Performance Assessment of Traditional Software Development Methodologies and DevOps Automation Culture


  • P. Narang Department of Computer Science and Applications, Maharshi Dayanand University, India
  • P. Mittal Department of Computer Science and Applications, Maharshi Dayanand University, India
Volume: 12 | Issue: 6 | Pages: 9726-9731 | December 2022 |


Successful implementations of Software Development Methodologies significantly improve software efficiency, collaboration and security. Most companies are moving away from traditional development methodologies towards DevOps for faster and better software delivery. DevOps, which is a primary need of the IT industry, brings development and operation teams together to overcome communication gaps responsible for software failures. It relies on different sets of automation tools to robotize the tasks of software development from continuous integration, to testing, delivery, and deployment. The existence of several automation tools in each development phase raises the need for an integrated set of tools to reduce development time. For this purpose, we used the DevOps-based hybrid model Integrated Tool Chain (ITC), along with three sample java-based projects or code repositories to quantify the results. This paper evaluates and compares measurement metrics of java projects using traditional development methodologies and DevOps, and the results are shown in tabular and graphical format. The latest Google and Stack Overflow Trends have also been included to retrieve the best performer development methodology. This comparative and evaluative performance analysis will be beneficial to young researchers that study the metrics of software development, while also they will be introduced to the automotive environment of DevOps, the latest emerging buzzword in software development.


automation, automation tools, integrated tool chain, software development, DevOps


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How to Cite

P. Narang and P. Mittal, “Performance Assessment of Traditional Software Development Methodologies and DevOps Automation Culture”, Eng. Technol. Appl. Sci. Res., vol. 12, no. 6, pp. 9726–9731, Dec. 2022.


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