Systems and methods for generating and executing a test case plan for a software product

1. A method, comprising:

receiving, by a device, a selection of a software product and test input data identifying inputs of a test case for the software product;

receiving, by the device, the software product based on the selection of the software product;

generating, by the device, test data for the test case based on the test input data and the software product,

wherein the test data includes information to be used to test the software product;

processing, by the device, the test data and the software product, with a machine learning model, to generate a test case plan that includes the test data and test steps,

wherein the machine learning model is trained based on historical test data to output test case plans that include the historical test data and steps corresponding to the historical test data;

generating, by the device, test scripts for the test case plan based on the software product;

causing, automatically by the device, the software product to execute the test scripts to generate test results; and

performing, by the device, one or more actions based on the test results.

2. The method of claim 1 , wherein generating the test data for the test case comprises:

determining a functionality associated with the software product;

generating a test case flow based on the functionality associated with the software product; and

generating the test data for the test case based on the test case flow.

3. The method of claim 1 , wherein performing the one or more actions comprises:

removing a portion of the software product based on the test results;

generating a new portion for the software product based on the test results; and

replacing the portion of the software product with the new portion.

4. The method of claim 1 , wherein performing the one or more actions comprises:

determining a correction to the software product based on the test results; and

implementing the correction to the software product.

5. The method of claim 1 , wherein performing the one or more actions comprises:

modifying the software product based on the test results and to generate a modified software product; and

retesting the modified software product.

6. The method of claim 1 , wherein receiving the selection of the software product and the test input data identifying the inputs of the test case for the software product comprises:

providing a chat interface to a user device;

conducting a chat with a user of the user device via the chat interface; and

receiving the selection of the software product and the test input data based on conducting the chat with the user of the user device.

7. The method of claim 1 , wherein generating the test data for the test case based on the test input data and the software product comprises:

providing the test input data and the software product to an application programming interface development platform; and

receiving the test data for the test case from the application programming interface development platform.

8. A device, comprising:

one or more processors configured to:

receive a selection of a software product and test input data identifying inputs of a test case for the software product;

receive the software product based on the selection of the software product;

provide the test input data and the software product to an application programming interface development platform;

receive test data for the test case from the application programming interface development platform,

wherein the test data includes information to be used to test the software product;

process the test data and the software product, with a machine learning model, to generate a test case plan that includes the test data and test steps,

wherein the machine learning model is trained based on historical test data to output test case plans that include the historical test data and steps corresponding to the historical test data;

generate test scripts for the test case plan based on the software product;

cause, automatically, the software product to execute the test scripts to generate test results; and

perform one or more actions based on the test results.

9. The device of claim 8 , wherein the machine learning model includes a test case model associated with a test management tool.

10. The device of claim 8 , wherein the one or more processors, to generate the test scripts for the test case plan based on the software product, are configured to:

generate the test scripts to be executable by an end-to-end testing framework and a behavior-driven development testing framework.

11. The device of claim 8 , wherein the one or more processors, to cause the software product to execute the test scripts to generate the test results, are configured to:

cause the software product to execute the test scripts, via an end-to-end testing framework and a behavior-driven development testing framework, to generate the test results.

12. The device of claim 8 , wherein the one or more processors are further configured to:

provide the test case plan for display to a user device; and

receive, from the user device, information indicating approval of the test case plan prior to generating the test scripts for the test case plan.

13. The device of claim 8 , wherein the one or more processors, to cause the software product to execute the test scripts to generate the test results, are configured to:

cause the software product to execute the test scripts, locally or remotely, to generate the test results.

14. The device of claim 8 , wherein the one or more processors, to generate the test data for the test case based on the test input data and the software product, are configured to:

analyze a test case flow, identified in the test input data, for the test case; and

generate the test data for the test case based on analyzing the test case flow.

15. A non-transitory computer-readable medium storing a set of instructions, the set of instructions comprising:

one or more instructions that, when executed by one or more processors of a device, cause the device to:

receive a selection of a software product and test input data identifying inputs of a test case for the software product;

receive the software product based on the selection of the software product;

generate test data for the test case based on the test input data and the software product,

wherein the test data includes information to be used to test the software product;

process the test data and the software product, with a machine learning model, to generate a test case plan that includes the test data and test steps,

wherein the machine learning model is trained based on historical test data to output test case plans that include the historical test data and steps corresponding to the historical test data;

generate test scripts for the test case plan based on the software product,

wherein the test scripts are to be executable by an end-to-end testing framework and a behavior-driven development testing framework;

cause, automatically, the software product to execute the test scripts, via the end-to-end testing framework and the behavior-driven development testing framework, to generate test results; and

perform one or more actions based on the test results.

16. The non-transitory computer-readable medium of claim 15 , wherein the one or more instructions, that cause the device to perform the one or more actions, cause the device to one or more of:

generate a notification based on the test results;

provide information about the test results for display;

retrain the machine learning model based on the test results;

remove and replace a portion of the software product based on the test results;

determine and implement a correction to the software product based on the test results; or

modify the software product based on the test results.

17. The non-transitory computer-readable medium of claim 15 , wherein the one or more instructions, that cause the device to receive the selection of the software product and the test input data identifying the inputs of the test case for the software product, cause the device to:

provide a chat interface to a user device;

conduct a chat with a user of the user device via the chat interface; and

receive the selection of the software product and the test input data based on conducting the chat with the user of the user device.

18. The non-transitory computer-readable medium of claim 15 , wherein the one or more instructions, that cause the device to generate the test data for the test case based on the test input data and the software product, cause the device to:

provide the test input data and the software product to an application programming interface development platform; and

receive the test data for the test case from the application programming interface development platform.

19. The non-transitory computer-readable medium of claim 15 , wherein the one or more instructions further cause the device to:

provide the test case plan for display to a user device; and

receive, from the user device, information indicating approval of the test case plan prior to generating the test scripts for the test case plan.

20. The non-transitory computer-readable medium of claim 15 , wherein the one or more instructions, that cause the device to generate the test data for the test case based on the test input data and the software product, cause the device to:

analyze a test case flow, identified in the test input data, for the test case; and

generate the test data for the test case based on analyzing the test case flow.