
Applications of Modern Software Engineering Methods in Cloud Service Projects - An Example of Charging Piles
- 1 Northwest Normal University, School of Computer Science and Engineering, Lanzhou, Gansu, 730000, China
* Author to whom correspondence should be addressed.
Abstract
In the environment of the continuous development of the new energy industry, the traditional software engineering methods have been gradually backward in the face of the ever-complex demands, so this paper analyses the successful implementation of the charging pile cloud service project of Company T as an example, and explores how the modern software engineering methods can promote the development efficiency and the development quality of the cloud service project. This paper adopts the case study method and comparative analysis method. It is found that after applying the new software engineering methodology, the development quality and development efficiency of the project are significantly improved, and the final product has high reliability and stability, which meets the current market demand. Compared with the products developed using the traditional methodology, the products developed using the software engineering methodology have gone through the development process of requirements definition and system design, agile development and continuous integration, and have an advantage in the development cycle and development quality. In the subsequent operation and maintenance, the new software engineering approach uses DevOps thinking to incorporate post-operation at the time of development, which allows for continuous updating of the product operation and maintenance, and reduces costs through automated operation and maintenance. This paper supplements the theory of software engineering methodology for cloud service project development and further illustrates the significance of applying the new methodology to software development projects, which can provide reference suggestions for the development of the industry.
Keywords
Software Engineering Methods, Cloud Services, Charging Pile, Project Development
[1]. Zilong Qin. (2024) Analysis of the current situation of the development of new energy automobile industry in China and its countermeasures. Modern Industrial Economy and Informationization,14:131-143.
[2]. Ze Tian, Zixian Liu, Yangjun Ren. (2025) Mechanism research on digital economy empowering new energy automobile industry high-quality development. Journal of Industrial Technological Economics, 2:67-77.
[3]. Pressman, R. S., & Maxim, B. R. (2020). Software Engineering: a Practitioner's Approach (9th ed.). McGraw-Hill Education.
[4]. Huaxiao Liu. (2014) Research on Some Lssues in Requirements Engineering.4. (Dissertation).
[5]. Jingshan Kang, Yong Han, Yingbo Duan. (2024) Research on Software Testing Methods. Electronic Product Reliability and Environmental Testing, 5:76 -82.
[6]. Pingping Fu, Fuyong Zheng, Hua Wang, Min Li, Shi Yu. (2022) Development of Intelligent Charging Pile Management System and Mobile Application Based on Cloud Platform. Microcomputer Applications, 6:180-183.
[7]. Haoyu Wang. (2022) Review on Technologies of Requirement Engineering of Software. Computer Science, S2:766-779.
[8]. Miao Guo. (2024) DevOps platform design based on containers and microservices [J]. Computer Knowledge and Technology, 2024, 20(27):52-55. DOI:10.14004/j.cnki.ckt.2024.1393.
[9]. Ru An. (2024). Agile Development Methodology and Project Management Practice in Software Technology. Changjiang Information & Communications, 10:156-158.
[10]. Xiumin Hua. (2022). Research on quality management of internet projects based on agile development model. Electronic Communication & Computer Science, 4(1).
[11]. Zhi Jin, Lin Liu, Xiaohong Chen, Tong Li. (2023) Software Requirements Engineering Methodology and Practice, Tsinghua University Press, Beijing.
Cite this article
Xu,Y. (2025). Applications of Modern Software Engineering Methods in Cloud Service Projects - An Example of Charging Piles. Applied and Computational Engineering,146,76-82.
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Volume title: Proceedings of SEML 2025 Symposium: Machine Learning Theory and Applications
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