Source note
Contract-Coding: Towards Repo-Level Generation via Structured Symbolic Paradigm
Repo Level Code GenerationMulti Agent Software EngineeringCode IntelligenceSymbolic ContractsParallel Agent Orchestration
Summary
Contract-Coding is a repo-level code generation method that turns vague user intent into a structured contract, then uses that contract to coordinate parallel code generation and verification. The paper claims this reduces cross-file confusion and improves success on multi-file software tasks.
Problem
- Repo-level generation from vague intent often fails because agents generate files in sequence and must carry growing amounts of raw code context.
- Early design mistakes spread through later files, and long code histories push important architectural details out of the model's effective attention.
- This matters for autonomous software production because multi-file projects need consistent APIs, file structure, and cross-module behavior, not just locally valid code.
Approach
- The system first converts a loose user request into a Language Contract, a structured artifact that records requirements, APIs, module-to-file mapping, type signatures, and state definitions.
- Code generation is then factorized as: infer the contract from intent, then generate each file conditioned on the contract rather than on previously generated raw code.
- A Hierarchical Execution Graph (HEG) schedules tasks from the contract so multiple module implementations can run in parallel when their interfaces are already defined.
- A verifier and contract auditor check whether generated code matches the contract, whether required files and symbols exist, and whether code changes require contract updates.
- The contract is built and revised through constrained add/update operations, with checks for issues such as invalid graph structure or inconsistent signatures.
Results
- On the Greenfield-5 benchmark, the full method reports 100% success on Gomoku in 136s, 100% on Plane Battle in 117s, 87% on City Sim in 257s, 80% on Snake++ in 198s, and 47% on Roguelike in 232s.
- Against academic multi-agent baselines on Roguelike, Contract-Coding reports 47% success versus 30% for OpenHands, 10% for MetaGPT, 10% for ChatDev, and 0% for FLOW.
- Against commercial tools on Roguelike, it matches Trae at 47%, beats CodeBuddy at 40%, beats Lingma at 33%, and trails Gemini Studio at 63%.
- The HEG ablation shows the same success rate but lower speed: on Roguelike, Ours w/o HEG gets 47% in 510s, while Ours (Full) gets 47% in 232s; on Snake++, 78% in 465s improves to 80% in 198s.
- The paper claims a sub-linear context effect: for the Roguelike task, a repository of 8,857 tokens is reduced to a contract of about 1,900 tokens, or about 4.6x compression.
- The abstract also claims 47% functional success with near-perfect structural integrity on Greenfield-5, but the excerpt does not provide a direct numeric structural-integrity metric.