# From Runnable to Shippable: Multi-Agent Test-Driven Development for Generating Full-Stack Web Applications from Requirements

arXiv: https://arxiv.org/abs/2605.17242 · HTML: https://mlsanity.com/paper/2605.17242/

## Key facts

- Cited by 1 papers in the map (data through 14 Oct 2026).
- Placed in Software engineering coding agents, one of 16 directions in LLM agents and tool use.
- First posted on arXiv 17 May 2026.

## Placed in

- LLM agents and tool use / [Software engineering coding agents](https://mlsanity.com/agents/software-engineering-coding-agents/)

## Built on by (most cited first, 1 of 1)

- [CodeShrink: Adaptive Visual Compression for Efficient Multimodal Code Understanding](https://mlsanity.com/paper/2607.29637/) (2026)

## Abstract (arXiv)

Coding agents can generate runnable web applications, but their outputs frequently fail to satisfy functional requirements. Although test-driven development (TDD) offers a principled repair loop, applying it to web applications requires deriving executable acceptance tests, validating behavior through dynamic browser interactions, and translating observed failures into actionable feedback. We present TDDev, an experimental instrument that automates these tasks and enables closed-loop TDD with minimal human mediation. Using TDDev, we conduct the first controlled study of TDD for full-stack web application generation across 20 diverse web applications, multiple backbone models, two coding agents, and three TDD implementations. With sufficiently capable backbones, TDD improves accuracy by 15.5--23.7 percentage points and remains effective across both minimal and full-featured coding agents; replacing unreliable feedback with a stronger tester restores positive gains for a lower-capability backbone. Incremental TDD provides bounded control, Whole-Project TDD enables coordinated repair and achieves the highest cost efficiency in most configurations, and Agentic TDD performs best with highly capable models. Based on these findings, we provide a practical decision tree that selects an implementation according to model capability, feedback reliability, and deployment objectives. By automating acceptance testing and failure-guided repair, TDDev also reduces the human testing and intervention required during development.