In modern e-commerce systems, faceted search is an important function that allows consumers to quickly sort through a massive list of products to find the item that best meets their needs. Ensuring the user experience is fast, efficient and accurate can mean the difference between a successful transaction and a frustrated shopper.


That’s why testing the code for a faceted search engine is so important and generating the right test data to represent all permutations of product data for testing all possible edge conditions is even more important.

In this solutions video, we illustrate how GenRocket can quickly and easily generate an infinite array of images and facet data based on a defined test scenario. By defining a product category (e.g., men’s jeans) and a set of facets with the category (e.g., color, fit, style and waist size), GenRocket can generate all possible permutations of images and facet data for that product category.

GenRocket allows testers to quickly and easily generate:
  • Thousands to millions of generic images
  • Permutations of images and facet data with predictable results
  • Thousands of predictable and non-predictable edge cases
  • Small volumes of data to unit test algorithms
  • Huge amounts of data to conduct performance and load testing
GenRocket can easily run continuous automated regression tests via a CI/CD pipeline