Optimization of Software Development Processes Through the Use of Full-Stack Technologies and Automation

Denys Drofa
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Denys Drofa: Engineering Department, Smart Barrel, Inc, 7251 NE 2nd Ave Suite 102, Miami, FL 33138, USA

Contemporary Issues in Artificial Intelligence, 2025, vol. 1, issue 1

Abstract: The research examines the impact of MERN and MEAN full-stack technologies and automation tools on software development processes. It analyzes case studies from 2019 to 2024 and finds that these technologies lead to significant improvements in productivity and shorter development times. They are 25–35% faster than other development approaches due to their modularity and integrated design approaches. React’s reusable bits, Angular’s two-way data binding, and Node.js’s asynchronous processing help teams work together. Automation tools like Jenkins, Selenium, Docker, and Kubernetes manage testing and deployment, achieving a 40% decrease in next deployment time and a 50% reduction in defect rate. Cost efficiency can reach 20–40% due to single development practices and optimal resource use. However, challenges like high-slope learning and initial configuration difficulties remain. These can be addressed through training programs, community support, and partnering tools with project needs. The integration of MERN and MEAN stacks with automation tools provides a strong foundation for software development, promoting efficiency, better quality, and less expense.

Keywords: Deep Learning; Software Development; Automated Testing; Machine Learning; Full Stack (search for similar items in EconPapers)
Date: 2025
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Persistent link: https://EconPapers.repec.org/RePEc:cvj:ciai01:v:1:y:2025:i:1:n:1

DOI: 10.69635/ciai.2025.12

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