Modern software engineering transcends isolated code edits: engineers run applications, interact with GUI interfaces, and visually inspect rendering feedback to diagnose errors and verify changes. CUA-SWE bridges coding agents and computer-use agents by introducing the first unified benchmark and environment for visual software engineering. Spanning four engineering domains, CUA-SWE challenges agents to interleave code/config modifications, terminal execution, GUI interactions, and screenshot inspections, with deterministic test suites evaluating behavioral correctness.
Key Takeaways
- ✓First multimodal visual software engineering benchmark coupling computer-use capabilities with code repositories
- ✓Text-only agents stall below 12% on visual defect repairs, while closed-loop visual feedback elevates success to 43.8%
- ✓Identifies attention contention bottlenecks between high-resolution GUI screenshots and repository-scale source code
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Background and the Problem
Traditional coding benchmarks like SWE-bench assume specifications and verification are purely text-based. In industry, visual defects (layout glitches, interactive race conditions, canvas rendering) cannot be diagnosed or resolved without launching applications, manipulating interfaces, and visually inspecting state changes. Coding agents and computer-use agents (CUA) have remained siloed, leaving visual software engineering unaddressed.
Architecture and How It Works
CUA-SWE establishes a unified testbed combining code manipulation with interactive visual environments:
- Integrated Multi-Modal Sandbox: Equips agents with terminal access, code editing tools, and direct graphical interaction (mouse/keyboard events, screenshot feeds).
- Visually-Gated Specifications: Tasks purposefully place essential requirements exclusively within active UI interfaces, compelling agents to interact and inspect runtime behavior.
- Visual-Code Causal Mapping: Assesses whether agents can trace visual UI artifacts back to underlying component lifecycles, CSS properties, or state machines.
- Deterministic Dual-Layer Verification: Couples behavioral GUI interaction suites with standard unit test harnesses to guarantee functional compliance.
Benchmarks and Measured Results
Evaluated across Web, Desktop GUI, Interactive Dashboards, and Game Tooling:
- Text-Only Agents Suffer Severe Degradation: Deprived of GUI feedback, frontier models solve less than 12% of visually-dependent bug repairs.
- Closed-Loop Visual Feedback Elevates Success to 43.8%: Interleaving visual inspection with incremental code edits propels success rates to 43.8% for leading frontier models.
- Attention Bottlenecks Identified: Dense visual tokens across extended interaction horizons create context contention against repository-scale code navigation.
Getting Started for Developers
CUA-SWE is open-sourced on GitHub with containerized environments and automated runners. Teams building next-generation multimodal IDEs can leverage CUA-SWE to train and validate agents that possess both code-generation and visual-verification capabilities.
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