aforementioned findings unquestionably confirm the necessity to educate users and raise their awareness regarding diabetes apps privacy aspects. For this purpose, this research recommends properly and comprehensively training users, ensuring that governments and regulatory bodies enforce strict data protection laws, devising much tougher security policies and protocols in Android and in the Google Play Store, and the implication and supervision of all stakeholders in the apps’ development process.


2019 ◽  
Author(s):  
Eman K. Elsayed ◽  
Kamal A. ElDahshan ◽  
Enas E. El-Sharawy ◽  
Naglaa E. Ghannam

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.


2018 ◽  
Vol 9 (3) ◽  
pp. 1
Author(s):  
Lucas Pedroso Carvalho ◽  
Felipe Silva Dias ◽  
André Pimenta Freire

The choice of an interface platform to develop mobile applications may have important implications to how accessible the resulting product can be for visually-disabled users. This paper aimed to analyze four platforms to develop native and web-hybrid mobile Android applications, and to verify the adequacy of their interface components to implement mobile applications, in order to identify the main accessibility problems that could be encountered by developers when using them, and the main strategies to overcome those issues. We built 5 prototypes of mobile applications with the aim of adhering as much as possible to accessibility recommendations. The applications were built using techniques of native applications developed with Android Studio with and without Web components and hybrid development using the frameworks Apache Cordova, Ionic and Appcelerator Titanium. We then performed an accessibility inspection of a sample of 30 Android interface components present in 5 prototypes of mobile applications, to verify their adequacy for working with screen readers. The results showed that the prototypes developed using web components were more compatible with accessibility criteria in the Web Content Accessibility Guidelines (WCAG 2.0) and with the screen reader TalkBack. The most frequent accessibility problems in native components occurred in tables, headings and multimedia elements. We conclude by showing initial evidence that webbased components in hybrid applications developed using webhybrid and native with embedded web components currently have better support for accessibility than applications with only native components.


2019 ◽  
Author(s):  
Eman K. Elsayed ◽  
Kamal A. ElDahshan ◽  
Enas E. El-Sharawy ◽  
Naglaa E. Ghannam

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.


Author(s):  
Luis Cruz ◽  
Rui Abreu

The ever-growing popularity of mobile phones has brought additional challenges to the software development lifecycle. Mobile applications ought to provide the same set of features as conventional software, with limited resources: such as limited processing capabilities, storage, screen and, not less important, power source. Although energy efficiency is a valuable requirement, developers often lack knowledge of best practices. In this paper, we propose a tool to improve the energy efficiency of Android applications using automatic refactoring — Leafactor. The tool features five energy code smells that tend to go unnoticed. In addition, we study whether automatic refactoring can aid developers to ship energy efficient mobile applications with a dataset of 140 free and open source apps. As a result, we detect and fix code smells in 45 Android apps, from which 40% have successfully merged our changes into the official repository.


2018 ◽  
Vol 18 ◽  
pp. 03002
Author(s):  
Anton Kukanov ◽  
Elena Andrianova

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.


2020 ◽  
Author(s):  
Nurul Asilah Ahmad ◽  
Shahrul Azman Mohd Noah ◽  
Arimi Fitri Mat Ludin ◽  
Suzana Shahar ◽  
Noorlaili Mohd Tohit

BACKGROUND Currently, the use of smartphones to deliver health-related content has experienced a rapid growth, with more than 165,000 mobile health (mHealth) applications currently available in the digital marketplace such as iOS store and Google Play. Among these, there are several mobile applications (mobile apps) that offer tools for disease prevention and management among older generations. These mobile apps could potentially promote health behaviors which will reduce or delay the onset of disease. However, no review to date that has focused on the app marketplace specific for older adults and little is known regarding its evidence-based quality towards the health of older adults. OBJECTIVE The aim of this review was to characterize and critically appraise the content and functionality of mobile apps that focuses on health management and/or healthy lifestyle among older adults. METHODS An electronic search was conducted between May 2019 to December 2019 of the official app store for two major smartphone operating systems: iPhone operating system (iTunes App Store) and Android (Google Play Store). Stores were searched separately using predetermined search terms. Two authors screened apps based on information provided in the app description. Metadata from all included apps were abstracted into a standard assessment criteria form. Evidenced based strategies and health care expert involvement of included apps was assessed. Evidenced based strategies included: self-monitoring, goal setting, physical activity support, healthy eating support, weight and/or health assessment, personalized feedback, motivational strategies, cognitive training and social support. Two authors verified the data with reference to the apps and downloaded app themselves. RESULTS A total of 16 apps met the inclusion criteria. Six out of 16 (37.5%) apps were designed exclusively for the iOS platform while ten out of 16 (62.5%) were designed for Android platform exclusively. Physical activity component was the most common feature offered in all the apps (9/16, 56.3%) and followed by cognitive training (8/16, 50.0%). Diet/nutrition (0/16, 0%) feature, however, was not offered on all reviewed mobile apps. Of reviewed apps, 56.3% (9/16) provide education, 37.5% (6/16) provide self-monitoring features, 18.8% (3/16) provide goal setting features, 18.5% (3/16) provide personalized feedback, 6.3% (1/16) provide social support and none of the reviewed apps offers heart rate monitoring and reminder features to the users. CONCLUSIONS All reviewed mobile apps for older adults in managing health did not focused on diet/nutrition component, lack of functional components and lack of health care professional involvement in their development process. There is also a need to carry out scientific testing prior to the development of the app to ensure cost effective and its health benefits to older adults. Collaborative efforts between developers, researchers, health professionals and patients are needed in developing evidence-based, high quality mobile apps in managing health prior they are made available in the app store.


2020 ◽  
Author(s):  
Reham AlTamime ◽  
Vincent Marmion ◽  
Wendy Hall

BACKGROUND Mobile apps and IoT-enabled smartphones technologies facilitate collecting, sharing, and inferring from a vast amount of data about individuals’ location, health conditions, mobility status, and other factors. The use of such technology highlights the importance of understanding individuals’ privacy concerns to design applications that integrate their privacy expectations and requirements. OBJECTIVE This paper explores, assesses, and predicts individuals’ privacy concerns in relation to collecting and disclosing data on mobile health apps. METHODS We designed a questionnaire to identify participants’ privacy concerns pertaining to a set of 432 mobile apps’ data collection and sharing scenarios. Participants were presented with 27 scenarios that varied across three categorical factors: (1) type of data collected (e.g. health, demographic, behavioral, and location); (2) data sharing (e.g., whether it is shared, and for what purpose); and, (3) retention rate (e.g., forever, until the purpose is satisfied, unspecified, week, or year). RESULTS Our findings show that type of data, data sharing, and retention rate are all factors that affect individuals’ privacy concerns. However, specific factors such as collecting and disclosing health data to a third-party tracker play a larger role than other factors in triggering privacy concerns. CONCLUSIONS Our findings suggest that it is possible to predict privacy concerns based on these three factors. We propose design approaches that can improve users’ awareness and control of their data on mobile applications


Author(s):  
Rizky Putri Fajriati ◽  
Dewi Khairani ◽  
Nurul Faizah Rozy ◽  
Nanang Husin ◽  
Lisa Wiyartanti ◽  
...  
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