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Integrate collection run / test flow execution with external CI/CD pipelines (Azure, Jenkins, AWS) to validate APIs during build/deploy. Detailed Requirements: Provide API endpoints for triggering test runs. Return pass/fail status and execution summary. Trigger email notifications post the run. Support deployment on multi-cloud (Azure, AWS).

Role-Based Shared and Exclusive APIs Some APIs are common across roles (shared login, setup), while others are role-specific. Shared APIs should run globally for all users. Role-specific APIs should execute only for intended roles. Users should not have to duplicate shared APIs in their personal flows. Test execution should have this segregation and isolation.

Support automated execution of test flows based on defined schedules with post-run notifications to stakeholders via email. Requirement Create schedules for test execution. Run the test cases based on the schedule. Assign recipients for result notifications. Generate execution summary and error details via email.

Automatically generate test cases covering both valid and invalid input scenarios based on a set of configurable rules. Requirement Provide AI or rules-based engine to create test cases. Define rule sets for invalid values (empty, null, wrong type, boundary values). Generate a matrix of combinations. Allow review and customization before execution. Execute tests and collect coverage insights.

Allow APIs to run iteratively using structured external data sources like Excel, CSV, or JSON. Requirement Upload files with row-wise test data. Execute the APIs row-wise using input sets. Enable output chaining across requests within a single iteration. Visualize results for each iteration.

Enhance validation capabilities by allowing assertions on response content, beyond simple status code checks. Requirement Support response body assertions. Include validation for value matching, data presence, type checking and other cases. Support custom expression evaluation. Provide logs with detailed assertion success/failure cases.

Provide a flexible system to input, manage, and reuse mock data sets with multiple data combinations to simulate varied scenarios. Requirement Upload JSON or CSV files or use AI containing containing multiple combinations. View the datasets. Assign mock sets to specific API requests in collection. Preview mock data. Simulate valid and invalid cases using mock sets. Enable users to switch mock sets dynamically during testing.

Enable Sparrow to intelligently identify recurring parameters across multiple APIs and promote them as environment or global variables. This feature should simplify variable management and promote reuse, especially for Collections and test flows involving multiple APIs. Requirement Automatically scan collection parameters for repeated keys and values. Identify potential candidates for global or environment variables using AI. Allow users to review, edit, approve, and convert suggestions into environment/global variables. Enable batch conversion of parameters from requests.