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PACGBI: A Pipeline for Automated Code Generation from Backlog Items

Authors: Sarschar, Mahja and Zhang, Gefei and Nowak, Annika

Abstract:

While there exist several tools to leverage Large Language Models (LLMs) for code generation, their capabilities are limited to the source code editor and are disconnected from the overall software development process. These tools typically generate standalone code snippets that still require manual integration into the codebase. There is still a lack of integrated solutions that seamlessly automate the entire development cycle, from backlog items to code generation and merge requests. We present the Pipeline for Automated Code Generation from Backlog Items (PACGBI), an LLM-assisted pipeline integrated into GitLab CI. PACGBI reads backlog items in the code repository, automatically generates the corresponding code, and creates merge requests for the generated changes. Our case study demonstrates the potential of PACGBI in automating agile software development processes, allowing parallelization of development and reduction of development costs. PACGBI can be utilized by software developers and enables nontechnical stakeholders and designers by providing a holistic solution for using LLMs in software development. A screencast of this tool is available at https://youtu.be/TI53m-fIoyc, its source code at https://github.com/Masa-99/pacgbi.

Link: Read Paper

Labels: code generation, program synthesis