Automated code development based on genetic programming in graphical programming language: A pilot study.

Continual technological advances associated with the recent automation revolution have tremendously increased the impact of computer technology in the industry. Software development and testing are time-consuming processes, and the current market faces a lack of specialized experts. Introducing auto...

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Main Authors: Pavel Kodytek, Alexandra Bodzas, Jan Zidek
Format: Article
Language:English
Published: Public Library of Science (PLoS) 2024-01-01
Series:PLoS ONE
Online Access:https://journals.plos.org/plosone/article/file?id=10.1371/journal.pone.0299456&type=printable
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author Pavel Kodytek
Alexandra Bodzas
Jan Zidek
author_facet Pavel Kodytek
Alexandra Bodzas
Jan Zidek
author_sort Pavel Kodytek
collection DOAJ
description Continual technological advances associated with the recent automation revolution have tremendously increased the impact of computer technology in the industry. Software development and testing are time-consuming processes, and the current market faces a lack of specialized experts. Introducing automation to this field could, therefore, improve software engineers' common workflow and decrease the time to market. Even though many code-generating algorithms have been proposed in textual-based programming languages, to the best of the authors' knowledge, none of the studies deals with the implementation of such algorithms in graphical programming environments, especially LabVIEW. Due to this fact, the main goal of this study is to conduct a proof-of-concept for a requirement-based automated code-developing system within the graphical programming environment LabVIEW. The proposed framework was evaluated on four basic benchmark problems, encompassing a string model, a numeric model, a boolean model and a mixed-type problem model, which covers fundamental programming scenarios. In all tested cases, the algorithm demonstrated an ability to create satisfying functional and errorless solutions that met all user-defined requirements. Even though the generated programs were burdened with redundant objects and were much more complex compared to programmer-developed codes, this fact has no effect on the code's execution speed or accuracy. Based on the achieved results, we can conclude that this pilot study not only proved the feasibility and viability of the proposed concept, but also showed promising results in solving linear and binary programming tasks. Furthermore, the results revealed that with further research, this poorly explored field could become a powerful tool not only for application developers but also for non-programmers and low-skilled users.
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spelling doaj.art-81ef9a6b807d4d1198115407d98a99032024-03-13T05:31:20ZengPublic Library of Science (PLoS)PLoS ONE1932-62032024-01-01193e029945610.1371/journal.pone.0299456Automated code development based on genetic programming in graphical programming language: A pilot study.Pavel KodytekAlexandra BodzasJan ZidekContinual technological advances associated with the recent automation revolution have tremendously increased the impact of computer technology in the industry. Software development and testing are time-consuming processes, and the current market faces a lack of specialized experts. Introducing automation to this field could, therefore, improve software engineers' common workflow and decrease the time to market. Even though many code-generating algorithms have been proposed in textual-based programming languages, to the best of the authors' knowledge, none of the studies deals with the implementation of such algorithms in graphical programming environments, especially LabVIEW. Due to this fact, the main goal of this study is to conduct a proof-of-concept for a requirement-based automated code-developing system within the graphical programming environment LabVIEW. The proposed framework was evaluated on four basic benchmark problems, encompassing a string model, a numeric model, a boolean model and a mixed-type problem model, which covers fundamental programming scenarios. In all tested cases, the algorithm demonstrated an ability to create satisfying functional and errorless solutions that met all user-defined requirements. Even though the generated programs were burdened with redundant objects and were much more complex compared to programmer-developed codes, this fact has no effect on the code's execution speed or accuracy. Based on the achieved results, we can conclude that this pilot study not only proved the feasibility and viability of the proposed concept, but also showed promising results in solving linear and binary programming tasks. Furthermore, the results revealed that with further research, this poorly explored field could become a powerful tool not only for application developers but also for non-programmers and low-skilled users.https://journals.plos.org/plosone/article/file?id=10.1371/journal.pone.0299456&type=printable
spellingShingle Pavel Kodytek
Alexandra Bodzas
Jan Zidek
Automated code development based on genetic programming in graphical programming language: A pilot study.
PLoS ONE
title Automated code development based on genetic programming in graphical programming language: A pilot study.
title_full Automated code development based on genetic programming in graphical programming language: A pilot study.
title_fullStr Automated code development based on genetic programming in graphical programming language: A pilot study.
title_full_unstemmed Automated code development based on genetic programming in graphical programming language: A pilot study.
title_short Automated code development based on genetic programming in graphical programming language: A pilot study.
title_sort automated code development based on genetic programming in graphical programming language a pilot study
url https://journals.plos.org/plosone/article/file?id=10.1371/journal.pone.0299456&type=printable
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