Extracting Mapping Relations for Mobile User Interface Transformation

Migrating to Android for iOS Developers gives youas an experienced native iOS app developerthe skills to learn native Android apps development from scratch. Starting with preparing your Android integrated development environment and introducing just enough Android application framework fundamentals, youll understand how to create a simple but meaningful HelloAndroid project immediately. This book provides the guidelines and tutorial projects to show you how to translate your existing iOS app to the Android platform. Youll use your mobile app knowledge to structure your Android apps in a similar way to how you would structure your iOS apps. To implement use cases with detailed screens, the most common mobile topics are discussed, including user interfaces, managing data, and networking with remote services. As you move through the book, youll create Android apps with rich UI components to handle common CRUD operations locally and remotely. There are many Android goodies described in the book. Instead of relying on routine text descriptions, youll discover the uniqueness of Android and appreciate the many features that are unique to the platform. This book also explores more powerful mobile UX patterns that are commonly used on the iOS and Android platforms. When you finish reading Migrating to Android for iOS Developers, youll be an Android developer as well as an iOS developer. And, you will be fully convinced you can do everything in Android that you can do in iOS. What youll learn How to maximize your existing iOS mobile knowledge to learn Android programming skills How to use the Android integrated development environment with the Eclipse ADT plugin How to translate your existing iOS code to Android with the following common mobile topics: Common mobile screen navigation patterns User interface components and UI animations Storing data Networking and using remote services Using system apps Maps and location awareness Mobile search frameworks Mobile analyticsWho this book is for This book is for iOS app developerslike youwho want to port their native iOS app to become an Android app. Also, if you are not an iOS developer, but already familiar with mobile apps, then this book can also help you understand Android development with step-by-step instructions and tutorial projects.

Mobile app development within mental health is often time- and resource-consuming, challenging the development of mobile apps for psychiatry. There is a continuum of software development methods ranging from linear (waterfall model) to continuous adaption (Scrum). Rapid application development (RAD) is a model that so far has not been applied to psychiatric settings and may have some advantages over other models. This study aims to explore the utility of the RAD model in developing a mobile app for patients with borderline personality disorder (BPD) in a psychiatric outpatient setting. The 4 phases of the RAD model: (1) requirements planning, (2) user design, (3) construction, and (4) cutover, were applied to develop a mobile app within psychiatric outpatient services for patients diagnosed with BPD. For the requirements planning phase, a short time frame was selected to minimize the time between product conceptualization and access within a clinical setting. Evidenced-based interactive content already developed was provided by current staff to enhance usability and trustworthiness. For the user design phase, activity with video themes and a discrete number of functions were used to improve the app functionality and graphical user interface. For the construction phase, close collaboration between clinicians, researchers, and software developers yielded a fully functional, in-house-developed app ready to be tested in clinical practice. For the cutover phase, the mobile app was tested successfully with a small number (n=5) of patients with a BPD. The RAD model could be meaningfully applied in a psychiatric setting to develop an app for BPD within a relatively short time period from conceptualization to implementation in the clinic. Short time frames and identifying a limited number of stakeholders with relevant skills in-house facilitated the use of this model. Despite some limitations, RAD could be a useful model in the development of apps for clinical populations to enable development and access to evidence-based technology.

Most of today's mobile apps rely on the underlying networks to deliver key functions such as web browsing, file synchronization, and social networking. Compared to desktop-based networks, mobile networks are much more dynamic with frequent connectivity disruptions, network type switches, and quality changes, posing unique programming challenges for mobile app developers. As revealed in this paper, many mobile app developers fail to handle these intermittent network conditions in the mobile network programming. Consequently, network programming defects (NPDs) are pervasive in mobile apps, causing bad user experiences such as crashes, data loss, etc. Despite the development of network libraries in the hope of lifting the developers' burden, we observe that many app developers fail to use these libraries properly and still introduce NPDs. In this paper, we study the characteristics of the real-world NPDs in Android apps towards a deep understanding of their impacts, root causes, and code patterns. Driven by the study, we build NChecker, a practical tool to detect NPDs by statically analyzing Android app binaries. NChecker has been applied to hundreds of real Android apps and detected 4180 NPDs from 285 randomly-selected apps with a 94+% accuracy. Our further analysis of these defects reveals the common mistakes of app developers in working with the existing network libraries' abstractions, which provide insights for improving the usability of mobile network libraries.

ObjectivesTechnology in the form of mobile apps has played an essential role in facilitating, tracking, and maintaining health and fitness activities during the pandemic. When countries opted for partial or complete lockdowns to contain the spread of the coronavirus disease 2019 virus, it led to people working on their health and fitness-related activities from their homes, just as they continued working from home. This paper aims to quantify the impact of coronavirus disease 2019 on the development of health and fitness mobile apps. Specifically, we compute the effect of coronavirus disease 2019 on the growth of different sub-categories of health and fitness apps.MethodsWe scraped data about a population of 78,890 health and fitness apps from the iOS App Store. First, categories of health and fitness apps are identified using text analysis on the descriptions of apps. Second, the rise in the development of new apps is analyzed. To quantify the impact of coronavirus disease 2019 on the growth of the health and fitness apps, multiple time-series forecasting models are created for different categories of health and fitness apps.ResultsThe text analysis identified twelve different types of health and fitness apps on the app market. Our models estimated that the number of health and fitness apps on the iOS app market exceeded the expected growth by 29.9% after the pandemic. The results of all categories of health and fitness are discussed in the paper.ConclusionsOur analysis found significant growth in the development of new health and fitness apps after the pandemic outbreak. The post hoc study of the population of health and fitness apps presented the current state of this particular area of the app market. In addition, it provided potential growth areas in app markets where there are fewer apps.

This article describes how the mobile app market is growing day by day. Mobile app stores have created the opportunity for the users to publicly provide feedback on mobile apps that they have installed or used. In this way, users are involved in the design and development of mobile apps, which was done by designers and developers before. Online user reviews are a useful source to know the user's perception about mobile apps and thus provide a way of co-value creation. This article is conducted to investigate the factors affecting the acceptability of mobile Apps. Main purpose of this article is to use online reviews for construction of a model instead of using existing acceptance theories. The model proposed in this research is based on the analysis of reviews and app information extracted from the Google Play Store. The ratings and number of installs are two key indicators of the popularity of an app. Other characteristics like price, category and size also influence the user's selection of an app. The findings showed the appropriateness of the proposed model and hypotheses for evaluating mobile apps acceptability and popularity. This article provides mobile app developers and marketers with an insight into the mobile app popularity and acceptability dynamics.

Mobile app development has been considered as one of the fastest growing segments of the software industry both worldwide and in Saudi Arabia. Due to their pervasiveness, mobile applications call for consideration of complex and rapidly changing requirements given the diversity of their environments. Therefore, agile is considered the most suitable methodology for developing mobile apps. However, little research has investigated agile adoption in mobile app development in the real context. Therefore, the purpose of this PhD is to investigate the factors that have a significant impact on agile adoption in mobile app development by small and medium-size software organisations in Saudi Arabia. The expected key contribution of this research will be a deep insight into agile adoption in mobile app development, and the design and development of tools and techniques that may support agile adoption within Saudi context.

Aim/Purpose: This paper focuses on app review analysis techniques, driven by the rapid advancement of the mobile app market and NLP techniques in optimizing mobile app user experiences. Background: Owing to technological advancements, app review analysis has rapidly evolved. This study examines both conventional and emerging techniques, including current advancements such as large language models (LLMs) in app review analysis. It provides an overview of the various methods used across different categories of app review analysis, comparing effective strategies for identifying user concerns and enhancing app functionality. Methodology: A systematic review was utilized based on two major standard guidelines, PRISMA and Kitchenham’s guidelines, for the period of 2014 to 2024. After defining the review protocol, papers were identified through keyword-based searches on six major online databases: Scopus, Web of Science, IEEE Xplore, ACM Digital Library, Science Direct, and Springer. Following screening and excluding papers based on defined quality criteria, 53 papers were considered for this study. The use of PRISMA ensures a transparent and reproducible review process, while Kitchenham’s guidelines provide a structured and rigorous approach for evaluating and synthesizing the literature. Contribution: This review study aims to evaluate the current state of knowledge on app review analysis techniques to improve mobile app user experiences. This study categorized the existing state-of-the-art papers into eight different categories, such as sentiment analysis, review classification, summarization, and prioritization, and examined challenges related to app review analysis. Furthermore, the study emphasizes the potential of LLMs for optimizing and automating app review analysis and provides future directions to address gaps in user-centric app development. Findings: Among the eight main categories defined in app review analysis, sentiment analysis is the most prevalent, followed by review classification and information extraction. Most studies use a combination of these categories to achieve a comprehensive goal. Prioritization techniques such as risk matrices, thumbs-up count-based approach, and anomaly detection are widely used to identify emerging issues. Extracting meaningful information and evaluating the proposed approach are the most common challenges identified. Novel LLMs, like Chat-GPT, significantly enhance review analysis by automating the process, improving feature extraction, and enabling context-aware review classification. Recommendations for Practitioners: The combination of conventional approaches and novel LLM-based methods can enhance both the efficiency and accuracy in identifying and addressing critical issues raised through mobile app user reviews. It effectively prioritizes user concerns by leveraging the strengths of both traditional preprocessing techniques and advanced LLMs. Recommendation for Researchers: Researchers are encouraged to explore the integration of emerging technologies like LLMs to enhance the of app review analysis, particularly in feature-specific sentiment analysis. Impact on Society: The results of this study contribute to enhancing the mobile app user experience through effective app review analysis, which improves user satisfaction and supports user-centered app development. This ultimately leads to a better mobile app ecosystem, benefiting both users and developers. Future Research: In the future, this research can be extended in multiple directions. Researchers can address the existing research gaps that LLMs have yet to address, particularly in prioritizing user concerns. Additionally, there is potential for further research on tool implementations focusing on identifying persistent issues through time series analysis by considering the app version and date of the app reviews. Moreover, there is a need to develop comprehensive frameworks that are more generalizable across different apps and categories, with a focus on identifying user concerns related to specific features.

BackgroundOver the past few years, studies have increasingly focused on the development of mobile apps as complementary tools to existing traditional pharmacovigilance surveillance systems for improving and facilitating adverse drug reaction (ADR) reporting.ObjectiveIn this research, we evaluated the potentiality of a new mobile app (vaxEffect@UniMiB) to perform longitudinal studies, while preserving the anonymity of the respondents. We applied the app to monitor the ADRs during the COVID-19 vaccination campaign in a sample of the Italian population.MethodsWe administered vaxEffect@UniMiB to a convenience sample of academic subjects vaccinated at the Milano-Bicocca University hub for COVID-19 during the Italian national vaccination campaign. vaxEffect@UniMiB was developed for both Android and iOS devices. The mobile app asks users to send their medical history and, upon every vaccine administration, their vaccination data and the ADRs that occurred within 7 days postvaccination, making it possible to follow the ADR dynamics for each respondent. The app sends data over the web to an application server. The server, along with receiving all user data, saves the data in a SQL database server and reminds patients to submit vaccine and ADR data by push notifications sent to the mobile app through Firebase Cloud Messaging (FCM). On initial startup of the app, a unique user identifier (UUID) was generated for each respondent, so its anonymity was completely ensured, while enabling longitudinal studies.ResultsA total of 3712 people were vaccinated during the first vaccination wave. A total of 2733 (73.6%) respondents between the ages of 19 and 80 years, coming from the University of Milano-Bicocca (UniMiB) and the Politecnico of Milan (PoliMi), participated in the survey. Overall, we collected information about vaccination and ADRs to the first vaccine dose for 2226 subjects (60.0% of the first dose vaccinated), to the second dose for 1610 subjects (43.4% of the second dose vaccinated), and, in a nonsponsored fashion, to the third dose for 169 individuals (4.6%).ConclusionsvaxEffect@UniMiB was revealed to be the first attempt in performing longitudinal studies to monitor the same subject over time in terms of the reported ADRs after each vaccine administration, while guaranteeing complete anonymity of the subject. A series of aspects contributed to the positive involvement from people in using this app to report their ADRs to vaccination: ease of use, availability from multiple platforms, anonymity of all survey participants and protection of the submitted data, and the health care workers’ support.

Due to the advance of mobile technology, use of mobile devices such as smartphones has been growing rapidly in the U.S. and worldwide. Many health related mobile apps have been developed for care professionals and patients as well. However, studies indicate that there is a gap between science and commercially developed mobile apps. In addition to this, there is no framework to guide devlopment of a mobile app to overcome many challenges and obstacles. Through the development of a pain management mobile app for cancer patients, a framework was developed. A proposed framework was based on the technology acceptance model, ensuring usefulness and ease of use for end users. The first two steps in the framework enforce accurate knowledge translation and communication to build a science based mobile app. Iterative decisions points between steps enhance accomplishment of each step.

Problem definition: In today’s highly dynamic and competitive app markets, a significant portion of development takes place after the initial product launch via the addition of new features and the enhancement of existing products. In managing the sequential innovation process in mobile app development, two key operational questions arise. (i) What features and attributes should be added to existing products in successive versions? (ii) How should these features and attributes be implemented for greater market success? We investigate the implications of three different types of mobile app development activities on market performance. Academic/practical relevance: Our study contributes to the operations management literature by providing an empirically based understanding of sequential innovation and its market performance implications in mobile app development, an important industry in terms of size, scope and potential. Methodology: Using a novel data set of mobile apps in the Productivity category, we leverage text-mining and information retrieval techniques to study the rich information in the release notes of apps. We then characterize product development activities at each version release and link these activities with app performance in a dynamic estimation model. We also incorporate an instrumental variables analysis to substantiate our findings. Results: We find that greater update dissimilarity (i.e., dissimilarity of the features and attributes of a new update from those of previous updates) is associated with higher performance, especially in mature apps. We also find that the greater the product update market orientation (i.e., the greater the similarity of the focal firm’s new features and attributes with respect to the recent additions of its competitors), the higher is the market performance. This finding suggests that the market rewards those developers who have a responsive policy to their competitors’ product innovation efforts. Our results also suggest that a rapid introduction of updates dampens the potential market benefits that the mobile app developers might gain from market orientation. We find no evidence of a beneficial effect of product update scope (i.e., incorporating features and attributes from other product subcategories) on market performance. Managerial implications: Our study offers managerial insights into mobile app development by exploring the sequential innovation characteristics that are associated with greater market success in pursuing and implementing new features and attributes. Supplemental Material: The online appendices are available at https://doi.org/10.1287/msom.2022.1154 .

Net neutrality or “Open Internet” rulemaking has been ongoing for more than a decade. Some 50 nations have adopted formal rules including the US (then repealed), the European Union, India, and many countries in Latin America. Among other arguments, it is asserted that net neutrality rules are necessary for application innovation. While the focus for policymakers has largely been to make rules, there is less attention on how to measure the impact of such rules and how well they achieve their innovation goals. The article summaries a specific research investigation to what degree the introduction of rules in a given country stimulates innovation in that country’s mobile app ecosystem. The focus in on mobile networks because it allowed the most consistent data across countries. The study covered 53 countries, their net neutrality policies (or lack thereof), and the results to the respective mobile application ecosystems of the countries adopting rules between the period of 2010–2016. This investigation tests the proposition that countries which adopt net neutrality rules should experience an increase in mobile app development innovation within their national economy. To test this, a statistical methodology was developed based upon measuring the number of locally developed mobile apps in the country for relevant periods before and after rules are imposed and the corresponding app downloads, usage, and revenue. Measurement was conducted with two independent toolsets and adjusted for the sophistication and penetration of advanced mobile networks in the country. To make more meaningful comparisons and avoid inevitable heterogeneity across the countries, the investigation focuses on two similar countries with different rules, Denmark with soft rules (self-regulation) and Netherlands with hard rules (legislation). The study reviewed the leading theories of innovation as well as the foundational papers in net neutrality to explain the observed discrepancies. The research finds significant statistical support for “soft” net neutrality measures adopted on a voluntary basis. Hard rules adopted through legislation and regulation were not associated with greater mobile app development for the given country. Denmark increased in local mobile app development while Netherlands decreased. Additionally, the explosion of mobile apps from countries with no net neutrality rules and the general dearth of mobile apps from countries which have had hard rules for years runs counter to expected results. This suggests that policymakers revisit their assumptions and expectations for net neutrality policy.

Background/Purpose:We are living in an era where many disruptive technologies have emerged that have changed the entire perception of the business world. One of them is the emergence of mobile application development, which has completely changed the way people use software. While in the past software development usually meant single or web applications, now there is a huge scope for mobile application development. Standalone technologies require users to have at least one personal computer to use their applications. However, since the only platform on which the application can be used is the mobile phone, the target audience for the development of this application does a lot. Mobile app development has now become a norm for services to reach their destinations faster because almost everyone has access to mobile devices. The app development industry has grown at a rapid pace since its inception. This article covers the mobile app industry and its management in India in detail. Objectives: Analyze and understand the mobile app industry globally and in India, understand the trends, usage, revenue, cost and performance of app development in India Answer and perform SWOC analysis of the mobile app industry.

Given the attributes of mobile apps that shorten the time to make purchase decisions while enabling easy purchase cancellations, usability can be regarded to be a highly prioritized quality attribute among the diverse quality attributes that must be provided by mobile apps. With that backdrop, mobile app developers have been making great effort to minimize usability hampering elements that degrade the merchantability of apps in many ways. Most elements that hamper the convenience in use of mobile apps stem from those potential errors that occur when GUIs are designed. In our previous study, we have proposed a technique to analyze the usability of mobile apps using user behavior logs. We proposes a technique to detect usability hampering elements lying dormant in mobile apps` GUI models by expressing user behavior logs with finite state models, combining user behavior models extracted from multiple users, and comparing the combined user behavior model with the expected behavior model on which the designer`s intention is reflected. In addition, to reduce the burden of the repeated test operations that have been conducted by existing developers to detect usability errors, the present paper also proposes a mobile usability error detection automation tool that enables automatic application of the proposed technique. The utility of the proposed technique and tool is being discussed through comparison between the GUI issue reports presented by actual open source app developers and the symptoms detected by the proposed technique.

A mobile user interface (UI) is a graphical and usually touch-sensitive display on a mobile device that allows the user to interact with the device’s apps, features, contents, and functions. Since people of the elderly age group were not as exposed to technology as much as the people of the present generation, they face hurdles while using mobile apps. Furthermore, designers also face difficulties while designing user interfaces for elderly users. It is difficult for them to determine whether a designed UI component will be perceived by the elderly users as per its purpose. An elderly user may perceive a tappable UI component as not tappable and vice versa. Therefore, the objective of this research is to propose a conceptual framework for developing an efficient system to evaluate whether an UI is usable to the elderly people or not considering the tappability of its (UI) components. As outcomes, a deep learning-based conceptual framework for such a system is proposed based on the identified user-requirements through semi-structured interviews. An initial UI prototype of the system is also developed and evaluated by the real end-users. It is expected that the conceptual framework will be able to pave the way for developing a system to help the elderly user by increasing the usability of the UIs and to aid the designers in designing intuitive UIs considering the limitations of the elderly user. KeywordsUsabilityMobile user interfaceTappabilityDeep learningElderly users

Smart City services' effectiveness is enabled by the integration and availability of data coming from city operators on different domains: mobility, energy, health, water, telecom, tourism, culture, etc. They may be open and private data, static and real time. The most cases, smart city developers still have to develop their applications by studying several data sets and API sources, recovering the data models, reconciliating and aggregating data manually, creating applications exploiting low level Web Service and/or REST Call without the support of development tools, and neither of a semantic data aggregator. In this paper, an innovative tool for smart city web and mobile Apps development is presented. It exploits the Km4City data aggregator and semantic model, and includes: (i) tools for assisting developers for generating calls to Smart City API via visual queries on a graphical user interface; and (ii) open source Apps Development Kit for shortening the development. Finally, the paper reports about experimental results performed in the usage of the tool in the context of a large national project called Sii-Mobility which involved several developers. The same approach is presently adopted by other large projects as well.