发表机构
EPAM Systems（EPAM系统公司）
机构由 AI 辅助整理，请以论文原文为准。AI 中文总结
本文以Oracle到PostgreSQL的软件迁移为任务，评估了Amazon Kiro等多个LLM开发智能体在规范驱动迁移中的表现，发现跨智能体迁移存在性能下降，提出需重视规范可移植性等问题。
AI 中文摘要
本文以Oracle到PostgreSQL的迁移作为受控软件转换任务，研究跨智能体的规范可移植性，研究包含两个实验阶段。第一阶段，对1006个PL/SQL文件评估了一种以规范为先的迁移流水线，其中623个文件被成功再生，380个生成的脚本可在PostgreSQL 16中成功执行。第二阶段，使用包含1802个Oracle脚本及对应PostgreSQL实现的数据集开展跨智能体实验，涉及Amazon Kiro、Google Gemini、GitHub Copilot，初始单智能体评估还纳入了Claude Code和Cursor。采用Token F1、精确匹配、SQL语法有效性、AST精确匹配、AST平均相似度及即时可运行性对原生和外部规范进行评估。结果显示，仅规范规模无法预测实现质量，跨智能体迁移会产生显著的智能体依赖型性能下降；最强的复现案例为Gemini直接使用Kiro生成的规范，其Token F1为0.035，SQL语法有效性为2.33%，AST平均相似度为0.015。重写在测试配置中大幅提升了Gemini的性能，压缩未提供通用益处，检索增强型数据摄取是Gemini和Copilot的智能体Pareto前沿中唯一共同的策略。研究结果表明，异构SDD工作流中的规范不应自动视为智能体中立的制品，需明确考虑规范可移植性、智能体特定解释及多智能体软件工程中基于检索的访问。
英文摘要
This paper investigates cross-agent specification portability using Oracle-to-PostgreSQL migration as a controlled software transformation task. The study combines two experimental stages. First, a specification-first migration pipeline was evaluated on 1,006 PL/SQL files, of which 623 were successfully regenerated and 380 generated scripts executed successfully in PostgreSQL 16. Second, cross-agent experiments were conducted on a dataset of 1,802 Oracle scripts with corresponding PostgreSQL implementations using Amazon Kiro, Google Gemini, and GitHub Copilot, with Claude Code and Cursor included in the initial single-agent evaluation. Native and foreign specifications were assessed using Token F1, exact match, SQL syntax validity, AST exact match, AST mean similarity, and immediate runnability. The results show that specification size alone does not predict implementation quality and that cross-agent transfer can produce substantial agent-dependent degradation. The strongest replicated case occurred when Gemini directly consumed a Kiro-origin specification, producing a Token F1 of 0.035, SQL syntax validity of 2.33%, and AST mean similarity of 0.015. Rewriting substantially improved Gemini in the tested configuration, compression did not provide a universal benefit, and retrieval-augmented ingestion was the only common strategy represented on the per-agent Pareto frontiers of both Gemini and Copilot. The findings suggest that specifications in heterogeneous SDD workflows should not automatically be treated as agent-neutral artifacts and motivate explicit consideration of specification portability, agent-specific interpretation, and retrieval-based access in multi-agent software engineering.
Comments11 pages, 4 figures, 7 tables, 27 references
