Última alteração: 2024-01-07
Resumo
With the growth of new artificial intelligence tools capable of assisting in the construction of software in increasingly faster and optimized ways, there is a need to analyze the impacts that these tools have on the development of new applications. This article aims to conduct a literature review to evaluate the effects of adopting artificial intelligence tools in software development. As a result, this work provides an overview of the impacts and challenges encountered in the adoption of these tools in the field of software engineering.
Com o crescimento de novas ferramentas de inteligência artificial capazes de auxiliar na construção de software de forma cada vez mais rápidas e otimizadas, há uma necessidade de analisar os impactos que estas ferramentas tem sobre o desenvolvimento de novas aplicações. Este artigo tem como objetivo realizar uma revisão da literatura para avaliar os efeitos da adoção de ferramentas de inteligência artificial no desenvolvimento de software. Como resultado, este trabalho apresenta um panorama geral sobre os impactos e os desafios encontrados na adoção dessas ferramentas na área de engenharia de software.
Palavras-chave
Referências
ABES. Mercado Brasileiro de Software: panorama e tendências, 2022.
BARENKAMP, M.; REBSTADT, J.; THOMAS, O. Applications of AI in classical software engineering. AI Perspectives, v. 2, n. 1, p. 1, 2020.
BOEHM, B. W.; PAPACCIO, P. N. Understanding and controlling software costs. IEEE transactions on software engineering, v. 14, n. 10, p. 1462-1477, 1988.
BRASSCOM. Estudo da Brasscom aponta demanda de 797 mil profissionais de tecnologia até 2025, 2021.
IBM. Estudo IBM: 41% das empresas no Brasil já implementaram ativamente inteligência artificial em seus negócios. IBM Comunica, 2022.
ISO/IEC/IEEE 24765 - Systems and software engineering — Vocabulary. Geneva, Switzerland: ISO/IEC, 2017.
ISO/IEC 25010 - Systems and software engineering – Systems and software Quality Requirements and Evaluation (SQuaRE) – System and software quality models, 2011.
ISO/IEC/TR24772-1 - Programming languages – Guidance to avoiding vulnerabilities in programming languages – Part 1: General, 2019.
KORZENIOWSKI,L; GOCZYLA,K Artificial intelligence for software development: the present and the challenges for the future Biuletyn Wojskowej Akademii Technicznej v68 n1-2019
KOTHARI, D. How artificial intelligence accelerates software development International Research Journal of Engineering and Technology (IRJET), v. 6, n. 8, p. 1392-1394, 2019.
KRASNER, H. Cost of Poor Software Quality in the U.S.: A 2022 Report. CISQ, Jan 2023.
LIU,S Development Trend of Computer Artificial Intelligence Technology Optimization Strategy in Software Development Journal of Physics: Conference Series v2037 p12006-2021
MARTIN, R. C. Clean Code: A Handbook of Agile Software Craftsmanship. 1. ed. USA: Prentice Hall PTR, 2008.
MCCARTHY, J. et al. What is artificial intelligence. Stanford University, 2007.
PAULK, M. C. et al. The Capability Maturity Model: Guidelines for Improving the Software Process. USA: Addison-Wesley Longman Publishing Co., Inc., 1995.
RUSSELL, S.; NORVIG, P. Artificial Intelligence: A Modern Approach, 2010.
SORTE,B.W; JOSHI,P.P; JAGTAP,V Use of artificial intelligence in software development life cycle—a state of the art review International Journal of Advanced Engineering and Global Technology v3 n3 p398-403-2015
STRIPE. The Developer Coefficient, 2018.
TURING, A. Computing Machinery and Intelligence, 1950.
VALENTE, M.T Engenharia de software moderna Princípios e Práticas para Desenvolvimento de Software com Produtividade v.1 p24-2020
Williams, L. Secure Software Lifecycle Knowledge Area Issue 1.0. In A. Martin (Ed.), CyBOK – The Cyber Security Body of Knowledge (pp. 517-550), 2019.