Empirical evaluation of automated code generation for mobile applications by AI tools

Santiago Aillon; Alejandro Garcia; Nicolas Velandia; Daniel Zarate; Pedro Wightman

doi:10.1109/C358072.2023.10436306

Empirical evaluation of automated code generation for mobile applications by AI tools

Santiago Aillon
, Alejandro Garcia
, Nicolas Velandia
, Daniel Zarate
, Pedro Wightman

Producción científica: Capítulo en Libro/Informe › Contribución a la conferencia

5 Citas (Scopus)

Resumen

The rapid advancement of AI technologies has opened up new possibilities for automating various aspects of software development. Mobile app development, in particular, can benefit from AI-powered tools that assist developers in writing code more efficiently, providing suggestions, and reducing the time required for implementation. This document aims to explore how well a modern artificial intelligence tool can assist a mobile application development process. For this work, ChatGPT 3.5 was used to generate a mobile application from scratch using the Flutter framework, while the complete process was evaluated at each step. The evaluation criteria for the experience considered four indicators: code quality, solution quality, response time, and comparison with human-generated code. Results show that, up to a certain level of complexity and by using an interactive process of increasingly detailed prompts, the AI tool is capable of generating functional code, that can be the base for the inclusion of a more complex logic or structure.

Idioma original	Inglés estadounidense
Título de la publicación alojada	1st IEEE Colombian Caribbean Conference, C3 2023
Editores	Paul Sanmartin Mendoza, Andres Navarro
Editorial	Institute of Electrical and Electronics Engineers Inc.
ISBN (versión digital)	9798350341799
DOI	https://doi.org/10.1109/C358072.2023.10436306
Estado	Publicada - 2023
Evento	1st IEEE Colombian Caribbean Conference, C3 2023 - Barranquilla, Colombia Duración: nov 22 2023 → nov 25 2023

Serie de la publicación

Nombre	1st IEEE Colombian Caribbean Conference, C3 2023

Conferencia

Conferencia	1st IEEE Colombian Caribbean Conference, C3 2023
País/Territorio	Colombia
Ciudad	Barranquilla
Período	11/22/23 → 11/25/23

ODS de las Naciones Unidas

Este resultado contribuye a los siguientes Objetivos de Desarrollo Sostenible

ODS 1: Fin de la pobreza

Áreas temáticas de ASJC Scopus

Inteligencia artificial
Redes de ordenadores y comunicaciones
Ingeniería eléctrica y electrónica
Ingeniería mecánica
Control y optimización
Modelización y simulación
Instrumental

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10.1109/C358072.2023.10436306

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Aillon, S., Garcia, A., Velandia, N., Zarate, D., & Wightman, P. (2023). Empirical evaluation of automated code generation for mobile applications by AI tools. En P. S. Mendoza, & A. Navarro (Eds.), 1st IEEE Colombian Caribbean Conference, C3 2023 (1st IEEE Colombian Caribbean Conference, C3 2023). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/C358072.2023.10436306

@inproceedings{9382af79988f46a6883eca2255b8574a,

title = "Empirical evaluation of automated code generation for mobile applications by AI tools",

abstract = "The rapid advancement of AI technologies has opened up new possibilities for automating various aspects of software development. Mobile app development, in particular, can benefit from AI-powered tools that assist developers in writing code more efficiently, providing suggestions, and reducing the time required for implementation. This document aims to explore how well a modern artificial intelligence tool can assist a mobile application development process. For this work, ChatGPT 3.5 was used to generate a mobile application from scratch using the Flutter framework, while the complete process was evaluated at each step. The evaluation criteria for the experience considered four indicators: code quality, solution quality, response time, and comparison with human-generated code. Results show that, up to a certain level of complexity and by using an interactive process of increasingly detailed prompts, the AI tool is capable of generating functional code, that can be the base for the inclusion of a more complex logic or structure.",

author = "Santiago Aillon and Alejandro Garcia and Nicolas Velandia and Daniel Zarate and Pedro Wightman",

note = "Publisher Copyright: {\textcopyright} 2023 IEEE.; 1st IEEE Colombian Caribbean Conference, C3 2023 ; Conference date: 22-11-2023 Through 25-11-2023",

year = "2023",

doi = "10.1109/C358072.2023.10436306",

language = "English (US)",

series = "1st IEEE Colombian Caribbean Conference, C3 2023",

publisher = "Institute of Electrical and Electronics Engineers Inc.",

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Aillon, S, Garcia, A, Velandia, N, Zarate, D & Wightman, P 2023, Empirical evaluation of automated code generation for mobile applications by AI tools. En PS Mendoza & A Navarro (eds.), 1st IEEE Colombian Caribbean Conference, C3 2023. 1st IEEE Colombian Caribbean Conference, C3 2023, Institute of Electrical and Electronics Engineers Inc., 1st IEEE Colombian Caribbean Conference, C3 2023, Barranquilla, Colombia, 11/22/23. https://doi.org/10.1109/C358072.2023.10436306

Empirical evaluation of automated code generation for mobile applications by AI tools. / Aillon, Santiago; Garcia, Alejandro; Velandia, Nicolas et al.
1st IEEE Colombian Caribbean Conference, C3 2023. ed. / Paul Sanmartin Mendoza; Andres Navarro. Institute of Electrical and Electronics Engineers Inc., 2023. (1st IEEE Colombian Caribbean Conference, C3 2023).

Producción científica: Capítulo en Libro/Informe › Contribución a la conferencia

TY - GEN

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AU - Garcia, Alejandro

AU - Velandia, Nicolas

AU - Zarate, Daniel

AU - Wightman, Pedro

PY - 2023

Y1 - 2023

N2 - The rapid advancement of AI technologies has opened up new possibilities for automating various aspects of software development. Mobile app development, in particular, can benefit from AI-powered tools that assist developers in writing code more efficiently, providing suggestions, and reducing the time required for implementation. This document aims to explore how well a modern artificial intelligence tool can assist a mobile application development process. For this work, ChatGPT 3.5 was used to generate a mobile application from scratch using the Flutter framework, while the complete process was evaluated at each step. The evaluation criteria for the experience considered four indicators: code quality, solution quality, response time, and comparison with human-generated code. Results show that, up to a certain level of complexity and by using an interactive process of increasingly detailed prompts, the AI tool is capable of generating functional code, that can be the base for the inclusion of a more complex logic or structure.

AB - The rapid advancement of AI technologies has opened up new possibilities for automating various aspects of software development. Mobile app development, in particular, can benefit from AI-powered tools that assist developers in writing code more efficiently, providing suggestions, and reducing the time required for implementation. This document aims to explore how well a modern artificial intelligence tool can assist a mobile application development process. For this work, ChatGPT 3.5 was used to generate a mobile application from scratch using the Flutter framework, while the complete process was evaluated at each step. The evaluation criteria for the experience considered four indicators: code quality, solution quality, response time, and comparison with human-generated code. Results show that, up to a certain level of complexity and by using an interactive process of increasingly detailed prompts, the AI tool is capable of generating functional code, that can be the base for the inclusion of a more complex logic or structure.

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M3 - Conference contribution

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Aillon S, Garcia A, Velandia N, Zarate D, Wightman P. Empirical evaluation of automated code generation for mobile applications by AI tools. En Mendoza PS, Navarro A, editores, 1st IEEE Colombian Caribbean Conference, C3 2023. Institute of Electrical and Electronics Engineers Inc. 2023. (1st IEEE Colombian Caribbean Conference, C3 2023). doi: 10.1109/C358072.2023.10436306

Empirical evaluation of automated code generation for mobile applications by AI tools

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Áreas temáticas de ASJC Scopus

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