# Feature-Factory: Automating Software Feature Integration Using Generative AI

arXiv: https://arxiv.org/abs/2411.18226 · HTML: https://mlsanity.com/paper/2411.18226/

## Key facts

- No citing papers in the map yet (data through 14 Oct 2026).
- Builds on 3 of its 10 references that are in the map.
- First posted on arXiv 27 Nov 2024.

## Builds on (most cited first, 3 of 3)

- [GPT-4 Technical Report](https://mlsanity.com/paper/2303.08774/) (2023)
- [Evaluating Large Language Models Trained on Code](https://mlsanity.com/paper/2107.03374/) (2021)
- [GitHub Copilot AI pair programmer: Asset or Liability?](https://mlsanity.com/paper/2206.15331/) (2022)

## Abstract (arXiv)

Integrating new features into existing software projects can be a complex and time-consuming process. Feature-Factory leverages Generative AI with WatsonX.ai to automate the analysis, planning, and implementation of feature requests. By combining advanced project parsing, dependency resolution, and AI-generated code, the program ensures seamless integration of features into software systems while maintaining structural integrity. This paper presents the methodology, mathematical model, and results of the Feature-Factory framework.