The Problem

Data-driven testing in Katalon Studio is inherently sequential. A test suite bound to a data source with 500 rows executes each row one after another in a single browser instance. For fast-running test cases this might be acceptable, but when each iteration involves navigating multi-step workflows, waiting for page loads, or interacting with complex UIs, total execution time scales linearly with data volume. A suite that takes 30 seconds per row and has 500 rows runs for over four hours.

Katalon's built-in test suite collections support parallel execution, but only at the suite level — you can run different suites in parallel, not different slices of the same data-driven suite. Manually creating partitioned copies of a suite, each targeting a specific row range, is tedious, error-prone, and a maintenance headache every time the data source changes.

How Data Parallelism Solves It

This plugin automates the entire partitioning workflow. Given a source test suite and a desired partition count, it:

1. Parses the source suite XML to extract test case links, data bindings, and iteration configuration.
2. Resolves row counts by calling Katalon's findTestData() API, which works with any data source type — CSV, Excel, database queries, or Katalon's internal data format.
3. Calculates balanced row ranges across partitions. If 102 rows are split into 5 partitions, the distribution is 21, 21, 20, 20, 20 — earlier partitions absorb the remainder so every partition is as close to equal as possible.
4. Generates partition suite XML files, each identical to the source but with RANGE iteration type and a specific row range. Every generated suite and data link gets a fresh UUID to avoid collisions.
5. Generates a test suite collection with PARALLEL execution mode and maxConcurrentInstances set to the partition count, configured with your specified browser and execution profile.
6. Writes companion .groovy files required by Katalon's project structure for each generated suite.

The result: a single keyword call transforms one slow, sequential suite into N parallel suites ready to execute concurrently.

Usage

The plugin exposes two keywords:

createParallelSuites accepts:

• sourceTestSuiteId (required) — the path to your data-bound suite, e.g., "Test Suites/Print Names - SQLite"

• numberOfPartitions (required) — how many slices to create

• outputFolder — where to write generated files (defaults to a Generated subfolder alongside the source)

• collectionName — name for the generated collection (auto-derived from the source suite name if omitted)

• browser — browser ID for all partitions (defaults to "Chrome")

• profileName — execution profile (defaults to "default")

  cleanupParallelSuites removes all generated .ts and .groovy files from a specified folder, cleaning up after a run.

Demo Project

A companion project (data-parallelism-sample) demonstrates the full workflow with four template test suites — one each for CSV, Excel, SQLite, and internal data sources — all bound to the same ~100-row sample user dataset. Utility test cases show how to invoke the plugin keywords with environment variable overrides, making the partition count and source suite configurable for CI pipelines.

The demo also includes TestMu HyperExecute integration configuration showing how to scale beyond local parallel execution to cloud-based distributed runs, where each worker independently generates and executes its own partition subset.