Auto-generation of API documentation via implementation-neutral analysis of API traffic

1. A method comprising:

receiving an application programming interface (API) request and one or more API responses, wherein the API request and the one or more API responses are generated using the API;

determining at least one interaction parameter based on the API request, the one or more API responses, or both, the interaction parameter corresponds to data included in the API request, at least one of the API responses, or both;

using a validation dataset to train a machine learning model, the validation dataset including feedback related to the accuracy of automatically generated API documentation;

using statistics generated by the machine learning model to analyze the at least one interaction parameter corresponding to the API; and

generating the automatically generated API documentation based on the statistics and the at least one interaction parameter, wherein the API documentation includes descriptions of the API request, the one or more API responses, or both, and a description of the interaction parameter.

2. The method of claim 1 , wherein the validation dataset comprises feedback from at least one selected from a group comprising a user, a document generator, and storage device.

3. The method of claim 1 , wherein the API request includes at least one request parameter and the one or more API responses includes at least one response parameter.

4. The method of claim 3 , wherein the API request includes at least one optional request parameter.

5. The method of claim 3 , wherein the at least one response parameter includes a response code, response message, and response data.

6. The method of claim 1 , further comprising:

receiving audit documentation;

comparing the audit documentation with the automatically generated API documentation; and

responsive to a determining of a mismatch between the audit documentation and the automatically generated API documentation, updating the audit documentation.

7. The method of claim 1 , further comprising triggering an automated workflow based on the automatically generated API documentation.

8. A system comprising:

a gateway for receiving application requests and one or more application responses;

an analyzer for:

receiving an application programming interface (API) request and one or more API responses, wherein the API request and the one or more API responses are generated using the API;

determining at least one interaction parameter based on the API request, the one or more API responses, or both, the interaction parameter corresponds to data included in the API request, at least one of the API responses, or both;

using a validation dataset to train a machine learning model, the validation dataset including feedback related to the accuracy of automatically generated API documentation;

using statistics generated by the machine learning model to analyze the at least one interaction parameter corresponding to the API; and

generating the automatically generated API documentation based on the statistics and the at least one interaction parameter, wherein the API documentation documents includes descriptions of the API request, the one or more API responses, or both, and a description of the interaction parameter.

9. The system of claim 8 , wherein the validation dataset comprises feedback from at least one selected from a group comprising a user, a document generator, and storage device.

10. The system of claim 8 , wherein the API request includes at least one request parameter and the one or more API responses includes at least one response parameter.

11. The system of claim 10 , wherein the API request includes at least one optional request parameter.

12. The system of claim 10 , wherein the at least one response parameter includes a response code, response message, and response data.

13. The system of claim 8 , further comprising the analyzer:

receiving audit documentation;

comparing the audit documentation with the automatically generated API documentation; and

responsive to a determining of a mismatch between the audit documentation and the automatically generated API documentation, updating the audit documentation.

14. The system of claim 8 , further comprising the analyzer triggering an automated workflow based on the automatically generated API documentation.

15. An apparatus comprising:

an analyzer for:

receiving an application programming interface (API) request and one or more API responses from a gateway, wherein the API request and the one or more API responses are generated using the API;

determining at least one interaction parameter based on the API request, the one or more API responses, or both, the interaction parameter corresponds to data included in the API request, at least one of the API responses, or both; and

means for automatically generating API documentation that describes the API request, at least one of the one or more API responses, and the interaction parameter;

wherein the means for automatically generating the API documentation comprises training a machine learning model that generates the API documentation with a validation dataset.

16. The apparatus of claim 15 , wherein the validation dataset comprises feedback from at least one selected from a group comprising a user, a document generator, and storage device.

17. The apparatus of claim 15 , wherein the API request includes at least one request parameter and the one or more API responses includes at least one response parameter.

18. The apparatus of claim 17 , wherein the API request includes at least one optional request parameter.

19. The apparatus of claim 17 , wherein the at least one response parameter includes a response code, response message, and response data.

20. The apparatus of claim 15 , further comprising the analyzer:

receiving audit documentation;

comparing the audit documentation with the automatically generated API documentation; and

responsive to a determining of a mismatch between the audit documentation and the automatically generated API documentation, updating the audit documentation.