Software Engineering for and with GUI Agent
2026-08-10 • Software Engineering
Software EngineeringArtificial Intelligence
AI summaryⓘ
The authors reviewed hundreds of papers on GUI agents—software that interacts with user interfaces—and found the field has grown a lot recently but still faces many practical problems. These agents often break easily and lack important features like error recovery, clear safety checks, and ways for humans to step in when needed. Evaluations mainly focus on task success, missing broader testing and long-term maintenance. The authors suggest future research should improve dependable operation, better testing throughout the software’s life, privacy protections, and human oversight to make these agents reliable and safe for real-world use.
GUI agentsperceive-reason-act loopsoftware lifecycleevaluation metricserror recoveryhuman oversightprivacy engineeringbenchmarkingdeployabilityauditability
Authors
Shengcheng Yu, Yuchen Ling, Junyang Xing, Quan Zhou, Chunrong Fang, Zhenyu Chen
Abstract
GUI agents have advanced rapidly, producing a growing body of frameworks, benchmarks, and applications. However, this growth has outpaced the maturity of the field. GUI agents remain technically brittle, incompletely engineered, and insufficiently validated for sustained real-world use. They are evolving into closed-loop software systems. Within these systems, model reasoning is coupled with interface perception, execution feedback, recovery, and human oversight. This evolution calls for a software engineering perspective that remains largely absent from existing research. We address this gap by reviewing 336 GUI-agent papers from January 2018 to April 2026. Five research questions examine the research landscape, architectures, evaluation, software lifecycle concerns, and future opportunities. Our findings show that the field has expanded sharply since 2024, while mobile and web settings remain dominant. Architectures increasingly adopt modular perceive-reason-act loops, but recovery, human escalation, safety enforcement, and auditability remain underdeveloped. This architectural imbalance extends to evaluation. Evaluations are becoming more interactive, but they remain centered on task success and are difficult to compare across protocols. More broadly, existing studies provide limited support for testing beyond benchmarks and for maintaining agents after release. Observability, privacy engineering, and systematic human oversight are also underdeveloped. Together, these findings show that capability improvements alone cannot ensure deployment readiness. Future research should connect dependable execution with lifecycle-centered testing and reproducible evaluation. It should also integrate permission and privacy controls with cost-aware, human-centered governance. This integration is necessary to build dependable, maintainable, secure, and deployable GUI-agent systems.