International Journal of Computer Applications |
Foundation of Computer Science (FCS), NY, USA |
Volume 186 - Number 54 |
Year of Publication: 2024 |
Authors: Ravi Kiran Mallidi, Manmohan Sharma, Yogeswara Prasad Paladugu |
10.5120/ijca2024924268 |
Ravi Kiran Mallidi, Manmohan Sharma, Yogeswara Prasad Paladugu . Story Point Estimate Model: Project Development using Generative AI (GenAI) Tools. International Journal of Computer Applications. 186, 54 ( Dec 2024), 68-71. DOI=10.5120/ijca2024924268
Software development estimations by using Agile story points are crucial for predicting effort, cost, and scope. Currently, management is encouraged to explore the usage of AI tools for their practices to improve code productivity and debugging capabilities. In the past couple of years, Generative Artificial Intelligence (GenAI) tools have evolved and Organizations are using different tools in SDLC phases Architecture, Development, Testing, and Maintenance activities. GenAI usage in projects enhances productivity, eliminates bugs, and makes it more competitive for managing challenges. This paper discusses GenAI usage in software development and how Story Point estimates are derived, adjusted, and arrived at to complete the use case—conducted interviews with the development team where the Copilot and ChatGPT were used and identified the factors for considering the effort estimations. For the usage of the GenAI tools, the development cost may be reduced when compared with the traditional way of development which leads to a decrease in Agile Story Points. Presented the factors impacted while doing story point analysis for the usage of GenAI tools like ChatGPT, and Copilot. Coding assisting tools by GenAI provide code suggestions, tasks, code blocks, and standards. Educating project teams and shift of mindset and methodology required for usage of GenAI in project development and estimating the project.