ObSynth: An Interactive Synthesis System for Generating Object Models from Natural Language Specifications
This addresses the challenge of specification reification for software developers, though it is incremental as it builds on existing LLM capabilities without reducing design time.
The authors tackled the problem of designing object models from natural language specifications by introducing ObSynth, an interactive system that leverages LLMs to synthesize detailed components, resulting in more detailed models with a majority of generated objects, methods, and fields being retained by users.
We introduce ObSynth, an interactive system leveraging the domain knowledge embedded in large language models (LLMs) to help users design object models from high level natural language prompts. This is an example of specification reification, the process of taking a high-level, potentially vague specification and reifying it into a more concrete form. We evaluate ObSynth via a user study, leading to three key findings: first, object models designed using ObSynth are more detailed, showing that it often synthesizes fields users might have otherwise omitted. Second, a majority of objects, methods, and fields generated by ObSynth are kept by the user in the final object model, highlighting the quality of generated components. Third, ObSynth altered the workflow of participants: they focus on checking that synthesized components were correct rather than generating them from scratch, though ObSynth did not reduce the time participants took to generate object models.