The Dataset of the Experimental Evaluation of Software Components for Application Design Selection Directed by the Artificial Bee Colony Algorithm
The paper presents the swarm intelligence approach to the selection of a set of software components based on computational experiments simulating the desired operating conditions of the software system being developed. A mathematical model is constructed, aimed at the effective selection of componen...
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| Format: | Article |
| Language: | English |
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MDPI AG
2020-07-01
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| Series: | Data |
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| Online Access: | https://www.mdpi.com/2306-5729/5/3/59 |
| _version_ | 1797562995129188352 |
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| author | Alexander Gusev Dmitry Ilin Evgeny Nikulchev |
| author_facet | Alexander Gusev Dmitry Ilin Evgeny Nikulchev |
| author_sort | Alexander Gusev |
| collection | DOAJ |
| description | The paper presents the swarm intelligence approach to the selection of a set of software components based on computational experiments simulating the desired operating conditions of the software system being developed. A mathematical model is constructed, aimed at the effective selection of components from the available alternative options using the artificial bee colony algorithm. The model and process of component selection are introduced and applied to the case of selecting Node.js components for the development of a digital platform. The aim of the development of the platform is to facilitate countrywide simultaneous online psychological surveys in schools in the conditions of unstable internet connection and the large variety of desktop and mobile client devices, running different operating systems and browsers. The module whose development is considered in the paper should provide functionality for the archiving and checksum verification of the survey forms and graphical data. With the swarm intelligence approach proposed in the paper, the effective set of components was identified through a directional search based on fuzzy assessment of the three experimental quality indicators. To simulate the desired operating conditions and to guarantee the reproducibility of the experiments, the virtual infrastructure was configured. The application of swarm intelligence led to reproducible results for component selection after 312 experiments instead of the 1080 experiments needed by the exhaustive search algorithm. The suggested approach can be widely used for the effective selection of software components for distributed systems operating in the given conditions at this stage of their development. |
| first_indexed | 2024-03-10T18:36:17Z |
| format | Article |
| id | doaj.art-1fffe3b61d1f4b1ba1ee57b20f2d222f |
| institution | Directory Open Access Journal |
| issn | 2306-5729 |
| language | English |
| last_indexed | 2024-03-10T18:36:17Z |
| publishDate | 2020-07-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Data |
| spelling | doaj.art-1fffe3b61d1f4b1ba1ee57b20f2d222f2023-11-20T06:11:49ZengMDPI AGData2306-57292020-07-01535910.3390/data5030059The Dataset of the Experimental Evaluation of Software Components for Application Design Selection Directed by the Artificial Bee Colony AlgorithmAlexander Gusev0Dmitry Ilin1Evgeny Nikulchev2Russian Academy of Education, Data-Center, 119121 Moscow, RussiaMIREA—Russian Technological University, Institute of Integrated Safety, Security and Special Instrumentation, 119454 Moscow, RussiaMIREA—Russian Technological University, Institute of Integrated Safety, Security and Special Instrumentation, 119454 Moscow, RussiaThe paper presents the swarm intelligence approach to the selection of a set of software components based on computational experiments simulating the desired operating conditions of the software system being developed. A mathematical model is constructed, aimed at the effective selection of components from the available alternative options using the artificial bee colony algorithm. The model and process of component selection are introduced and applied to the case of selecting Node.js components for the development of a digital platform. The aim of the development of the platform is to facilitate countrywide simultaneous online psychological surveys in schools in the conditions of unstable internet connection and the large variety of desktop and mobile client devices, running different operating systems and browsers. The module whose development is considered in the paper should provide functionality for the archiving and checksum verification of the survey forms and graphical data. With the swarm intelligence approach proposed in the paper, the effective set of components was identified through a directional search based on fuzzy assessment of the three experimental quality indicators. To simulate the desired operating conditions and to guarantee the reproducibility of the experiments, the virtual infrastructure was configured. The application of swarm intelligence led to reproducible results for component selection after 312 experiments instead of the 1080 experiments needed by the exhaustive search algorithm. The suggested approach can be widely used for the effective selection of software components for distributed systems operating in the given conditions at this stage of their development.https://www.mdpi.com/2306-5729/5/3/59swarm intelligencequality of systems and programsNode.jssoftware system developmentdigital platformsevolutionary computation |
| spellingShingle | Alexander Gusev Dmitry Ilin Evgeny Nikulchev The Dataset of the Experimental Evaluation of Software Components for Application Design Selection Directed by the Artificial Bee Colony Algorithm Data swarm intelligence quality of systems and programs Node.js software system development digital platforms evolutionary computation |
| title | The Dataset of the Experimental Evaluation of Software Components for Application Design Selection Directed by the Artificial Bee Colony Algorithm |
| title_full | The Dataset of the Experimental Evaluation of Software Components for Application Design Selection Directed by the Artificial Bee Colony Algorithm |
| title_fullStr | The Dataset of the Experimental Evaluation of Software Components for Application Design Selection Directed by the Artificial Bee Colony Algorithm |
| title_full_unstemmed | The Dataset of the Experimental Evaluation of Software Components for Application Design Selection Directed by the Artificial Bee Colony Algorithm |
| title_short | The Dataset of the Experimental Evaluation of Software Components for Application Design Selection Directed by the Artificial Bee Colony Algorithm |
| title_sort | dataset of the experimental evaluation of software components for application design selection directed by the artificial bee colony algorithm |
| topic | swarm intelligence quality of systems and programs Node.js software system development digital platforms evolutionary computation |
| url | https://www.mdpi.com/2306-5729/5/3/59 |
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