Cross-platform Framework Research Articles

Comparison of performance of Xamarin and Flutter cross-platform frameworks

This article conducts a performance comparative study of two cross-platform development frameworks: Flutter and Xamarin. For this purpose, two test applications running on Android were developed, implementing the same functions, i.e. CRUD operations on the database and sorting an array of objects by the Merge Sort algorithm. Tests were performed on an emulator and on a physical device. The sorted arrays had different sizes, and database operations were performed for different sizes of data sets. The metric used for comparisons was the average implementation time of a given operation. The analysis of the research results showed that Xamarin was definitely more efficient in three CRUD operations, while Flutter performed computational operations, which in this case was sorting, much faster.

What Do Flutter Developers Ask About? An Empirical Study on Stack Overflow Posts

Since Google launched Flutter, an open-source framework, in 2017, many companies and software developers have turned to its use owing to its cross-platform feature. Other attractive features include hot reloading, a rich widget library, and improved performance compared to other cross-platform frameworks. Despite the rise in the use and adoption of the framework, little has been done to understand developers’ challenges. This study aims to understand what Flutter developers post on Stack Overflow – a popular Q&A website for developers. Analyzing such posts would help us understand the challenges faced by Flutter developers. To meet this goal, the study used a topic modeling approach to analyze all “flutter” tagged posts between 2019 and 2023. This study revealed state management, widgets, navigation, packages, and persistence as some areas developers face challenges. Further, the study established that there is a growth in the number of Flutter-related posts and developers. While the Flutter framework is promising for companies and software developers, this study points out areas where Flutter trainers and developers should emphasize. Flutter Framework developers should provide more documentation and support as the language matures.

ПРОЕКТ ИНФОРМАЦИОННОЙ СИСТЕМЫ «СТОИМОСТЬ ЖИЗНИ В РЕГИОНАХ РОССИИ» НА ASP.NET CORE

In the course of work on the project, the implementation of an information system is considered, which displays the average cost of the consumer basket depending on the region. The development of the information system is carried out using a free cross-platform framework for creating web appli-cations on the .NET open source platform

Prediction of Cross-Platform and Native Apps Technology Opportunities for Beginner Developers Using C 4.5 and Naive Bayes Algorithms

The competition between native and cross-platform app development makes application development simpler, safer, and more scalable. However, this makes developers must have sufficient fundamentals and the industry must conduct good research to shorten development time and minimize expenses. In order to solve these problems, this study made a prediction that discusses the technology that has a chance to survive in the industry so as not to be left behind in technology. The use of Naïve Bayes and C 4.5 algorithms into a dataset that has 9 programming languages related to mobile app development. Results obtained in This research is Dart as a programming language that supports cross-platform frameworks and Kotlin as a programming language that supports native apps frameworks is a technology that will have the opportunity in the future with an accuracy level above 90% with Naïve Bayes and C 4.5 algorithms. These results are obtained by considering the results of testing an algorithm model using MAPE, consistent dataset sharing, and careful data processing. Expected this research Can help entry-level developers learn and deepen the fundamentals of technology and can add knowledge to the industry in choosing a technology.

Prediction of Cross-Platform and Native Apps Technology Opportunities for Beginner Developers Using C 4.5 and Naive Bayes Algorithms

The competition between native and cross-platform app development makes application development simpler, safer, and more scalable. However, developers must have sufficient fundamentals, and the industry must conduct good research to shorten development time and minimize expenses. In order to solve these problems, this study made a prediction that discusses the technology that has a chance to survive in the industry so as not to be left behind in technology. Using Naïve Bayes and C 4.5 algorithms into a dataset with nine programming languages related to mobile app development. Results obtained in This research show Dart as a programming language that supports cross-platform frameworks and Kotlin as a programming language that supports native app frameworks is a technology that would have the opportunity in the future with an accuracy level above 90% with Naïve Bayes and C 4.5 algorithms. These results are obtained by testing an algorithm model using MAPE, consistent dataset sharing, and careful data processing. This research Can help entry-level developers learn and deepen the fundamentals of technology and can add knowledge to the industry in choosing a technology.

Development of a Workflow Management System for Higher Education: A case study of the Department of Mathematical and Computer Sciences, Fountain University, Osogbo.


 Abstract— The growing complexity of academic and administrative processes in educational institutions necessitates an efficient and streamlined approach to managing workflows effectively. The research work presents the development of a cutting-edge Workflow Management System (WMS) designed to cater to the needs of the Department of Mathematical and Computer Sciences. The WMS is built using Flutter, a popular cross-platform framework, and Firebase, a scalable and cloud-based backend service. These challenges underscore the importance of a tailored WMS that can centralize communication, automate tasks, and enhance productivity. This research project encompasses a systematic approach, beginning with requirements gathering through observation and prototyping, followed by the design and development phases. Agile development principles were employed to ensure flexibility and adaptability throughout the project life-cycle. The outcomes of the research work, including any improvements made based on user feedback. This research has significantly improved communication efficiency, task allocation, and time management. Users reported increased collaboration, reduced delays, and better organization of academic and administrative activities and the potential to improve the efficiency and accuracy of collaboration management within the department and enhance the user experience for both the collaboration department and the college community. The developed workflow Management System proved valuable for the department, addressing their needs and streamlining their workflows. The successful integration of Flutter and Firebase showcased the potential of modern technologies to revolutionize traditional processes in educational institutions.

An Observational Study on React Native (RN) Questions on Stack Overflow (SO)

Mobile applications are continuously increasing in prevalence. One of the main challenges in mobile application development is creating cross-platform applications. To facilitate developing cross-platform applications, the software engineering community created several solutions, one of which is React Native (RN), which is a popular cross-platform framework. The software engineering literature demonstrated the effectiveness of Stack Overflow (SO) in providing real-world perspectives on a variety of technical subjects. Therefore, this study aims to gain a better understanding of the stance of RN on SO. We identified and analyzed 131,620 SO RN-related questions. Moreover, we observed how the interest toward RN on SO evolves over time. Additionally, we utilized Latent Dirichlet Allocation (LDA) to identify RN-related topics that are discussed within the questions. Afterward, we utilized a number of proxy measures to estimate the popularity and difficulty of these topics. The results revealed that interest toward RN on SO was generally increasing. Moreover, RN-related questions revolve around six topics, with the topics of layout and navigation being the most popular and the topic of iOS issues being the most difficult. Software engineering researchers, practitioners, educators, and RN contributors may find the results of this study beneficial in guiding their future RN efforts.

Review on Comparative Study of Flutter App and Android App

Abstract: In today lives, mobile application can be increasing vital. In flutter is a cross platform framework and other native mobile application is one particular operating system. The time of 2015 year mobile application development increasing day by day. and also, the time of COVID-19 mobile application was very popular there was huge competition between the mobile application that available in a market. flutter can support both iOS and Android platform application. The main focused on the paper highlight the comparison between flutter mobile application and other native android mobile application. In this we can comparison on flutter SDK and android SDK on the basic of compilation, memory consumption, CPU usage, app size, etc.

Modeling the Nexus Between Perceived Value, Risk, Negative Marketing, and Consumer Trust with Consumers' Social Cross-Platform Buying Behaviour in India Using Smart-PLS

Purpose: The purpose of the study is to highlight the need for research on the relationship between consumer value, risk, and trust in the context of social cross-platform perceptions, specifically in India. The study aims to provide insights into how these factors influence consumers' cross-platform buying behavior, ultimately contributing to a better understanding of online shopping dynamics and informing strategies for building trust and enhancing consumer experiences in the online shopping environment. Methodology: The research methodology involved conducting a survey among 320 online shoppers in India. The objective was to investigate the relationship between social cross-platform perceptions of consumer value, risk, and trust in the context of online shopping. The researchers developed a questionnaire to collect data on perceived value, risk propensity, trust, and cross-platform buying behavior. Partial least squares (PLS) path modeling were used to analyze the data, revealing significant effects of perceived value, risk propensity, and trust on consumers' cross-platform buying behavior. Finding: This research focuses on the rise of social cross-platform buying behaviour in India and examines the influence of perceived risk, perceived value, trust, and marked negative reporting on consumer behaviour. The study found that consumers' perceptions of perceived risk and perceived value significantly impact their likelihood of using social e-commerce platforms like Meesho. Perceived risk refers to the level of uncertainty or potential harm associated with a purchase, while perceived value refers to the benefits or worth a consumer perceives from a product or service. Marked negative reporting refers to negative reviews or news articles that can impact a consumer's trust in a platform. Managerial implication: The study's managerial implications highlight the importance of reducing perceived risk, increasing perceived value, and building trust to improve social e-commerce marketing strategies. Organizations should be cautious of negative reporting and its impact on consumer behavior. Researchers can gain insights into consumer behavior and the significance of trust and perceived risk in driving purchase decisions in the context of social e-commerce marketing. To encourage cross-platform purchases, companies should address negative reports from other platforms, establish trust with consumers, and find ways to minimize perceived risk associated with social media purchases. Value: A significant contribution to the body of knowledge is achieved through testing and subsequent confirmation of the effects of online purchasing in the study model. This research enhances our understanding of the factors influencing online purchasing in the context of social cross-platform interactions. By investigating the relationship between Risk, Trust and various constructs within the social cross-platform framework, this study provides valuable insights into the dynamics of consumer behavior in the digital era.

“Customer Reviews or Vlogger Reviews?” The Impact of Cross-Platform UGC on the Sales of Experiential Products on E-Commerce Platforms

User-generated content (UGC) from e-commerce platforms and third-party platforms can impact customer-perceived risk and influence product sales in online stores. However, the understanding of UGC from which platform type yields a stronger effect on product sales and how the effects interact across the platforms remains limited. This limitation arises from the complexity of consumer purchasing behavior and information processing, as well as the heterogeneity of UGC features across different platforms and the uncertainty surrounding causal relationships. This study constructs a novel cross-platform framework using the elaboration likelihood model (ELM) to investigate the underlying mechanism of how cross-platform UGC affects online sales of experiential products. Additionally, it examines the mediating effect of purchase intention in the relationship between cross-platform UGC and product sales, as well as the moderating effect of product price. Taking the e-commerce platform Tmall and third-party platform Bilibili as a cross-platform example, we analyzed customer reviews on Tmall and vlogger reviews on Bilibili for 300 cosmetic products, using text sentiment analysis and multiple regression. Results show that the number of product evaluations from third-party platforms positively impacts sales, but this impact is weaker compared to the influence of UGC originating from e-commerce platforms on sales. The underlying mechanism refers to the process by which UGC on an e-commerce platform directly impacts sales and also influences sales through purchase intention. In contrast, UGC on third-party platforms only influences sales through purchase intention. Furthermore, the product price has no significant moderating effect on the positive relationship between review length and sales. This study provides a cross-platform UGC research framework that can guide effective cross-platform marketing management by shedding light on the role of UGC in reducing customer-perceived risk and its impact on online sales of experiential products.

A Comprehensive Analysis and Strategy Development for Maximizing Code Reusability in Cross-Platform Development Frameworks

This examination offers an in-depth exploration of code reusability for cross-platform improvement. With the growing desire for software program solutions to be well matched throughout numerous systems, cross-platform improvement has gained great prominence. But the balance between maximizing code reusability and catering to platform-specific customization requirements remains a difficult problem. This study on the whole aims to assess the volume of code reuse across unique cross-platform development frameworks, examine the effect of platform-specific customization on code reusability, and suggest techniques to beautify code reuse in this context. A combined-method technique was employed, combining quantitative data analysis of several open-supply initiatives with qualitative records collected through expert interviews. An examination of popular cross-platform frameworks, which include Flutter, React Native, Xamarin, and Ionic, discovered the inherent differences affecting code reusability. Furthermore, an empirical study was carried out to determine the impact of platform-specific customization on code reuse. The findings indicate a sizable variance in code reusability across different frameworks, and the necessity for platform-specific customization certainly impacts code reusability. But this research additionally provides a group of powerful techniques, such as the use of layout styles, element-primarily based improvement, abstracting platform-specific code, utilization of go-platform libraries, code refactoring, computerized testing, and continuous integration/non-stop deployment, to maximize code reusability. This observation provides essential insights for developers, researchers, and choice-makers within the discipline of mobile platform improvement. Future studies can build upon these findings to further delve into this critical component of software improvement

Comparative Analysis of Cross-Platform Frameworks

The use of frameworks for cross-platform development, whether native or hybrid, is a fundamental part of the field of programming, facilitating in one way or another to software developers to save time, reduce compilation errors, and optimize resources, among other features that denote some advantage between one tool and another. For this reason, it was decided to perform a comparative analysis between the cross-platform application development frameworks Flutter, React Native, Ionic, and Xamarin, using relevant features of each tool as parameters. For this purpose, research was conducted through a literature review of research articles, theses, and books obtained using the Google Scholar search engine, and consequently, parameters were determined that allowed comparing the mentioned frameworks. As a case study, a simple web page was developed in the Flutter framework with the help of the Visual Studio Code environment, to experiment with the characteristics of the mentioned framework directly and briefly. It is concluded that the frameworks for multiplatform development are useful tools that optimize time and maintenance by not requiring writing code to create a computer application on different platforms, benefiting developers and companies focused on software development.

Combining Experience Sampling and Mobile Sensing for Digital Phenotyping With m-Path Sense: Performance Study.

The experience sampling methodology (ESM) has long been considered as the gold standard for gathering data in everyday life. In contrast, current smartphone technology enables us to acquire data that are much richer, more continuous, and unobtrusive than is possible via ESM. Although data obtained from smartphones, known as mobile sensing, can provide useful information, its stand-alone usefulness is limited when not combined with other sources of information such as data from ESM studies. Currently, there are few mobile apps available that allow researchers to combine the simultaneous collection of ESM and mobile sensing data. Furthermore, such apps focus mostly on passive data collection with only limited functionality for ESM data collection. In this paper, we presented and evaluated the performance of m-Path Sense, a novel, full-fledged, and secure ESM platform with background mobile sensing capabilities. To create an app with both ESM and mobile sensing capabilities, we combined m-Path, a versatile and user-friendly platform for ESM, with the Copenhagen Research Platform Mobile Sensing framework, a reactive cross-platform framework for digital phenotyping. We also developed an R package, named mpathsenser, which extracts raw data to an SQLite database and allows the user to link and inspect data from both sources. We conducted a 3-week pilot study in which we delivered ESM questionnaires while collecting mobile sensing data to evaluate the app's sampling reliability and perceived user experience. As m-Path is already widely used, the ease of use of the ESM system was not investigated. Data from m-Path Sense were submitted by 104 participants, totaling 69.51 GB (430.43 GB after decompression) or approximately 37.50 files or 31.10 MB per participant per day. After binning accelerometer and gyroscope data to 1 value per second using summary statistics, the entire SQLite database contained 84,299,462 observations and was 18.30 GB in size. The reliability of sampling frequency in the pilot study was satisfactory for most sensors, based on the absolute number of collected observations. However, the relative coverage rate-the ratio between the actual and expected number of measurements-was below its target value. This could mostly be ascribed to gaps in the data caused by the operating system pushing away apps running in the background, which is a well-known issue in mobile sensing. Finally, some participants reported mild battery drain, which was not considered problematic for the assessed participants' perceived user experience. To better study behavior in everyday life, we developed m-Path Sense, a fusion of both m-Path for ESM and Copenhagen Research Platform Mobile Sensing. Although reliable passive data collection with mobile phones remains challenging, it is a promising approach toward digital phenotyping when combined with ESM.

DroMOD: A Drone-Based Multi-Scope Object Detection System

Drone-based Multi-scope Object Detection (DroMOD) system targets an efficient detection of different kinds of objects using drones. DroMOD relies on a cross-platform framework where objects’ detection tasks are shared between the drone and the server. The drone stores a set of reference images about the supervised zone. Each time an image is captured with a well-defined spatial frequency, it is compared to its reference image and only ‘trigger images’ showing a change from the reference image are sent to the server. A Big Data streaming platform is deployed on server-side for scalable and efficient real-time object detection processing based on Deep Learning (DL) models. DroMOD system architecture allows for dynamically upgrading the DL models so that newly considered objects to detect can be added to the drone mission on the fly without modifying the drone embedded software. When compared to existing alternatives, DroMOD presents the best compromise between (i) object detection accuracy, (ii) real-time processing and (iii) resource efficiency. Since only lightweight processing is performed on the drone-side, memory and computation are highly optimised on drones. Furthermore, the drone-side image filtering is independent of the objects to detect and the object detection programs are deployed and updated only on the server-side which allows for multi-target detection with minimal engineering efforts and expertise.

ExGen: Cross-platform, Automated Exploit Generation for Smart Contract Vulnerabilities

Smart contracts, just like other computer programs, are prone to a variety of vulnerabilities, which lead to severe consequences including massive token and coin losses. Prior works have explored automated exploit generation for vulnerable Ethereum contracts. However, the scopes of prior works are limited in both vulnerability types and contract platforms. In this paper, we propose a cross-platform framework, called <sc xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">ExGen</small> , to generate multiple transactions as exploits to given vulnerable smart contracts. <sc xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">ExGen</small> first translates either Ethereum or EOS contracts to an intermediate representation (IR). Then, <sc xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">ExGen</small> generates symbolic attack contracts with transactions in a partial order and then symbolically executes the attack contracts together with the target to find and solve all the constraints. Lastly, <sc xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">ExGen</small> concretizes all the symbols, generates attack contracts with multiple transactions, and verifies the generated contracts’ exploitability on a private chain with values crawled from the public chain. We implemented a prototype of <sc xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">ExGen</small> and evaluated it on Ethereum and EOS benchmarks. <sc xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">ExGen</small> successfully exploits 1,258/1,399 (89.9%) Ethereum and 126/130 (96.9%) EOS vulnerabilities. <sc xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">ExGen</small> is also able to exploit zero-day vulnerabilities on EOS.

Comparison of the cross-platform mobile applications performance in 2D graphics processing

The article presents a comparison of cross-platform frameworks in 2D graphics processing. The tests consisted in applying filters to 2D images, and then the image processing time and standard deviation were measured. The test will be conducted on the Huawei P8 and Samsung A50 phones. The comparison concerns two very popular cross-platform programming frameworks: Flutter and Xamarin.

Cross-device Cross-Platform Framework: Analyzing User Behavior and Tracking Methods

This study explores the dynamic shifts in the digital landscape and the evolution of user journeys. Additionally, it investigates the impactful role of crossdevice and cross-platform transitions in elevating the user experience. A crucial aspect addressed in this paper is the identification of tracking methods for each transition, emphasizing their pivotal role in optimizing and enhancing the overall user journey

Cross-platform virtual reality for real-time construction safety training using immersive web and industry foundation classes

Virtual reality (VR) has been studied extensively in the construction industry, particularly for safety training, as it is capable of simulating the hazardous areas of a construction site in a virtual environment that enables workers to visualize the real scenario before being introduced to job sites. However, at present, VR safety training requires specialized hardware and software, thus limiting worker access as only a few workers can participate in each training session. Therefore, this paper proposes a cross-platform framework based on Industry Foundation Classes (IFC) and WebXR (Immersive Web) for conveniently accessible VR safety training (CPVR) in the construction industry. Workers can access VR safety training sessions using their mobile device or desktop with the aid of the recommended framework. Furthermore, they can interact and communicate with other participants in real-time. A prototype based on the CPVR framework was developed, and its practicality and effectiveness for safety training were validated by senior students, managers, site engineers, and workers in the construction field. The proposed framework would help improve employees, particularly the worker, accessibility to VR safety training, which enables them to receive training at any time and from any location to enhance their awareness and knowledge. Furthermore, it could generate collaboration among employees and help assist managers in assessing employees' safety knowledge.

Cyberbullying Detection across Social Media Platforms via Platform-Aware Adversarial Encoding

Despite the increasing interest in cyberbullying detection, existing efforts have largely been limited to experiments on a single platform and their generalisability across different social media platforms has received less attention. We propose XP-CB, a novel cross-platform framework based on Transformers and adversarial learning. XP-CB can enhance a Transformer leveraging unlabelled data from the source and target platforms to come up with a common representation while preventing platform-specific training. To validate our proposed framework, we experiment on cyberbullying datasets from three different platforms through six cross-platform configurations, showing its effectiveness with both BERT and RoBERTa as the underlying Transformer models.

FRONT-END APPLICATION FOR MULTIPLE STOREFRONTS ECOMMERCE USING CROSS-PLATFORM TECHNOLOGY

Cross-platform framework is becoming more and more popular. Many giant tech companies have their own offering with different programming languages. With so many choices, sometimes it is difficult for a start-up developer to choose which framework they will use for their project. Therefore, this research aims to give insight for start-up developers on which cross-platform framework is better between Flutter and React Native by comparing their performance. This research achieved its goal by creating two identical mobile applications using Flutter and React Native and then comparing their performance using a theoretical framework that measures load time, average frame rate, and memory usage. The result of this testing is that Flutter has a shorter load time at 1.69 second compared to React Native at 4.26 second and lower memory usage at 6.52MB compared to React Native at 27.6MB. Their average frame rate is very comparable hovering around 60 frames per second. With faster load time and lower memory usage Flutter has better performance wise compared to React Native.