Test Automation

Ship Faster with Confidence

Build quality into every release with our suite of automation tools and frameworks.

Upcoming Automation Projects

2026 Q1

Enterprise Java Framework

Advanced reporting, enhanced CI/CD integrations, and enterprise-grade features for the Java Test Framework.

2026 Q1

TypeScript Framework Release

Full-featured Playwright TypeScript framework with Gherkin support, Page Object Model, and comprehensive reporting.

2026 Q2

Web Interface for Tools

Web-based interface for Fixture Builder and Gherkin Generator with upload, preview, and export capabilities.

2026 Q2

Domtree Cloud Integration

Cloud platform for reusable test datasets, AI-powered test data generation, and community template sharing.

Tools

Agentic

Automation Frameworks

Fixture Builder

Generate clean, consistent and test-ready data fixtures from CSV, JSON, PDF or DOCX documents.

Powered by OpenAI GPT-4o-mini and built in Node.js + TypeScript.

What is Fixture Builder?

Fixture Builder is a lightweight CLI that transforms real data into normalised, ready-to-use fixtures for Cypress, Playwright, or raw JSON tests.

It supports multiple input formats: CSV/JSON ingestion for structured data, and AI-powered extraction for PDF and DOCX documents — turning unstructured documents like reports, tables, and specifications into structured JSON automatically.

Using OpenAI GPT-4o-mini, the AI engine intelligently recognises headers, extracts tables, and structures data from PDF and Word documents, making it perfect for converting legacy documents or specifications into test-ready fixtures.

It combines automation efficiency with human insight — letting teams move faster without compromising product understanding or quality.

Built in Node.js + TypeScript — with schema inference, deterministic masking, AI-powered document extraction, and AI-ready extension points.

Key Features

  • CSV / JSON Ingestion

    Reads and cleans raw data from multiple sources

  • PDF Extraction

    AI-powered extraction from PDF documents - recognises tables and structures automatically

  • DOCX Extraction

    Extract structured data from Word documents - works with tables and key-value formats

  • AI-Powered Processing

    Uses OpenAI GPT-4o-mini to intelligently extract and structure data from unstructured documents

  • Schema Inference

    Automatically detects boolean, numeric, date, email, enum types

  • Test-Ready Output

    Generates fixtures for Cypress, Playwright, or generic JSON

  • Deterministic Masking

    Safely hides PII while keeping tests repeatable

  • Header Normalisation

    Trims, removes BOMs, and converts to camelCase

  • Configurable Rules

    Custom mappings, enrichment, and masking options

  • Repeatable Builds

    Deterministic for stable CI runs

See It In Action

Before: Raw Table
NameEmailPhoneAge
John Doejohn@example.com555-012328
Jane Smithjane@example.com555-045632
Bob Wilsonbob@example.com555-078945
Step 1: Structured JSON
[
  {
    "name": "John Doe",
    "email": "john@example.com",
    "phone": "555-0123",
    "age": 28
  },
  {
    "name": "Jane Smith",
    "email": "jane@example.com",
    "phone": "555-0456",
    "age": 32
  },
  {
    "name": "Bob Wilson",
    "email": "bob@example.com",
    "phone": "555-0789",
    "age": 45
  }
]
After: Playwright Fixture
import { test } from '@playwright/test';

export const users = [
  {
    name: "John Doe",
    email: "masked_email_1@example.com",
    phone: "masked_phone_1",
    age: 28
  },
  {
    name: "Jane Smith",
    email: "masked_email_2@example.com",
    phone: "masked_phone_2",
    age: 32
  },
  {
    name: "Bob Wilson",
    email: "masked_email_3@example.com",
    phone: "masked_phone_3",
    age: 45
  }
];

Step-by-Step Instructions

Choose your input format to see specific instructions:

1 Install

npm i -D domtree-fixture-foundry

2 Create Your Input Data

Start with a CSV or JSON file. Example:

mkdir -p data
curl -L -o data/users.csv https://raw.githubusercontent.com/datablist/sample-csv-files/main/files/people/people-100.csv

3 Create Config File

Create domtree.config.json in your project root:

{
  "input": "data/users.csv",
  "frameworks": ["cypress", "playwright", "raw"],
  "outputDir": "dist",
  "datasetName": "users",
  "mask": ["email", "phone"]
}

Key fields:

  • input - Path to your CSV or JSON file
  • frameworks - Output formats: cypress, playwright, or raw JSON
  • outputDir - Folder for generated fixtures
  • datasetName - Base name for output files
  • mask - Fields to anonymise deterministically

4 Generate Fixtures

npx domtree-fixtures generate --config domtree.config.json

Result: dist/cypress/fixtures/users.json, tests/fixtures/users.ts, users.json

How It Works

Ingests CSV or JSON

Reads your raw data files

Infers Schema

Detects data types automatically

Normalises & Masks

Cleans headers, masks PII, fills missing data

Generates Fixtures

Creates test-ready fixture files

Deterministic + repeatable = high-quality test data that behaves the same in local and CI environments.

Test Automation Roadmap

What's coming next for Fixture Builder and Gherkin Generator

Phase Focus Key Features Status
Phase 1 — Foundation Establishing reliable, repeatable fixture generation • CSV + JSON ingestion
• Schema inference (boolean, number, date, enum)
• Deterministic masking for PII
• Header normalisation (camelCase, BOM removal)
• Cypress / Playwright / Raw JSON outputs
• Config-driven CLI
• Published on npm
Complete
Phase 2 — Expansion Broaden supported input types & data flexibility • File adapters for Excel, PDF, DOCX
domtree-fixtures extract command for pre-processing
• Plugin architecture for new file formats
• Improved validation and data consistency checks
Complete
Phase 3 — Intelligence (AI-Assist) Integrating AI for smarter, context-aware data --ai-suggest for LLM-powered schema inference
--ai-enrich for contextual, anonymised data filling
• AI-driven test scenario generation (user journeys, edge cases)
• Human-in-the-loop schema review
Planned
Phase 4 — Experience (Domtree Vision) Enabling collaboration, visibility & learning • Web interface for upload, preview, and export
• Domtree Cloud for reusable datasets
• AI engine that reads PRDs & UX docs to propose test data
• Community template sharing
Future
Continuous Enhancements Refinement, stability & scale • CI/CD integrations (GitHub Actions, Jenkins)
• Config validation and schema typing
• CLI UX improvements
• Privacy & security modes
Future