arXiv AI
A Hybrid Dependency-Aware Framework for Task Decomposition and Dynamic Agent Generation in Oracle-to-PostgreSQL Migration
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arXiv AI
Aug 24
Specification Portability Across LLM Development Agents: Cross-Agent Compatibility in Specification-Driven Software Migration
arXiv:2608.21208v1 Announce Type: cross Abstract: This paper investigates cross-agent specification portability using Oracle-to-PostgreSQL migration as a controlled software transformation task. The...
arXiv AI
Aug 21
Measuring What a Specification Determines: A Formal Semantic-Block Model and an Execution-Judged Benchmark
arXiv:2608. 19475v1 Announce Type: cross Abstract: This work introduces a formal semantic-block model for specifications and an execution-judged benchmark for evaluating specification quality independently of model capability.
arXiv AI
Aug 26
Identifying Latent Declarative Representations of Code for Assisting Repository Migration
The paper introduces ADFD‑Migrate, a method that extracts a latent declarative representation of code—an annotated data‑flow diagram (ADFD)—to aid large‑scale repository migration. By using an LLM to infer the source ADFD from repository context and guiding target‑language generation with dependency‑aware chunking, the approach improves porting soundness and completeness. Evaluated on 50 Fortran repositories, the system achieves high behavioral agreement and a superior migration outcome index compared to baseline translation methods.
arXiv AI
Sep 10
ProcArena: A Multi-Scenario Benchmark for LLMs on Direct and Interactive PL/SQL Development from Natural Language
ProcArena is a new benchmark for evaluating large language models on natural‑language to PL/SQL translation tasks. It contains 3,998 executable tasks across 157 databases, covering nine development subscenarios in PostgreSQL and Oracle, and supports both direct generation and interactive multi‑turn scenarios. Experiments on seven models show that even the best performers achieve only about 62% accuracy in direct mode and 58% in interactive mode, highlighting the difficulty of realistic NL‑to‑PL/SQL development.
arXiv AI
Jun 2
APEX-SQL: Talking to the data via Agentic Exploration for Text-to-SQL
arXiv:2602. 16720v2 Announce Type: replace-cross Abstract: Text-to-SQL systems powered by Large Language Models have excelled on academic benchmarks but struggle in complex enterprise environments.
arXiv AI
5d ago
LYNX: Analytical Program Synthesis via Grounding and Closed-Loop Refinement
arXiv:2610.14777v1 Announce Type: new Abstract: LLM-powered data analytics aims to translate natural language instructions into executable analytical programs over underlying data. However, existing...