[2603.21430] DomAgent: Leveraging Knowledge Graphs and Case-Based Reasoning for Domain-Specific Code Generation

Computer Science > Artificial Intelligence arXiv:2603.21430 (cs) [Submitted on 22 Mar 2026] Title:DomAgent: Leveraging Knowledge Graphs and Case-Based Reasoning for Domain-Specific Code Generation Authors:Shuai Wang, Dhasarathy Parthasarathy, Robert Feldt, Yinan Yu View a PDF of the paper titled DomAgent: Leveraging Knowledge Graphs and Case-Based Reasoning for Domain-Specific Code Generation, by Shuai Wang and 2 other authors View PDF HTML (experimental) Abstract:Large language models (LLMs) have shown impressive capabilities in code generation. However, because most LLMs are trained on public domain corpora, directly applying them to real-world software development often yields low success rates, as these scenarios frequently require domain-specific knowledge. In particular, domain-specific tasks usually demand highly specialized solutions, which are often underrepresented or entirely absent in the training data of generic LLMs. To address this challenge, we propose DomAgent, an autonomous coding agent that bridges this gap by enabling LLMs to generate domain-adapted code through structured reasoning and targeted retrieval. A core component of DomAgent is DomRetriever, a novel retrieval module that emulates how humans learn domain-specific knowledge, by combining conceptual understanding with experiential examples. It dynamically integrates top-down knowledge-graph reasoning with bottom-up case-based reasoning, enabling iterative retrieval and synthesis of structured kno...