Cross-platform Framework Research Articles

Review on Detail Information About Flutter Cross Platform

Abstract: Now a days The Rapid growth of wireless technology and Mobile devices in this era is creating a great impact on our lives. Due to which many things going digitalized with time. Hence to reduce the manual work we are doing work through application. For Making application now the developer use cross platform framework. Flutter is a popular UI framework for developing mobile applications by Google. This library consists of various reusable UI(User Interface) elements, such as sliders, buttons, and text inputs. Developers building mobile applications with the Flutter framework will do so using a programming language called Dart. Keywords: Cross Platform Mobile Application, IDE, IOS, Flutter, Dart, Firebase.

Smartphone-based plant leaf area meter

A portable device is described for measuring an important plant trait – plant leaf area. The principle of operation of the device is based on digital processing of the obtained images by the method of technical vision. It is implemented on the basis of a free cross-platform framework for game development and visualization – the LibGDX software project. An algorithm and a program for the automated determination of the leaf area are presented. The device is autonomous and is based on a smartphone and a gadget for it. The results of his research tests are presented. The purpose of the device is to study the influence of the environment on ecological systems in the field.

Tren dan Peluang Cross-Platform Mobile App untuk Developer Pemula

The development of cross-platform based mobile applications has grown rapidly in the last five years. From a developer's point of view, the many technologies that must be studied make them confused about which programming language to master because it will correlate with the time required and technology adoption by the industrial world. From an industry point of view, the challenge faced is determining the right framework or programming language and tools for their application. It also correlates with development time and costs, as well as finding the best talent with the technology. The purpose of this paper is to provide insight, trends and perspectives to new programmers who want to start a career and industry related to technology used in cross-platform mobile applications by looking at the results of surveys conducted by Stackoverflow, SateOfJS and Ionic Framework for the past 5 years. So this will help new programmers and industry in choosing the right technology and framework. The author found that currently JavaScript has mastered the frontend, backend and test tools. Regarding cross-platform frameworks, we find the Ionic Framework, React Native to be the most widely used.

EvoCluster: An Open-Source Nature-Inspired Optimization Clustering Framework

EvoCluster is an open source and cross-platform framework implemented in Python language, which includes the most well-known and recent nature-inspired metaheuristic optimizers that are customized to perform partitional clustering tasks. This paper is an extension to the existing EvoCluster framework in which it includes different distance measures for the objective function, different techniques of detecting the k value, and a user option to consider either supervised or unsupervised datasets. The current implementation of the framework includes ten metaheuristic optimizers, thirty datasets, five objective functions, twelve evaluation measures, more than twenty distance measures, and ten different ways for detecting the k value. The source code of EvoCluster is publicly available at http://evo-ml.com/evocluster/ .

Cross-Platform Mobile App Development in Industry: A Multiple Case-Study

Cross-platform frameworks for mobile application development are pervasive and allow developers to build applications that can operate on a spectrum of mobile platforms. With the high availability of such frameworks, it is imperative to give better understanding about the perception of industry and the challenges they face in this field. Although there are several studies in this field of research, only few research works investigate cross-platform mobile development in the industrial contexts in-depth. We conducted a qualitative research using multiple case-study approach. Interviews and focus groups methods were applied to gather information from four different software development companies in Palestine. This study aims at understanding industrial teams approach to mobile cross-platform development. In particular, it seeks to identify the challenges they face in the areas of code maintenance and software testing. Our findings cover the important aspects in industrial contexts, including the development process, as well as, how and why the cross-platform development approach is chosen. From the practitioners’ perspectives, we argue that the developers’ experience is the most influential factor in the development process. Further, our study investigates the different cross-platform technologies in the industry, and the dominant one from the practitioners’ perspectives, where they agreed that the React-Native is the promising and dominant technology. From the challenges perspective, we found that the APIs provided by the vendors are not easy to operate by developers and considered to be a major challenge. Finally, this research investigates how testing and maintenance methodologies are applied along with their challenges.

Cross-Platform Analysis and Development of Online Catering Platform (Kunyahku)

Kunyahku is an online catering platform that provides catalogs of menus from local caterer near the user and become the distributor that will take the order and deliver them. In developing an application, the most important aspect for small start-up companies is to have a development stack that can deliver the app into multiple platform by using a single code base to reduce the cost of developers, improve efficiency and reduce the time to develop the application itself. To provide the necessity of building an application for Kunyahku, this paper is aimed to find the most suitable cross platform framework for developing the Kunyahku application. This research focuses on comparison between existing popular cross-platform and proving the suitable one to be used in development cycle in the case of Kunyahku requirements. Sets of test and comparison were conducted in order to compare the most suitable cross platform between React Native and Flutter such as render test and comparing each advantage coming out from using each of the cross-platform.After all the requirements are gathered and then the most suitable framework will be chosen which is Flutter. Performance analysis and the benefits of using Flutter framework are elaborated and thus proving it is the most suitable development stack to be used in Kunyahku case and the development time can be reduced since it is a cross-platform technology that output the application into three different platform rather than managing separate platform for each different one. Testing shows that flutter also met all the requirements thus proving flutter address the problems of scalability and faster development compared to developing each native platform one by one.

A Comparison of Native and Cross-Platform Frameworks for Mobile Applications

The methods used for developing applications for mobile devices have become an important field of research. In this article, we analyze the two most popular approaches, native and cross platform, and compare identical applications developed using various tools.

THE CONSTRUCTION METHODS FOR SOFTWARE COMPLEXES BY THE EXAMPLE OF OPEN CROSS-PLATFORM ONLINE SYSTEM FOR TEXT TRANSLATION

Popular online translators Google Translate, Bing Translator, DeepL Translator, and Apertium are reviewed. The goal is to compare the interfaces and functionality of these translators. The advantages of using the C ++ programming language are investigated. The choice of the Qt cross-platform framework among other analogues has been substantiated. Qt most of all meets the requirements set in the article for the development of its own software product. The basis for the development of the program is chosen methods of object-oriented programming using the application programming interface. The stages of development of the online «Crow Translate» system are presented. Its capabilities for text translation are described: an application programming interface for translation, peculiarities of the implementation of a C ++ programming system based on the Qt framework, basic commands of the console interface, functionality of the graphical interface for dubbing and translation, customization options, localization possibilities and ways of distributing the offered «Crow Translate» software. During the development of the system, the implementation of the translation process and the program interface were divided into two separate projects. A peculiarity of the project implementation is the development of a separate QOnlineTranslator library for text translation. This system is free software and is published on the GitHub page under the GPL v3 license for use in any similar projects. The details of the implementation of the suggested library and its main functions are described. Thanks to the use of the Google interface in the described program, a high-quality translation is ensured. The developed project provides for the ability to work in the dictionary mode when entering one word or a piece of text. Various translation options are additionally displayed for one word. There is support for displaying transliteration. When developing a software product, the possibility of receiving a translation in a pop-up window without additional transitions to the browser or other applications was taken into account. The result is an open cross-platform software product that has convenient access to the translation of a text selected in any application and takes up a small amount of RAM.

Smartphone Naïve Bayes Human Activity Recognition Using Personalized Datasets

Recognizing human activity in real time with a limited dataset is possible on a resource-constrained device. However, most classification algorithms such as Support Vector Machines, C4.5, and K Nearest Neighbor require a large dataset to accurately predict human activities. In this paper, we present a novel real-time human activity recognition model based on Gaussian Naïve Bayes (GNB) algorithm using a personalized JavaScript object notation dataset extracted from the publicly available Physical Activity Monitoring for Aging People dataset and University of Southern California Human Activity dataset. With the proposed method, the personalized JSON training dataset is extracted and compressed into a 12×8 multi-dimensional array of the time-domain features extracted using a signal magnitude vector and tilt angles from tri-axial accelerometer sensor data. The algorithm is implemented on the Android platform using the Cordova cross-platform framework with HTML5 and JavaScript. Leave-one-activity-out cross validation is implemented as a testTrainer() function, the results of which are presented using a confusion matrix. The testTrainer() function leaves category K as the testing subset and the remaining K-1 as the training dataset to validate the proposed GNB algorithm. The proposed model is inexpensive in terms of memory and computational power owing to the use of a compressed small training dataset. Each K category was repeated five times and the algorithm consistently produced the same result for each test. The result of the simulation using the tilted angle features shows overall precision, recall, F-measure, and accuracy rates of 90%, 99.6%, 94.18%, and 89.51% respectively, in comparison to rates of 36.9%, 75%, 42%, and 36.9% when the signal magnitude vector features were used. The results of the simulations confirmed and proved that when using the tilt angle dataset, the GNB algorithm is superior to Support Vector Machines, C4.5, and K Nearest Neighbor algorithms.

An empirical investigation of performance overhead in cross-platform mobile development frameworks

The heterogeneity of the leading mobile platforms in terms of user interfaces, user experience, programming language, and ecosystem have made cross-platform development frameworks popular. These aid the creation of mobile applications – apps – that can be executed across the target platforms (typically Android and iOS) with minimal to no platform-specific code. Due to the cost- and time-saving possibilities introduced through adopting such a framework, researchers and practitioners alike have taken an interest in the underlying technologies. Examining the body of knowledge, we, nonetheless, frequently encounter discussions on the drawbacks of these frameworks, especially with regard to the performance of the apps they generate. Motivated by the ongoing discourse and a lack of empirical evidence, we scrutinised the essential piece of the cross-platform frameworks: the bridge enabling cross-platform code to communicate with the underlying operating system and device hardware APIs. The study we present in the article benchmarks and measures the performance of this bridge to reveal its associated overhead in Android apps. The development of the artifacts for this experiment was conducted using five cross-platform development frameworks to generate Android apps, in addition to a baseline native Android app implementation. Our results indicate that – for Android apps – the use of cross-platform frameworks for the development of mobile apps may lead to decreased performance compared to the native development approach. Nevertheless, certain cross-platform frameworks can perform equally well or even better than native on certain metrics which highlights the importance of well-defined technical requirements and specifications for deliberate selection of a cross-platform framework or overall development approach.

Fw‐fuzz: A code coverage‐guided fuzzing framework for network protocols on firmware

SummaryFuzzing is an effective approach to detect software vulnerabilities utilizing changeable generated inputs. However, fuzzing the network protocol on the firmware of IoT devices is limited by inefficiency of test case generation, cross‐architecture instrumentation, and fault detection. In this article, we propose the Fw‐fuzz, a coverage‐guided and crossplatform framework for fuzzing network services running in the context of firmware on embedded architectures, which can generate more valuable test cases by introspecting program runtime information and using a genetic algorithm model. Specifically, we propose novel dynamic instrumentation in Fw‐fuzz to collect the running state of the firmware program. Then Fw‐fuzz adopts a genetic algorithm model to guide the generation of inputs with high code coverage. We fully implement the prototype system of Fw‐fuzz and conduct evaluations on network service programs of various architectures in MIPS, ARM, and PPC. By comparing with the protocol fuzzers Boofuzz and Peach in metrics of edge coverage, our prototype system achieves an average growth of 33.7% and 38.4%, respectively. We further verify six known vulnerabilities and discover 5 0‐day vulnerabilities with the Fw‐fuzz, which prove the validity and utility of our framework. The overhead of our system expressed as an additional 5% of memory growth.

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English

A cross-platform modular framework for building Life Cycle Assessment

In recent years the application of Life Cycle Assessment (LCA) for assessing and improving the environmental performance of buildings has increased. At the same time, the automated optimization of building designs is gaining attraction for both design and research purposes. In this regard, a number of issues persist when aiming to optimize building’s environmental impacts along the design process. Firstly, as LCA applies a life cycle perspective, many aspects have to be considered (e.g. energy demand in operation as well as consumption of resources and energy for production and end of life treatment) and a variety of specific calculations is needed (e.g. building energy performance simulation, material quantity take-off). Secondly, sophisticated software packages are available and being used for each of these calculations (e.g. software for building modelling, dynamic energy simulation, quantity surveying). Though many of these software packages are currently standalone applications that rely on human interaction, there is an increasing trend to provide an application programming interface (API) that enables customization and automation. Thirdly, the mentioned processes and calculations are influencing each other in various ways and several scenarios have to be assessed. Thus, a comprehensive and modular approach is required that promotes interconnectivity of the different software solutions and automation of the assessment. In this paper we propose a modular cross-platform framework for LCA of buildings aiming to support flexibility and scalability of building LCA. We present a conceptual framework, example data exchange requirements and highlight potential implementation strategies.

A Systematic Mapping Study of Cross-Platform Mobile Apps

Cross-platform frameworks for mobile Application (app) development allow developers to deploy solutions on a range of platforms such as iOS and Android. With the increased use of such frameworks, it is of utmost importance to understand the contributions and challenges in this emergent field. Although there have been many studies in this area of research, there is a lack of a coherent view. To address this issue, we have conducted a Systematic Mapping Study (SMS) to categorize the available studies in the area of cross-platform mobile app development. More specifically, we aim to understand the accomplishments, contribution facets and the challenges presented in this field. Thirty (30) studies are mapped to a classification scheme. Different research gaps are identified: more research needs to be conducted using more complex and real-world apps; the point of how cross-platform apps are identified and distinguished from the native is still not clarified; and we argue that there should be more research contribution in the particular area of testing and maintenance.

Neural Interactome: Interactive Simulation of a Neuronal System.

Connectivity and biophysical processes determine the functionality of neuronal networks. We, therefore, developed a real-time framework, called Neural Interactome1,2, to simultaneously visualize and interact with the structure and dynamics of such networks. Neural Interactome is a cross-platform framework, which combines graph visualization with the simulation of neural dynamics, or experimentally recorded multi neural time series, to allow application of stimuli to neurons to examine network responses. In addition, Neural Interactome supports structural changes, such as disconnection of neurons from the network (ablation feature). Neural dynamics can be explored on a single neuron level (using a zoom feature), back in time (using a review feature), and recorded (using presets feature). The development of the Neural Interactome was guided by generic concepts to be applicable to neuronal networks with different neural connectivity and dynamics. We implement the framework using a model of the nervous system of Caenorhabditis elegans (C. elegans) nematode, a model organism with resolved connectome and neural dynamics. We show that Neural Interactome assists in studying neural response patterns associated with locomotion and other stimuli. In particular, we demonstrate how stimulation and ablation help in identifying neurons that shape particular dynamics. We examine scenarios that were experimentally studied, such as touch response circuit, and explore new scenarios that did not undergo elaborate experimental studies.

Investigation of the cross-platform Flutter framework. Will the heyday of this technology mean the disappearance of the native development on Android and iOS?

The work is devoted to research of the cross-platform framework for developing mobile applications Flutter from Google. A practical test of the technology was carried out to establish whether it is convenient enough and reliable. The article presents the findings of the testing. The comparison of the mechanisms of Flutter and other popular mobile cross-platform frameworks is given. The main features and differences of the technology are considered. Recommendations on its use are formulated.

Dynamic Analysis of Android Apps written with PhoneGap Cross-Platform Framework

In this paper, we propose an effective technique that can perform dynamic analysis for Android appwritten with PhoneGap cross-platform framework. For a systematic study, we have written a maliciousAndroid app using PhoneGap framework. We compare the structural differences between abasic Android app (a native app) and the other malicious Android app built in release mode on Phone-Gap framework, and also analyze the malicious app dynamically. The proposed technique first copiesthe web root directory of the target malicious app into a writable directory inside the smartphone.When the app is executed, its web pages and Javascript files are loaded from the copied directoryusing a dynamic instrumentation. Finally, we dynamically change the flag for WebView debuggingso that a remote debugger can successfully be attached to the app built in release mode. Using ourproposed technique, a malware analyst can debug a malicious PhoneGap app built in release modewithout repackaging, which cannot be debugged as it is by Chrome remote debugger. She/he canalso utilize the debugging features supported by the remote debugger. The technique allows the analystto bypass the repackaging detection method that malicious apps use to avoid antivirus detection.

NeuroMorphoVis: a collaborative framework for analysis and visualization of neuronal morphology skeletons reconstructed from microscopy stacks.

MotivationFrom image stacks to computational models, processing digital representations of neuronal morphologies is essential to neuroscientific research. Workflows involve various techniques and tools, leading in certain cases to convoluted and fragmented pipelines. The existence of an integrated, extensible and free framework for processing, analysis and visualization of those morphologies is a challenge that is still largely unfulfilled.ResultsWe present NeuroMorphoVis, an interactive, extensible and cross-platform framework for building, visualizing and analyzing digital reconstructions of neuronal morphology skeletons extracted from microscopy stacks. Our framework is capable of detecting and repairing tracing artifacts, allowing the generation of high fidelity surface meshes and high resolution volumetric models for simulation and in silico imaging studies. The applicability of NeuroMorphoVis is demonstrated with two case studies. The first simulates the construction of three-dimensional profiles of neuronal somata and the other highlights how the framework is leveraged to create volumetric models of neuronal circuits for simulating different types of in vitro imaging experiments.Availability and implementationThe source code and documentation are freely available on https://github.com/BlueBrain/NeuroMorphoVis under the GNU public license. The morphological analysis, visualization and surface meshing are implemented as an extensible Python API (Application Programming Interface) based on Blender, and the volume reconstruction and analysis code is written in C++ and parallelized using OpenMP. The framework features are accessible from a user-friendly GUI (Graphical User Interface) and a rich CLI (Command Line Interface).Supplementary information Supplementary data are available at Bioinformatics online.

UFlow: software for rational engineering of secondary flows in inertial microfluidic devices

Approaches to abstract and modularize models of fluid flow in microfluidic devices can enable predictive and rational engineering of microfluidic circuits with rapid designer feedback. The shape of co-flowing streams in the inertial flow regime has become of particular importance for new developments in high throughput microscale manufacturing, biological, and chemical research. In a process known as flow sculpting, the cross-sectional distribution of fluid elements is deformed due to the combined effects of diffusion and transverse advection, which are brought on by interaction with velocity gradients induced by sequences of pillar structures. However, the difficulty in solving the Navier–Stokes equations for complex flow-deforming geometries makes design in this space unintuitive, time-consuming, and costly. To mitigate these issues, we have efficiently embedded flow deformation operations previously relegated to high-performance computing into a free, user-friendly, and cross-platform framework called “uFlow”, to bring flow sculpting to the broader community. uFlow computes flow deformation including both advection and diffusion effects from a single pillar in 25 ms on modern consumer hardware, enabling real-time manual design and exploration of microfluidic devices, and fast visualization of 3D particles fabricated via stop flow lithography or optical transient liquid molding. Advanced numerical routines give instant access to a practically infinite set of flow transformations. We showcase uFlow’s design models, describe their implementation and usage, and validate the algorithms which allow real-time feedback with confocal imaging and cutting-edge microfluidic particle fabrication.

ECharts: A declarative framework for rapid construction of web-based visualization

While there have been a dozen of authoring systems and programming toolkits for visual design and development, users who do not have programming skills, such as data analysts or interface designers, still may feel cumbersome to efficiently implement a web-based visualization.In this paper, we present ECharts, an open-sourced, web-based, cross-platform framework that supports the rapid construction of interactive visualization. The motivation is driven by three goals: easy-to-use, rich built-in interactions, and high performance. The kernel of ECharts is a suite of declarative visual design language that customizes built-in chart types. The underlying streaming architecture, together with a high-performance graphics renderer based on HTML5 canvas, enables the high expandability and performance of ECharts. We report the design, implementation, and applications of ECharts with a diverse variety of examples. We compare the utility and performance of ECharts with C3.js, HighCharts, and Chart.js. Results of the experiments demonstrate the efficiency and scalability of our framework. Since the first release in June 2013, ECharts has iterated 63 versions, and attracted over 22,000 star counts and over 1700 related projects in the GitHub. ECharts is regarded as a leading visualization development tool in the world, and ranks the third in the GitHub visualization tab.