Author(s)

Chuanqiang Sun

Corresponding Author

Chuanqiang Sun

Abstract

With the rapid development of big data technologies, software engineering project development methods are evolving. Traditional software development methods face many challenges when dealing with large amounts of complex data, and big data analytics provides new ways to solve these problems. This study aims to explore software engineering project development methodologies based on big data analytics and propose a new development framework that utilizes the advantages of big data to improve the efficiency and quality of project development. This paper first outlines the current status of the application of big data analytics in software engineering, and then describes in detail the big data-driven project development methods based on big data, including the enhancement of agile methodology, the application of predictive analytics, and so on, and demonstrates the practical effects of these methods through case studies. Finally, the paper discusses the technical and organizational challenges faced by big data-driven approaches in the implementation process and looks forward to future research directions. The findings show that methods based on big data analysis can significantly improve the development efficiency and quality of results in software engineering projects, providing a valuable reference for industry practice.

Keywords

Big data analytics, software engineering, project development, data-driven methods, agile development, predictive analytics, software development life cycle