Search Results for "data field mapper"

...And you can mix API and UI test-automation within the same test script. A Java API also exists for those who prefer to programmatically integrate Karate’s rich automation and data-assertion capabilities. It is worth pointing out that JSON is a ‘first class citizen’ of the syntax such that you can express payload and expected data without having to use double-quotes and without having to enclose JSON field names in quotes.

The RecordEditor is a Data File editor for Flat Files (delimited and fixed field position). It supports Unix / PC / Legacy (e.g. Mainframe) file formats, both Text and binary files. The Editor uses a Record-Layout description to format the files. This is ideal for Fixed width (Text or Binary) files, Cobol Data Files, Mainframe files and complicated Csv files.

Mastek has successfully developed a highly configurable Hybrid Automation framework: “Swift” using Selenium tool that offers quick turnaround for Automation Suite Implementation with support of Keyword & Data Driven framework approach. The Automation regression suite can be created or modified using tester friendly keywords for modules, screens, and verifications, thereby ensuring a more effective and efficient Test automation process and better ROI through the complete application life...

Hyenae.Net is an advanced data generator and the successor of Hyenae. Hyenae.Net allows you to set up and dispatch custom data streams and can be used to simulate almost any network or data protocol including checksums and data field randomizaion.

...It acts as a proxy that fans out real production requests to three backends: the current “primary,” a “candidate” (new build), and a “shadow” baseline, then compares responses to detect behavioral differences. By using live traffic rather than synthetic tests, Diffy surfaces edge cases and data-dependent discrepancies that unit tests often miss. It provides mechanisms to normalize noise (timestamps, IDs, ordering) so diffs reflect meaningful regressions rather than incidental variance. Results are aggregated and visualized so teams can triage by endpoint, response field, or error type, turning release validation into a data-driven process. ...

...DataWoo is meant to be a research and development platform that can be extended into just about any enterprise-level web application. The architecture will be developed in three phases: 1. Basic Spring Architecture: Provides all the basic components needed to field an enterprise-level application. 2. Programmatic Security Model: Incorporates the components needed to dynamically assign users to user roles and user roles to profiles. 3. Meta-Driven Architecture: Use meta-data to dynamically configure 80%-90% of the application using the concepts exemplified in the Compiere open source project.