aiqbench analysis
VISTA introduces a rigorous benchmark for coding agents by evaluating their ability to generate fully functional web and mobile applications from design specifications, rather than just visual mockups. The study reveals significant gaps in current agent systems, where most fail to implement interactive behaviors correctly despite producing visually accurate interfaces. This work is critical for advancing the reliability of AI-driven software development pipelines.
VISTA: An End-to-End Benchmark for Visual Spec-to-Web-App Coding Agents
arXiv:2605.26144v4 Announce Type: replace-cross Abstract: Coding agents can now build applications from design mockups, but a screen that looks right is not an application that works. Existing benchmarks either score visual reconstruction without a backend or test full-stack functionality from textual requirements, and few tie scores to the individual components a design requires. We introduce VISTA (VIsual Spec-To-App), an end-to-end benchmark in which coding agents turn multi-page design handoffs (Figma renders, structure, and textual requirements) into runnable full-stack Web and Mobile (Android) applications. VISTA provides 8,487 human-annotated interactive components across 18 applications (126 Web pages and 576 Android screens) and an executable evaluator that locates annotated components in the running application and probes their interactions, yielding localization, behavior, and joint scores traceable to individual design requirements. Across 14 deployed coding-agent systems, the best joint score is 0.553 on Web and 0.378 on Mobile, and 13 of 14 systems score lower on behavior than on localization on Web. Component probes detect unresponsive controls in 90.1% of audited Web deliveries. Development traces show where the process departs from the task: 44.5% of trajectories never open the design screenshots, 73.0% omit the prescribed self-audit, and 8.3% report success after a failed check. VISTA makes the gap between rendering a design and delivering a working application measurable at the level of individual components. Code is available at \href{https://github.com/kaboider/VISTA_Bench}.
Abstract:Coding agents can now build applications from design mockups, but a screen that looks right is not an application that works. Existing benchmarks either score visual reconstruction without a backend or test full-stack functionality from textual requirements, and few tie scores to the individual components a design requires. We introduce VISTA (VIsual Spec-To-App), an end-to-end benchmark in which coding agents turn multi-page design handoffs (Figma renders, structure, and textual requirements) into runnable full-stack Web and Mobile (Android) applications. VISTA provides 8,487 human-annotated interactive components across 18 applications (126 Web pages and 576 Android screens) and an executable evaluator that locates annotated components in the running application and probes their interactions, yielding localization, behavior, and joint scores traceable to individual design requirements. Across 14 deployed coding-agent systems, the best joint score is 0.553 on Web and 0.378 on Mobile, and 13 of 14 systems score lower on behavior than on localization on Web. Component probes detect unresponsive controls in 90.1% of audited Web deliveries. Development traces show where the process departs from the task: 44.5% of trajectories never open the design screenshots, 73.0% omit the prescribed self-audit, and 8.3% report success after a failed check. VISTA makes the gap between rendering a design and delivering a working application measurable at the level of individual components. Code is available at \href{this https URL}.
Software Engineering (cs.SE); Artificial Intelligence (cs.AI); Computer Vision and Pattern Recognition (cs.CV)
arXiv:2605.26144 [cs.SE]
(or arXiv:2605.26144v4 [cs.SE] for this version)
https://doi.org/10.48550/arXiv.2605.26144 Focus to learn more arXiv-issued DOI via DataCite
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