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¿Cómo influye = el uso de la inteligencia artificial en el desarrollo de software?<= /span>

 = ;

How does the use of artificial intelligence influence software development?

 


1

Diego Omar Guerra Poalasin

https://orcid.org/0000-00= 03-0408-8655

 

 

Universidad Técnica de Ambato, Ambato, Ecuador.

<= span style=3D'font-size:10.0pt;font-family:"Times New Roman",serif;mso-fareast= -font-family: "Times New Roman"'>dguerra6729@uta.edu.ec

2

Francisco Israel Ruales Flore= s                               https://orcid.org/0009-0= 001-9231-7229

Universidad Técnica de Ambato, Ambato, Ecuador.

<= span style=3D'font-size:10.0pt;font-family:"Times New Roman",serif;mso-fareast= -font-family: "Times New Roman"'>fruales3566@uta.edu.ec

 

 

 

 

 

 

 

 =

 

Artículo de Investigación Científica y Tecnológica<= /b>

Enviado: 13/07/2024

Revisado: 21/08/2024

Aceptado: 10/09/2024

Publicado:05/10/2024

DOI: https://doi.org/10.33262/ct.v3i4.53    <= /span>          

=  

 

 

Cítese:<= span lang=3DES-EC style=3D'font-size:12.0pt;line-height:115%;font-family:"Time= s New Roman",serif; mso-fareast-font-family:"Times New Roman";mso-font-kerning:0pt;mso-ligatu= res: none;mso-ansi-language:ES-EC;mso-fareast-language:ES'>

 

<= o:p> 

G= uerra Poalasin, D. O., & Ruales Flores, F. I. (= 2024). ¿Cómo influye el uso de la inteligencia artificial en el desarrollo de software?. Ciencia & Turismo, 3(4), 56-69. https://doi.org/10.33262/ct.v3= i4.53

 

 

<= /b>

 

 

CIENCIA & TURISMO, <= /span>es una revista multidisciplinaria, trimestral, que se publicará en soporte electrónico tiene como misión contribuir a la   formació= n de profesionales competentes con visión humanística y crítica que sean capac= es de exponer sus resultados investigativos y científicos en la misma medida= que se promueva mediante su intervención cambios positivos en la sociedad.&nb= sp;

La revista es editada por la Editorial Ciencia Digital (Editorial de prestigio registrada en la Cámara Ecuatoriana de Li= bro con No de Afiliación 663) www.celibro.org.ec

 

 

<= /b>

 

E= sta revista está protegida bajo una licencia Creative Co= mmons AttributionNonCommercialNoDerivatives 4.0 International. Copia de la licencia: http://creativecommons.org/licenses/by-nc-nd/4.0/<= /i>

 

Palabras claves:

I= nteligencia artificial, software, tecnología, desarrolladores, implementación

 

Resum= en

Introducción: Se presenta un panorama general sobre la integración de la IA en el desarrollo de software, destacando su creciente relevancia en tareas como la generación de código, pruebas automatizadas y mantenimiento. Asimismo, se examina su capacidad para transformar la industria tecnológica y fomentar la innovación. Objetivos: El estudio tiene como propósito identificar los principales aportes de la IA al desarrollo de software, evaluar su impact= o en la productividad y en las competencias de los desarrolladores, y explorar= las implicaciones económicas y sociales derivadas de su implementación. Metodología: Se utilizó un enfo= que cualitativo y cuantitativo, analizando estudios previos, encuestas a desarrolladores y datos sobre herramientas basadas en IA. Además, se investigaron casos de uso en empresas tecnológicas para comprender cómo se aplican estas herramientas en contextos reales. Resultados: Los hallazgos revelan que la IA mejora significativamente la eficiencia del desarrollo de software al automatizar tareas repetitivas, reducir errores y acelerar la entrega de productos. También fomenta el aprendizaje continuo y la colaboración humano-máquina, permitiendo a los desarrolladores enfocarse en tareas más complejas y creativas. Para las empresas, la IA representa una ventaja competitiva al reducir costos y democratizar el acceso al desarrollo tecnológico. Conclusiones: La IA está redefi= niendo el desarrollo de software, generando beneficios tangibles en términos de productividad, accesibilidad y crecimiento económico. Sin embargo, su implementación plantea desafíos éticos y técnicos que requieren una gesti= ón adecuada. Promover un uso equilibrado y responsable de estas herramientas será clave para maximizar su impacto positivo en el futuro de la industria tecnológica. Área de estudio general: Tecnología. Área de estudio específica: Desarrollo de softw= are. Tipo de estudio:  Artículo revisión bibliográfica

 

 

Keywords:

Artificial intelligence, software, technology, developers, implementation

 

Abstract

In= troduction: An overview of the integration of AI in software development is presented, highlighting its growing relevance in tasks such as code generation, automated testing, and maintenance. It also examines its ability to trans= form the technology industry and foster innovation. Objectives: The study aims to identify the main contributions= of AI to software development, assess its impact on developer productivity a= nd skills, and explore the economic and social implications of its implementation. Methodology:= A qualitative and quantitative approach was used, analyzing previous studie= s, developer surveys, and data on AI-based tools. In addition, use cases in technology companies were investigated to understand how these tools are applied in real-world contexts. = Results: The findings reveal that AI significantly improves the efficiency of soft= ware development by automating repetitive tasks, reducing errors, and accelera= ting product delivery. It also fosters continuous learning and human-machine collaboration, allowing developers to focus on more complex and creative tasks. For companies, AI represents a competitive advantage by reducing c= osts and democratising access to technological development. Conclusions: AI= is redefining software development, generating tangible benefits in terms of productivity, accessibility and economic growth. However, its implementat= ion poses ethical and technical challenges that require proper management. Promoting a balanced and responsible use of these tools will be key to maximising their positive impact on the future of t= he technology industry.

 <= /p>

 

 

 

 

<= span lang=3DES-EC style=3D'font-size:12.0pt;line-height:115%;font-family:"Times = New Roman",serif; mso-fareast-font-family:"Times New Roman";mso-ansi-language:ES-EC'>1.&n= bsp;    Introducción

= La inteligencia artificial (IA) ha emergido como una de las tecnologías más transformadoras de las últimas décadas, revolucionando múltiples sectores, incluido el desarrollo de software. Su implementación en este campo ha permitido optimizar procesos, mejorar la calidad de los productos y reducir significativamente los tiempos de desarrollo. Herramientas basadas en IA, c= omo los asistentes de codificación, los sistemas de prueba automatizados y los modelos predictivos, están redefiniendo la manera en que los desarrolladores diseñan, prueban y mantienen aplicaciones.

= Esta integración ha dado paso a una nueva era donde las tareas de programación, análisis de sistemas, y gestión de proyectos se optimizan mediante algoritm= os inteligentes, capaces de aprender, adaptarse y ejecutar tareas con una eficiencia sin precedentes. La IA no solo ha revolucionado la forma en que = se diseñan y desarrollan las aplicaciones, sino que también ha mejorado significativamente la experiencia de los desarrolladores y la eficiencia de= los procesos de desarrollo. (Huet, 2024)

= El nuevo acercamiento es construir sistemas que aprenden de sí mismos, convirtiéndose en expertos que modelan y abstraen reglas a partir de los da= tos que les son alimentados. Dichos sistemas van mejorando en su precisión, se adaptan a lo desconocido y expanden sus capacidades más allá de la programa= ción original. Las técnicas tradicionales de procesamiento de lenguaje natural (NLP), razonamiento basado en reglas y representación de conocimiento están siendo aumentadas con el machine learning —especialmente deep learni= ng— para mejorar la IA (ver figura 1). Los resultados preliminares son prometedores: estamos viendo surgir nuevas apps = con cierta “inteligencia” en una gran variedad de dominios.

= Esta ola de inteligencia artificial impactará el trabajo de los desarrolladores = de software, así que es importante estar preparados. Los desarrolladores deben entender en qué consisten dichas tecnologías y cómo pueden aplicarlas, tant= o en el ciclo de vida de desarrollo de software como en las aplicaciones mismas.= (Galván, 2023)

= El impacto laborar de la IA en la industria del desarrollo de software es un t= ema de gran relevancia y debate. Mientras la IA puede ofrecer herramientas poderosas que facilitan la entrada de programadores principiantes al campo, también plantea preguntas sobre la seguridad laboral a largo plazo para est= os mismos profesionales.

= Los profesionales se suelen adentrar en este mundo realizando tareas repetitiva= s y con bajo valor productivo por lo que puede llevar a una disminución de la demanda de profesionales con este tipo de rol.

= Es importante hacer ver a las empresas que dichos profesionales se convertirán= en un gran valor añadido pasado un tiempo ya que habrán adquirido los conocimientos necesarios tanto a nivel técnico como a nivel de producto sie= ndo muy difícil de reemplazar por una inteligencia artificial. (Rodríguez, 2024)

(Mármol, 2023) dice lo siguiente: “No cabe duda de que, en la actualidad, tener acceso a herramientas de inteligencia artificial es como tener un asistente que le pasas el trabajo y te lo genera en cuestión de segundos. Esto resulta especialmente útil para los desarrolladores que nece= sitan diseñar algoritmos que sean capaces de analizar grandes cantidades de información compleja y construir modelos que sean capaces de reaccionar a e= lla con tareas específicas”.

= Para (García, 2023), la IA es una herramienta que está favoreciendo otras tecnologías inteligentes, demostrando que en la actualidad la tendenc= ia es buscar la interacción entre todos los campos de la tecnología para desarrollar en conjunto una tecnología cada vez más sofisticada, inteligent= e e inclusiva.

= No obstante, el impacto de la inteligencia artificial en el desarrollo de soft= ware no está exento de desafíos. Aspectos como la dependencia tecnológica, la ét= ica en la toma de decisiones automatizadas y la necesidad de capacitar a los desarrolladores para interactuar con estas herramientas plantean nuevas interrogantes. Este artículo tiene como objetivo analizar cómo la inteligen= cia artificial influye en cada etapa del ciclo de vida del software, evaluando tanto sus beneficios como las barreras que enfrenta su adopción. A través d= e un enfoque integral, se busca explorar las implicaciones técnicas, económicas y sociales de esta tecnología en el futuro del desarrollo de software.

<= span lang=3DES-EC style=3D'font-size:12.0pt;line-height:115%;font-family:"Times = New Roman",serif; mso-fareast-font-family:"Times New Roman";mso-ansi-language:ES-EC'>2.&n= bsp;    Metodología

= Esta investigación tiene un enfoque mixto cualitativo y cuantitativo. Es cualita= tivo puesto se basó en fundamentación teórica y revisión bibliográfica. Lo cuantitativo se realizó a través de datos obtenidos en páginas especializad= as en estadísticas de uso de aplicaciones y redes sociales que han aportado al desarrollo del tema. Este trabajo cuenta con un nivel descriptivo, puesto s= e ha realizado en virtud de la doctrina y análisis emitido por autores que han tratado al respecto. Los métodos aplicados han sido el inductivo – deductiv= o, partiendo de ideas particulares hasta llegar a generales.

<= span lang=3DES-EC style=3D'font-size:12.0pt;line-height:115%;font-family:"Times = New Roman",serif; mso-fareast-font-family:"Times New Roman";mso-ansi-language:ES-EC'>3.&n= bsp;    Resultados

= La inteligencia artificial permite automatizar tareas repetitivas como las pru= ebas y la generación de código, optimizando el flujo de trabajo en el desarrollo= de software. A través de algoritmos de aprendizaje automático, es posible anal= izar grandes cantidades de datos históricos para detectar patrones, errores comu= nes y tendencias, facilitando que los desarrolladores se enfoquen en actividades más complejas y creativas. Por ejemplo, las herramientas de prueba automatizadas impulsadas por IA pueden crear casos de prueba de forma automática, ejecutarlos eficientemente y proporcionar resultados precisos, = lo que acelera el ciclo de desarrollo y mejora la calidad del producto final. Algunas de las herramientas que permiten lograr estos avances son: <= !--[if supportFields]>ADDIN CSL_CITATION {"citationItems":[{"id":"ITEM-1","itemDa= ta":{"author":[{"dropping-particle":"",&= quot;family":"Solvex Dominicana","given":"S R L","non-dropping-par= ticle":"","parse-names":false,"suffix":&= quot;"}],"container-title":"Linkedin.com","id= ":"ITEM-1","issued":{"date-parts":[[&quo= t;2024"]]},"note":"Accessed: 2024-12-11","title":"El Impacto de la Inteligencia Artificial en el Proceso de Desarrollo de Software","type":"article"},"uris":[&quo= t;http://www.mendeley.com/documents/?uuid=3D829e466b-9adc-49d9-89db-6de226d= 55fed"]}],"mendeley":{"formattedCitation":"(S= olvex Dominicana, 2024)","plainTextFormattedCitation":"(Solvex Dominicana, 2024)","previouslyFormattedCitation":"(Solv= ex Dominicana, 2024)"},"properties":{"noteIndex":0},&= quot;schema":"https://github.com/citation-style-language/schema/r= aw/master/csl-citation.json"}(Solvex Dominicana, 2024)

Tabla 1

Herramientas con inteligencia artificial

Herrami= enta

Descrip= ción

Selenium

 

Tabla 1

Herramientas con inteligencia artificial (continuación)

Herrami= enta

Descrip= ción

Testim

Mabl

Herrami= entas para la productividad

Visual Studi= o IntelliCode

TabNine

DeepCode

Herrami= entas de optimización

Jira Softwar= e

GitPrime (ahora parte de Pluralsigh= t Flow)

GitLab Auto DevOps

 

 

 

Tabla 1

Herramientas con inteligencia artificial (continuación)

Herrami= entas de detección y corrección de errores

AI Code Solver<= /span>

Code AI

Fuente: (Solvex Dominicana, 2024)

Tipos de Inteligencia Artificial en el desarrollo = de software

= La IA en el desarrollo se integra en varias etapas del ciclo de desarrollo de software, permitiendo a los desarrolladores construir aplicaciones más inteligentes y eficientes.

= Puedes encontrar oportunidades para utilizar estas tecnologías en tus proyectos de desarrollo de software. (Heinsohn, 2023)

= Aquí tienes algunos de los más comunes que puedes utilizar:

·      = Aprendizaje Automático (Machine Learning, ML): Los algoritmos de ML permiten que el software aprenda a partir de los datos y mejore su rendimiento con el tiempo.

·      = Procesamiento de Lenguaje Natural (Natural Language Processing, NLP): El NLP permite que el software comprenda y procese el lenguaje humano.

·      = Visión por Computadora (Compu= ter Vision): La visión por computador= a se centra en permitir que las máquinas vean e interpreten imágenes o videos.

·      = Sistemas Expertos (Expert Sys= tems): Los sistemas expertos utilizan técnicas basadas en conocimiento para imitar la habilidad humana en un dominio específico.

·      = Inteligencia de Negocios (Busi= ness Intelligence, BI): La inteligencia de negoc= ios implica el uso de técnicas de IA para analizar e interpretar grandes volúme= nes de datos y tomar decisiones empresariales informadas.

·      = Análisis Predictivo (Predictive Analytics): Utilizando algoritmos de IA y técnicas estadísticas, el análisis predictivo examina datos pasados y pronostica resultados futuros.

Beneficios de la IA para programar: programadores y empresas

= El uso de la inteligencia artificial ha transformado significativamente el desarrollo de software, brindando ventajas tanto a programadores individual= es como a empresas. Esta tecnología ha optimizado procesos, mejorado la eficie= ncia y facilitado la creación de soluciones más robustas y personalizadas. (Escoba= r, 2024)

Figura 1<= /o:p>

Beneficios de la IA para programar

Fuente: (Escoba= r, 2024)

= Según una investigación realizada por GitHub y Keystone.AI, se determinó que los desarrolladores aceptaron el 30% de las sugerencias de código, lo que les permitió completar tareas un 55% más rápido. (Bejarano, 2024)

Más Productividad =3D Más impulso económico

= El incremento en la productividad impulsado por el desarrollo de la inteligenc= ia artificial podría añadir más de $1.5 billones al PIB global. Con un aumento proyectado del 30% en la productividad y un estimado de 45 millones de desarrolladores profesionales para 2030, las herramientas de desarrollo generativo basadas en IA podrían equivaler a sumar 15 millones de "desarrolladores efectivos" adicionales a la capacidad mundial. E= ste aumento representaría una contribución sustancial a la actividad económica = generada por este sector de trabajadores, destacando el impacto transformador de la = IA en la economía global.

Figura 2<= /o:p>

Ganancias de la IA en el desarrollo de software

Fuente: (Griffi= ths, 2023)

=  A medida que los desarrolladores adopten herramientas para potenciar sus habilidades, adquirirán mayor destreza en el uso e interacción con la IA, lo que optimizará el ciclo de vida del desarro= llo. Esto contribuirá a democratizar el acceso al desarrollo de software, reduci= r la brecha laboral en el sector y convertir las herramientas de programación asistidas por IA en un componente esencial de la formación educativa estánd= ar para los desarrolladores.

 

 

 

 

Figura 3<= /o:p>

Porcentaje de aceptación= de herramientas con IA

Fuente: (Griffi= ths, 2023)

= Los desarrolladores señalaron que el principal beneficio de las herramientas de codificación basadas en IA era el fortalecimiento de sus habilidades en lenguajes de programación, lo que, según ellos, contribuye a tener una jorn= ada laboral más satisfactoria. Un objetivo del uso de la inteligencia artificia= l se centra precisamente en promover desarrolladores más productivos, competente= s y contentos con su trabajo.

Figura 4<= /o:p>

Productividad de los desarrolladores

Ejemplos de aplicación de la IA al desarrollo de software

= Un ejemplo de la aplicación de AI al trabajo de los desarrolladores es directamente la de generar código de aplicación.

= En este caso, se necesita escribir código Powershell para el plugin SnipDo de Windows. Se solicitó ChatGPT4 que escribiera este código.

= Este es el prompt donde se pide que escriba el códig= o:

“Escribe el código PowerShell que transfor= me una cadena de texto de entrada en el equivalente unico= de con aspecto de negrita. “    <= /o:p>

Y este es el resultado del codigo:

Figura 5<= /o:p>

Repuesta de código solicitado a CHATGPT

Fuente: (Ballarin, 2024)

 

 

4.     Conclusión

·       La implementación de inteligencia artificial ha transformado las etapas del ciclo de desarrollo, desde la codificación hasta las pruebas y el mantenimiento. Herramientas basadas en IA permiten automat= izar tareas repetitivas, detectar errores con mayor precisión y acelerar la entr= ega de productos, lo que resulta en una mayor eficiencia y calidad en el desarr= ollo de software.

·       El uso de la IA ha cambiado las competencias necesarias en los desarrolladores, orientándolos hacia tareas más creativas= y estratégicas. A medida que las herramientas de IA se integran en la práctica diaria, se fomenta el aprendizaje continuo y la capacidad de trabajar en colaboración con sistemas inteligentes, potenciando la productividad y la satisfacción laboral.

5.&n= bsp;    La inteligencia artificial no solo mejora la productividad de los equipos, sino que también democratiza el acceso al desarrollo de software, permitiendo que personas con conocimientos limitado= s en programación puedan participar en la creación de soluciones tecnológicas. Además, este avance tiene el potencial de generar un impacto económico significativo, impulsando la innovación y contribuyendo al crecimiento glob= al del sector tecnológico.

6.&n= bsp;    Conflicto de intereses

Los autores declaran que no existe conflicto de intereses.

7.&n= bsp;    Declaración de contribución de los autore= s

Todos autores contribuyeron significativamente en la elaboración del artículo.=

8.     Costos de financiamiento

La presente investigación fue financiada en su totalidad con fondos propios de los auto= res.

9.     Referencias bibliograficas

Ballarin, A. (2024). Cómo la {IA} potencia a los desarrolladores de software? In Linkedin.com. https://es.linkedin.com/pulse/cóm= o-la-ia-potencia-los-desarrolladores-de-software-ballarin--y0alf=

Bejarano, J. G. (2024). Cómo será= tu desarrollo de software si no incorporas inteligencia artificial? In Computing. https://es.linkedin.com/pulse/cómo-la-ia-potencia-los-desarrolladores-de-so= ftware-ballarin--y0alf

Escobar, C. H. (2024). Futuro y beneficios de la {IA} para programar. In OpenSistemas. https://opensistemas.com/futuro-y-beneficios-de-la-ia-para-programar/<= /o:p>

Galván, P. (2023). Impacto de la Inteligencia Artificial en el Desarrollo de Software. In {SG} Buzz. https://sg.com.mx/revista/56/inteligencia-artificial-desarrollo-software

García, J. (2023). Impacto = de {IA} en el desarrollo de software. In Telcel.com. https://www.telcel.com/empresas/tendencias/notas/desarrollo-software-con-ia=

Griffiths, A. L. (2023). {GitHub} Copilot: Un Año revolucionando la {IA}. In {DEV} Community. https://dev.to/github/github-copilot-un-ano-revolucionando-la-ia-466b<= /o:p>

Heinsohn. (2023). Desarrollo De Software Con Inteligencia Artificial. In Heinsohn. Heinsohn Business Technology. https://www.heinsohn.co/blog/desarrollo-de-software-con-inteligencia-artifi= cial/

Huet, P. (2024). Inteligencia artificial en desarrollo de software: Tendencias emergentes y futuro. In OpenWebinars.net. https://openwebinars.net/blog/inteligencia-artificial-en-desarrollo-de-soft= ware/

Mármol, J. (2023). Cómo la {IA} impulsa la nueva era del desarrollo de software. In Microsoft.com. https://news.microsoft.com/es-xl/como-la-ia-impulsa-la-nueva-era-del-desarr= ollo-de-software/

Rodríguez, E. (2024). Cómo la inteligencia artificial está transformando el desarrollo de software. In Blog de hiberus. Hiberus. https://www.hiberus.com/crecemos-contigo/inteligen= cia-artificial-desarrollo-software/

Solvex Dominicana, S. R. L. (2024= ). El Impacto de la Inteligencia Artificial en el Proceso de Desarrollo de Software. In Linkedin.com. https://es.linkedin.com/pulse/el-impacto-de-la-inteligencia-artificial-en-p= roceso-desarrollo-75ste

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El artículo que se publica es de exclusiva responsabilidad de los autor= es y no necesariamente reflejan el pensamiento de la Revista Ciencia & Turismo.


 

 

 

El artículo queda en propiedad de la revista y, por tanto, su publicaci= ón parcial y/o total en otro medio tiene que ser autorizado por el director de= la Revista Ciencia & Turismo.

 

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ISSN: 3028-8665<= /p>

Vol. 3 No. 4.  pp. 56<= /span>69, octubre – diciembre 2024=

Revista multidisciplinar

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www.cienciayturismo.or= g

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Guerra Poalasin et= al. (2024), ¿Cómo influye el uso de la inteligencia artificial en el desarr= ollo de software?. Artículo original. Ciencia &am= p; Turismo. ISSN: Vol. 3 No. 4.  p= p. 56 – 69, octubre – diciembre 2024

                 Edu= cación Ambiental             Página= 56= | 69

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