Single Code Base Research Articles

Comparative Analysis of Hybrid Mobile App Development Frameworks

With the rise of mobile devices and their usage, a lot of development has been made in terms of the development of applications for mobile devices. Traditionally, app development was restricted to the particular operating system, and a separate codebase was required for applications to be developed for multiple operating systems. A new paradigm of development took place in recent years which was of Hybrid app development, leading to the development of multiple frameworks which allowed for a single codebase to be used for multiple operating systems. This paper explores the features and analysis of different hybrid app development frameworks available in the market. A comprehensive analysis has been made to compare the different frameworks which are cross-platform and support web, Android, and iOS platforms. The analysis shows that all the frameworks have their merits and usage of anyone framework over others can vary from case-to-case basis. The detailed analysis of the features will bring a general conclusion over the choice of framework.

Student Services App

Cross-platform mobile application development is the pressing priority in today’s world and generation. Developers are enforced to either construct the same application numerous times for various OS (operating systems) or accept a low-quality similar solution that trades native speed and accuracy for portability. Flutter is an open-source SDK for developing high-performance and more reliable mobile applications for operating systems like iOS, Android and even windows [1]. Flutter is Google’s UI toolkit for building beautiful, natively compiled applications for mobile, web, and desktop from a single codebase. Student Service App is an automation which will provide duplicate degree, duplicate marksheet, migration, transcript, provisional degree and document verification services to all registered the Universities. It will provide University services related to academics to its registered students via mobile devices on their finger tips for which they have to be present physically at respective places. It has Service oriented architecture so that it will be integrated to the existing ERP (Web Portal) of the different universities.

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.

K-Athena: A Performance Portable Structured Grid Finite Volume Magnetohydrodynamics Code

Large scale simulations are a key pillar of modern research and require ever-increasing computational resources. Different novel manycore architectures have emerged in recent years on the way towards the exascale era. Performance portability is required to prevent repeated non-trivial refactoring of a code for different architectures. We combine ATHENA++, an existing magnetohydrodynamics (MHD) CPU code, with KOKKOS, a performance portable on-node parallel programming paradigm, into K-ATHENA to allow efficient simulations on multiple architectures using a single codebase. We present profiling and scaling results for different platforms including Intel Skylake CPUs, Intel Xeon Phis, and NVIDIA GPUs. K-ATHENA achieves > 10 <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">8</sup> cell-updates/s on a single V100 GPU for second-order double precision MHD calculations, and a speedup of 30 on up to 24 576 GPUs on Summit (compared to 172,032 CPU cores), reaching 1:94 × 10 <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">12</sup> total cell-updates/s at 76 percent parallel efficiency. Using a roofline analysis we demonstrate that the overall performance is currently limited by DRAM bandwidth and calculate a performance portability metric of 62.8 percent. Finally, we present the implementation strategies used and the challenges encountered in maximizing performance. This will provide other research groups with a straightforward approach to prepare their own codes for the exascale era. K-ATHENA is available at https://gitlab.com/pgrete/kathena.

Mobile cross-platform app development tools

This article discusses the existing popular tools for mobile cross-platform application development. It is contrasted with the so – called native application development-when applications are created using the tools provided by the development companies of the respective platforms. Google provides a tool like Android Studio for its Android mobile operating system. The main programming languages used to create applications for this platform are Java and Kotlin. Apple, in turn, offers developers such an integrated development environment as XCode, in which development is carried out using the Swift programming language. The authors reviewed some of the most popular tools for cross-platform development, such as React Native, Xamarin and Flutter. React Native is a product developed by the company Facebook. It inherits the main technological aspects from another framework from Facebook-React. Programming here is conducted in the JavaScript language. React Native is suitable for web developers who have worked with React before and now want to try their hand at developing mobile applications. Xamarin is a framework supported by Microsoft. It provides tools for creating cross-platform applications for the iOS and Android mobile operating systems. This framework is bundled with Microsoft Visual Studio as a downloadable component. What is typical for a Microsoft product, here the C# programming language is used for development. This is a significant advantage of the Xamarin framework: during the creation of a mobile application, developers can use all the important and convenient features of this programming language. Flutter is a tool developed by Google to create apps for Android and iOS using a single code base. Unlike other popular solutions, Flutter is not a framework: it is a set of software development tools that contains everything you need to create cross-platform applications. It includes a visualization engine, ready-made widgets, and tools for working with the command line. The main programming language here is Dart. In the course of studying these tools, the authors made the following conclusions: tools for cross-platform development are an excellent solution if you need to create an application that does not require high performance: displaying information received from the server, simple local information processors, such as applications for social networks, online stores, organizer applications. These tools are not suitable for creating applications that require computing resources.

SpikeInterface, a unified framework for spike sorting.

Much development has been directed toward improving the performance and automation of spike sorting. This continuous development, while essential, has contributed to an over-saturation of new, incompatible tools that hinders rigorous benchmarking and complicates reproducible analysis. To address these limitations, we developed SpikeInterface, a Python framework designed to unify preexisting spike sorting technologies into a single codebase and to facilitate straightforward comparison and adoption of different approaches. With a few lines of code, researchers can reproducibly run, compare, and benchmark most modern spike sorting algorithms; pre-process, post-process, and visualize extracellular datasets; validate, curate, and export sorting outputs; and more. In this paper, we provide an overview of SpikeInterface and, with applications to real and simulated datasets, demonstrate how it can be utilized to reduce the burden of manual curation and to more comprehensively benchmark automated spike sorters.

PlanetCARMA: A New Framework for Studying the Microphysics of Planetary Atmospheres

The Community Aerosol and Radiation Model for Atmospheres (CARMA) has been updated to apply to atmospheres of the Solar System outside of Earth. CARMA, as its name suggests, is a coupled aerosol microphysics and radiative transfer model and includes the processes of nucleation, condensation, evaporation, coagulation, and vertical transport. Previous model versions have been applied separately to the atmospheres of Solar System bodies and extrasolar planets. The primary advantage to PlanetCARMA is that the core physics routines each reside in their own self-contained modules and can be turned on/off as desired while a separate planet module supplies all the necessary parameters to apply the model run to a particular planet (or planetary body). So a single codebase is used for all planetary studies. PlanetCARMA has also been updated to Fortran 90 modular format. Examples of outer solar system atmosphere applications are shown.

Data-driven optimization model customization

When embedded in software-based decision support systems, optimization models can greatly improve organizational planning. In many industries, there are classical models that capture the fundamentals of general planning decisions (e.g., designing a delivery route). However, these models are generic and often require customization to truly reflect the realities of specific operational settings. Yet, such customization can be an expensive and time-consuming process. At the same time, popular cloud computing software platforms such as Software as a Service (SaaS) are not amenable to customized software applications. We present a framework that has the potential to autonomously customize optimization models by learning mathematical representations of customer-specific business rules from historical data derived from model solutions and implemented plans. Because of the wide-spread use in practice of mixed integer linear programs (MILP) and the power of MILP solvers, the framework is designed for MILP models. It uses a common mathematical representation for different optimization models and business rules, which it encodes in a standard data structure. As a result, a software provider employing this framework can develop and maintain a single code-base while meeting the needs of different customers. We assess the effectiveness of this framework on multiple classical MILPs used in the planning of logistics and supply chain operations and with different business rules that must be observed by implementable plans. Computational experiments based on synthetic data indicate that solutions to the customized optimization models produced by the framework are regularly of high-quality.

Heterogeneous computing with OpenMP and Hydra

SummaryHigh‐performance computing relies on accelerators (such as GPGPUs) to achieve fast execution of scientific applications. Traditionally, these accelerators have been programmed with specialized languages, such as CUDA or OpenCL. In recent years, OpenMP emerged as a promising alternative for supporting accelerators, providing advantages such as maintaining a single code base for the host and different accelerator types and providing a simple way to extend support for accelerators to existing application codes. Efficiently using this support requires solving several challenges, related to performance, work partitioning, and concurrent execution on multiple device types. In this article, we discuss our experiences with using OpenMP for accelerators and present performance guidelines. We also introduce a library, Hydra, that addresses several of the challenges of using OpenMP for such devices. We apply Hydra to a scientific application, PlasCom2, that has not previously been able to use accelerators. Experiments on three architectures show that Hydra results in performance gains of up to 10× compared with CPU‐only execution. Concurrent execution on the host and GPU resulted in additional gains of up to 20% compared to running on the GPU only.

Implementing a Language for Distributed Systems: Choices and Experiences with Type Level and Macro Programming in Scala

Multitier programming languages reduce the complexity of developing distributed systems by developing the distributed system in a single coherent code base. The compiler or the runtime separate the code for the components of the distributed system, enabling abstraction over low level implementation details such as data representation, serialization and network protocols. Our ScalaLoci language allows developers to declare the different components and their architectural relation at the type level, allowing static reasoning about about distribution and remote communication and guaranteeing static type safety across components. The compiler splits the multitier program into the component-specific code and automatically generates the communication boilerplate. Communication between components can be modeled by declaratively specifying data flows between components using reactive programming. In this paper, we report on the implementation of our design and our experience with embedding our language features into Scala as a host language. We show how a combination of Scala's advanced type level programming and its macro system can be used to enrich the language with new abstractions. We comment on the challenges we encountered and the solutions we developed for our current implementation and outline suggestions for an improved macro system to support the such use cases of embedding of domain-specific abstractions.

HashFight: A Platform-Portable Hash Table for Multi-Core and Many-Core Architectures

We introduce a new platform-portable hash table and collision-resolution approach, HashFight, for use in visualization and data analysis algorithms. Designed entirely in terms of dataparallel primitives (DPPs), HashFight is atomics-free and consists of a single code base that can be invoked across a diverse range of architectures. To evaluate its hashing performance, we compare the single-node insert and query throughput of Hash- Fight to that of two best-in-class GPU and CPU hash table implementations, using several experimental configurations and factors. Overall, HashFight maintains competitive performance across both modern and older generation GPU and CPU devices, which differ in computational and memory abilities. In particular, HashFight achieves stable performance across all hash table sizes, and has leading query throughput for the largest sets of queries, while remaining within a factor of 1.5X of the comparator GPU implementation on all smaller query sets. Moreover, HashFight performs better than the comparator CPU implementation across all configurations. Our findings reveal that our platform-agnostic implementation can perform as well as optimized, platform-specific implementations, which demonstrates the portable performance of our DPP-based design.

React Native for Android: Cross-Platform Mobile Application Development

React Native has been embraced by many companies, and some of the most well-known applications in the world, including Facebook, Uber, and Pinterest, are among those that have done so. Why is it so widespread? What does it mean to react natively? It will likely attribute a significant portion of its success to the company's ability to utilize a single codebase compatible with several platforms. The use of React Native is continually gaining more widespread support. While developing mobile applications, using React Native can have positive and negative effects, and this article will help us grasp both aspects. This study will provide all the necessary information before we use React Native in one of our applications. With this knowledge, we can determine if react native is the appropriate choice for our next project.

CyBy2: a strongly typed, purely functional framework for chemical data management

We present the development of CyBy2, a versatile framework for chemical data management written in purely functional style in Scala, a modern multi-paradigm programming language. Together with the core libraries we provide a fully functional example implementation of a HTTP server together with a single page web client with powerful querying and visualization capabilities, providing essential functionality for people working in the field of organic and medicinal chemistry. The main focus of CyBy2 are the diverse needs of different research groups in the field and therefore the flexibility required from the underlying data model. Techniques for writing type level specifications giving strong guarantees about the correctness of the implementation are described, together with the resulting gain in confidence during refactoring. Finally we talk about the advantages of using a single code base from which the server, the client and the software’s documentation pages are being generated. We conclude with a comparison with existing open source solutions. All code described in this article is published under version 3 of the GNU General Public License and available from GitHub including an example implementation of both backend and frontend together with documentation how to download and compile the software (available at https://github.com/stefan-hoeck/cyby2).

The CHIMAERA system for retrievals of cloud top, optical and microphysical properties from imaging sensors

Continuity and consistency of geophysical retrieval products obtained from different Earth-observing spaceborne or airborne atmospheric multispectral imagers can be challenging due to inherent differences in the instruments and/or the use of different retrieval algorithms. The Cross-platform HIgh resolution Multi-instrument AtmosphEric Retrieval Algorithms (CHIMAERA) system addresses the latter aspect of the inter-sensor continuity problem for cloud property retrievals by removing retrieval methodology and implementation as a source of inconsistency when applied to instruments that share common measurement capabilities.Transferring an existing retrieval algorithm to a new sensor oftentimes is a nontrivial task, as it is common for an algorithm code to be tightly coupled to the sensor for which it was developed. By creating a clear division between the science algorithm and the instrument I/O codes, CHIMAERA allows easy migration of science algorithms to different sensors. CHIMAERA is built from C and FORTRAN source code, and can operate in a variety of environments ranging from a personal laptop to a high-performance computing environment for near real-time satellite data production. It is highly adaptable, low-maintenance and allows for easy expansion such that adding new instruments into the system requires only instrument-specific I/O and provision of any external lookup tables specific to the instrument's spectral characteristics.CHIMAERA currently supports 14 spaceborne and airborne atmospheric imagers from a single code base, and has been in use since 2007. In this paper we describe the engineering aspects of CHIMAERA and briefly discuss a few examples from its many current applications.

Comparative Analysis of Two BI Tools: Micro Strategy and Tableau

The need for enterprise business intelligence initiatives has skyrocketed due to the potential to empower businesses to make better data driven decisions. Better insights are being needed by business users into core business problems as they need access to these insights faster than ever before. Many BI vendors have provided feasible options to buyer looking to implement BI solution. It is difficult for a business person to reach any one decision when given a variety of options.BI previously had merely reporting capabilities, BI solutions have progressively acquired drastic functionality, like data mining, improved analytics tools, and online analytical processing (OLAP) services, with various company mergers and acquisitions, and the BI field has evolved to more complex and heavy BI solutions.Two widely used BI-tools for reporting and providing business insights are MicroStrategy and Tableau. MicroStrategy is well known for its software which is based on single code base, it is suitable for applications of all sizes; grips hardware, operating system, and data source infrastructure while making BI more accessible for business users. Tableau supports ad hoc analysis for the day to day user, it facilitates the business users to better visualize and understand their data. Also, for easy consumption, it allows to display the KPIs easily on a centralized analytics platform.

Code generator framework for smart TV platforms

In recent years, smart TVs have become more common, making them need to be included as targets for the software industry. In this study, the authors developed a code generator framework and demonstrated it in an architectural view. The proposed framework converts C# programming language based projects, in a Windows Forms or a Windows Phone Application project, into native smart TV Platform applications. The selected primary smart TV platforms assigned for application conversion were Android TV, Firefox OS, and Tizen OS. The authors enabled developers to generate native codes for all three platforms from a single code base using model to model conversion, as in the model driven architecture approach with the use of the open source Roslyn C# language compiler. The need for creating projects for every single platform to make them run on different platforms will thus be eliminated and development cycles shortened. By doing so, the time required to develop an application for each platform is reduced while keeping the generated applications’ quality as high as the original application. To show the functionality, the proposed approach is applied in three case studies. The success of the code conversion is satisfactory and converted applications are functional.

ESSENCE Features for 2019

ObjectiveThe objective of this presentation is to discuss the new features that are under development for ESSENCE in 2019. This is a chance to describe the features, the use cases for the features, and open a dialogue with the community on potential new enhancements that are available.IntroductionThe ESSENCE system is a community-driven disease surveillance system. Installed in over 25 jurisdictions across the US, the system is built on a single codebase that is shared across all instances. While each individual location can customize many of the settings, data sources, and configurations, the underlying code and functionality is shared. This means that when one jurisdiction works with the Johns Hopkins University Applied Physics Laboratory (JHU/APL) to create a new feature, it is available to all sites.MethodsThe roadmap for ESSENCE in 2019 is based upon ongoing and future projects between jurisdictions and JHU/APL. While specifics can change before features are deployed, the following list of new features have exceptional capabilities. These include:Social Elements to the User Experience: Ability for users to share what they are doing within ESSENCE with their peers. Ability for users to see what others are querying and find interesting. Support sharing both within a system and across jurisdictions.Text Analysis: Text analysis and visualizations to help support the user in building new free-text queries.Provide correlation, trend, and association analytics for words and phrases to help the user determine what should or should not be included in their queries.Site Monitoring: Back-end tools and checks to better monitor an ESSENCE system for issues and data irregularities. This administrative tool will help the system maintain its day-to-day availability and improve visibility of errors and issues that may develop over time.Longitudinal Surveillance: Visualizations and cohort clustering analytics to determine the types of patients who are using the healthcare systems that provide data to ESSENCE. These tools can show patient uses over time with trends to better inform utilization of healthcare resources in a community.Opioid Overdose Surveillance: Visualizations and analytics to better support the surveillance activities related to the opioid overdose crisis. Work with additional data sources (EMS, Poison Control, Death Records, etc.) to determine the benefit of fusing multiple pieces of information into a common picture for improved opioid surveillance.And other new features…ResultsThe presentation will describe the current roadmap, demonstrate features that are mature enough in the software development process, share mock-ups for features still in the early stages of development and provide use cases for each of the new features discussed.ConclusionsNo organization can build a successful system without the participation and buy-in from its stakeholder community. ESSENCE is an excellent example of a tool built on collective input whose ongoing enhancements benefit all its users. By seeing the roadmap and understanding the new features for 2019, the community can prepare for upcoming enhancements and begin discussions about other needs and use cases that will drive the development of the next round of ESSENCE features.

An Argument Against Cross-Platform Development: Lessons From an Augmented Reality App Prototype for Rural Emergency Responders.

BackgroundMobile augmented reality (MAR) apps offer potential support for emergency responders in rural areas.ObjectiveIn this report, we described lessons learned from the development process of augmented reality (AR) Farm Mapping to Assist, Protect and Prepare Emergency Responders (MAPPER), a MAR app that provides emergency responders onsite information about the agricultural operation they enter.MethodsCross-platform frameworks were used to create AR MAPPER to accommodate budget constraints and overcome issues with markerless MAR technologies. Although the single codebase and Web technologies streamlined development, cross-device hardware limitations impacted location accuracy, lengthened the development cycle, and required regular updates to third-party libraries.ResultsA hybrid development approach of using Web-based technologies with native tie-ins for specialized components and enhanced performance cut time and costs. This also led to consistency across multiple platforms and ensured that there is only a single set of source files to modify for Android and iPhone operating systems. Meanwhile, active development was delayed by some major hurdles. Apple and Google both released new versions of their operating systems, and the Wikitude framework issued four major updates, each of which brought with it some important enhancements and also led to some new issues.ConclusionsDevelopers should consider single platform native development to benefit from platform-specific MAR implementations and to avoid development, testing, and maintenance costs associated with cross-platform implementation. Emergency response organizations may be more likely to utilize a single platform across the devices used by their command staff. This also reduces the benefits of cross-platform development. Furthermore, providing map-based, non-AR cross-platform apps for landowners, farmers, and ranchers would help improve and maintain data quality, which is crucial for the utility and user experience of MAR apps.

A new cross-platform architecture for epi-info software suite

BackgroundThe Epi-Info software suite, built and maintained by the Centers for Disease Control and Prevention (CDC), is widely used by epidemiologists and public health researchers to collect and analyze public health data, especially in the event of outbreaks such as Ebola and Zika. As it exists today, Epi-Info Desktop runs only on the Windows platform, and the larger Epi-Info Suite of products consists of separate codebases for several different devices and use-cases. Software portability has become increasingly important over the past few years as it offers a number of obvious benefits. These include reduced development time, reduced cost, and simplified system architecture. Thus, there is a blatant need for continued research. Specifically, it is critical to fully understand any underlying negative performance issues which arise from platform-agnostic systems. Such understanding should allow for improved design, and thus result in substantial mitigation of reduced performance. In this paper, we present a viable cross-platform architecture for Epi-Info which solves many of these problems.ResultsWe have successfully generated executables for Linux, Mac, and Windows from a single code-base, and we have shown that performance need not be completely sacrificed when building a cross-platform application. This has been accomplished by using Electron as a wrapper for an AngularJS app, a Python analytics module, and a local, browser-based NoSQL database.ConclusionsPromising results warrant future research. Specifically, the design allows for cross-platform form-design, data-collection, offline/online modes, scalable storage, automatic local-to-remote data sync, and fast analytics which rival more traditional approaches.

Demonstrating GPU code portability and scalability for radiative heat transfer computations

High performance computing frameworks utilizing CPUs, Nvidia GPUs, and/or Intel Xeon Phis necessitate portable and scalable solutions for application developers. Nvidia GPUs in particular present numerous portability challenges with a different programming model, additional memory hierarchies, and partitioned execution units among streaming multiprocessors. This work presents modifications to the Uintah asynchronous many-task runtime and the Kokkos portability library to enable one single codebase for complex multiphysics applications to run across different architectures. Scalability and performance results are shown on multiple architectures for a globally coupled radiation heat transfer simulation, ranging from a single node to 16,384 Titan compute nodes.