scholarly journals Comparative analysis of Kotlin and Java languages used to create applications for the Android system

2019 ◽  
Vol 13 ◽  
pp. 354-358
Author(s):  
Daniel Sulowski ◽  
Grzegorz Kozieł
Keyword(s):  
Comparative Analysis ◽  
Programming Languages ◽  
Mobile Applications ◽  
Community Support ◽  
Code Structure ◽  
Android System ◽  
Execution Times

This publication presents the results of a comparative analysis of Java and Kotlin programming languages used to create mobile applications for system Android. The analysis covers performance aspects such as CPU load, RAM load, as well as the compilation and execution times. Aspects such as code structure, availability of libraries, supported databases, popularity and community support were taken under consolidation.

scholarly journals A multi-criteria comparison of mobile applications built with the use of Android and Flutter Software Development Kits

2021 ◽  
Vol 19 ◽  
pp. 107-113
Author(s):  
Damian Gałan ◽  
Konrad Fisz ◽  
Piotr Kopniak
Keyword(s):  
Comparative Analysis ◽  
Software Development ◽  
Mobile Applications ◽  
Execution Time ◽  
Mobile Application ◽  
Source Code ◽  
Community Support ◽  
Cpu Usage

This publication presents a multi-criteria comparison of two mobile applications built with the use of Android and Flutter SDK. The former has been implemented with Kotlin and the latter with Dart. The benchmarking process examines factors such as execution time and CPU usage during data and disk operations. During the analysis, attention was paid to the length and volume the source code, community support and the availability of libraries. The comparative analysis shows that a mobile application written using Android SDK is often not only faster and more efficient, but also has greater community support and the number of libraries available. In addition, an analysis of the source code volume showed that Flutter has more concise but more difficult to navigate code than Android.

scholarly journals Comparison of mobile application using Swift and Objective-C

2017 ◽  
Vol 3 ◽  
pp. 54-58
Author(s):  
Kacper Erwin Sienkiewicz ◽  
Edyta Łukasik
Keyword(s):  
Comparative Analysis ◽  
Programming Languages ◽  
Mobile Applications ◽  
Mobile Application ◽  
Functional Applications ◽  
The Subject ◽  
Drawing Board ◽  
Similarities And Differences

The subject of the article is to compare the methodologies for the production of mobile applications in Swift and Objective-C languages. The similarities and differences of the implementation of applications for these two programming languages will be identified as a part of the analysis. An Magic Drawing Board application using Quartz 2D engine was designed and implemented. Two identical functional applications were created. The comparative analysis was carried out only after a thorough explanation of the implemented views.

scholarly journals SECURITY MECHANISMS AND ANALYSIS FOR INSECURE DATA STORAGE AND UNINTENDED DATA LEAKAGE FOR MOBILE APPLICATIONS

2016 ◽  
Vol 15 (8) ◽  
pp. 7008-7020
Author(s):  
Vanessa M. Santana ◽  
Paolina Centonze
Keyword(s):  
Comparative Analysis ◽  
Programming Languages ◽  
Data Storage ◽  
Programming Language ◽  
Mobile Applications ◽  
Mobile Application ◽  
Academic Research ◽  
Point Of View ◽  
Attack Surface ◽  
The Many

Using one mobile programming language like Objective-C, Swift or Java is challenging enough because of the many things that need to be considered from a security point of view, like the programming language secure guidelines and vulnerabilities. With the introduction of Swift in 2014 it’s now possible to build Swift/Objective-C mobile applications. Building a mobile application using two languages also adds a greater attack surface for hackers because of the need for developers to stay up to date on vulnerabilities on more than one language and operating system.To our best knowledge, since as of today, there is no academic-research based effort comparing Swift, Objective-C and Android from a programming language and platform security point of view. Our comparative analysis covers a subset of OWASP top ten mobile vulnerabilities and seeing how Swift, Objective-C and Android programming languages safeguard against these risks and how the built-in platform security mechanisms for Android and Apple for the chosen subset of OWASP vulnerabilities compare when placed side-by-side.

scholarly journals An Evaluation Framework and Comparative Analysis of the Widely Used First Programming Languages

PLoS ONE ◽  
2014 ◽  
Vol 9 (2) ◽  
pp. e88941 ◽  
Author(s):  
Muhammad Shoaib Farooq ◽  
Sher Afzal Khan ◽  
Farooq Ahmad ◽  
Saeed Islam ◽  
Adnan Abid
Keyword(s):  
Comparative Analysis ◽  
Programming Languages ◽  
Evaluation Framework

scholarly journals Comparative analysis of mobile applications by development method

2019 ◽  
Vol 53 (2) ◽  
Author(s):  
S.V. Chubeiko ◽  
R.I. Cherkasov ◽  
Yu.A. Timakina
Keyword(s):  
Comparative Analysis ◽  
Mobile Applications ◽  
Development Method

Comparative Analysis of Efficient Platforms

2015 ◽  
pp. 342-361
Author(s):  
Khawaja Tehseen Ahmed ◽  
Mazhar Ul-Haq ◽  
Arsalaan Ahmed Shaikh ◽  
Raihan ur Rasool
Keyword(s):  
Comparative Analysis ◽  
Programming Languages ◽  
Daily Lives ◽  
Real Time Processing ◽  
Time Processing ◽  
Large Numbers ◽  
Hybrid Platform ◽  
Paper Format ◽  
Technical Solutions ◽  
Different Levels

With the advancement of technology we are heading towards a paperless environment. But there are still a large numbers of documents that exist in paper format in our daily lives. Thus the need to digitize these paper documents, archive them and view them at all times has arisen. The number of documents of a small organization may be in thousands, millions or even more. This chapter presents comparative analysis of different programming languages and libraries where it is intended to parallel process a huge stream of images which undergo unpredictable arrival of the images and variation in time. Since the parallelism can be implemented at different levels, different algorithms and techniques have also been discussed. It also presents the state of the art and discussion of various existing technical solutions to implement the parallelization on a hybrid platform for the real time processing of the images contained in a stream. Experimental results obtained using Apache Hadoop in combination with OpenMP have also been discussed.

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