Parasoft vs. IRI RowGen

Parasoft aims to deliver automated testing tools and knowledge that enable companies to accelerate the launch of secure and dependable software. Parasoft C/C++test serves as a comprehensive test automation platform for C and C++, offering capabilities for static analysis, unit testing, and structural code coverage, thereby assisting organizations in meeting stringent industry standards for functional safety and security in embedded software applications. This robust solution not only enhances code quality but also streamlines the development process, ensuring that software is both effective and compliant with necessary regulations.

IRI RowGen creates billions of safe and intelligent rows of test data tailored for various targets such as databases, flat files, and formatted reports by leveraging metadata instead of actual data. This powerful tool synthesizes and fills databases with accurate relational test data that mirrors the characteristics of your production data. By utilizing existing metadata or generating it dynamically, RowGen can either randomly create structurally and referentially accurate test data or select it from real datasets. Moreover, it offers the flexibility to customize data formats, volumes, ranges, distributions, and additional properties either on the fly or through reusable rules, which aids in achieving key objectives like application testing and subsetting. Powered by the IRI CoSort engine, RowGen ensures the fastest generation, transformation, and bulk loading of large test datasets available in the market. Developed by experts in data modeling, integration, and processing, RowGen is designed to efficiently produce compliant test sets in both production-ready and customized formats. With RowGen, you can easily generate and provision synthetic test data that is safe and intelligent for various purposes, including DevOps, database validations, data visualizations, and data warehousing prototypes, all without needing access to production data. This capability not only enhances testing efficiency but also significantly reduces the risks associated with using sensitive production data.