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arxiv:2610.16402

EvoWeb: A Benchmark for Coding Agents on Evolving Web Applications

Published on Oct 12
ยท Submitted by
B Alon
on Oct 19
ยท TD-Labs TD Labs
Authors:
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Abstract

Web application development often proceeds through successive requests that extend an existing implementation. Yet web-generation benchmarks primarily evaluate development toward fixed specifications. We introduce EvoWeb, a novel benchmark comprising 320 cumulative requests over 32 web applications, grounded in real-world product features and structured by functional dependency graphs. Agents iteratively modify a persistent codebase, while a multimodal web agent tests each intermediate application in a live browser, assessing newly requested functionality, cross-request integration, and previously requested functionality. To characterize reliability throughout development, we integrate trajectory performance across user-tolerance thresholds rather than impose a fixed stopping criterion. Experiments across open- and closed-source frontier models show that EvoWeb reveals clear performance differences between models, with cross-request integration emerging as a key challenge. Further analysis shows that later requests with deeper or more numerous dependencies are solved less accurately, while runtime errors become more frequent over successive requests. EvoWeb provides a testbed for evaluating and improving coding agents in long-horizon, multi-request development.

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Most web-generation benchmarks test agents against a fixed spec, but real apps grow through successive requests. EvoWeb has 320 cumulative requests over 32 web apps, built on functional dependency graphs. A multimodal web agent tests every intermediate version in a live browser for new features, how they integrate with earlier ones, and regressions. Across open and closed frontier models, the hardest part is making new requests work with earlier ones, and runtime errors pile up as development goes on.

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