Impact analysis based on API functional testing

1. A computer-implemented method, comprising:

receiving, by one or more computing devices, a functional test suite corresponding to an application programming interface (API);

generating, by the one or more computing devices, a knowledge graph of information by combining a test-result graph of information based on a result of execution of a test of the functional test suite with a metadata-linked graph of information based on metadata corresponding to the API, wherein the metadata-linked graph comprises a plurality of metadata-linked subgraphs associated with a respective runtime identifier indicating a time stamp of when a respective test of the functional test suite is executed; and

generating, by the one or more computing devices, an alert message corresponding to the function test suite based on the knowledge graph of information, wherein the generating the alert message comprises identifying a knowledge subgraph corresponding to a failed test of the functional test suite, and determining a classification of the alert message using a machine-learning algorithm based on the knowledge graph.

2. The computer-implemented method of claim 1 , wherein the test-result graph comprises a test-result subgraph corresponding to the result of execution of the test of the functional test suite on an endpoint of the API.

3. The computer-implemented method of claim 1 , wherein the metadata-linked graph comprises the metadata-linked subgraph corresponding to a specification of the API associated with a specification identifier and a version identifier.

4. The computer-implemented method of claim 3 , wherein the metadata-linked subgraph is associated with the runtime identifier.

5. The computer-implemented method of claim 1 , wherein the generating the knowledge graph of information further comprises:

receiving an updated specification of the API; and

generating a new metadata-linked subgraph corresponding to the updated specification of the API.

6. A system, comprising:

a memory; and

at least one processor coupled to the memory and configured to:

receive a functional test suite corresponding to an application programming interface (API);

generate a knowledge graph of information by combining a test result graph of information based on a result of execution of a test in the functional test suite with a metadata linked graph of information based on metadata corresponding to the API, wherein the metadata-linked graph comprises a plurality of metadata-linked subgraphs associated with a respective runtime identifier indicating a time stamp of when a respective test of the functional test suite is executed; and

generate an alert message corresponding to the function test suite based on the knowledge graph of information by identifying a knowledge subgraph corresponding to a failed test of the functional test suite, and determining a classification of the alert message using a machine-learning algorithm based on the knowledge graph.

7. The system of claim 6 , wherein the test-result graph comprises a test-result subgraph corresponding to the result of execution of the test of the functional test suite on an endpoint of the API.

8. The system of claim 6 , wherein the metadata-linked graph comprises the metadata-linked subgraph corresponding to a specification of the API associated with a specification identifier and a version identifier.

9. The system of claim 8 , wherein the metadata-linked subgraph is associated with the runtime identifier.

10. The system of claim 6 , wherein to generate the knowledge graph of information, the at least one processor is further configured to:

receive an updated specification of the API; and

generate a new metadata-linked subgraph corresponding to the updated specification of the API.

11. A non-transitory computer-readable medium (CRM) having instructions stored thereon that, when executed by at least one computing device, causes the at least one computing device to perform operations comprising:

receiving a functional test suite corresponding to an application programming interface (API);

generating a knowledge graph of information by combining a test result graph of information based on a result of execution of a test in the functional test suite with a metadata linked graph of information based on metadata corresponding to the API, wherein the metadata-linked graph comprises a plurality of metadata-linked subgraphs associated with a respective runtime identifier indicating a time stamp of when a respective test of the functional test suite is executed; and

generating an alert message corresponding to the function test suite based on the knowledge graph of information, wherein the generating the alert message comprises identifying a knowledge subgraph corresponding to a failed test of the functional test suite, and determining a classification of the alert message using a machine-learning algorithm based on the knowledge graph.

12. The non-transitory CRM of claim 11 , wherein the test-result graph comprises a test-result subgraph corresponding to the result of execution of the test of the functional test suite on an endpoint of the API.

13. The non-transitory CRM of claim 11 , wherein the metadata-linked graph comprises the metadata-linked subgraph corresponding to a specification of the API associated with a specification identifier and a version identifier.

14. The non-transitory CRM of claim 13 , wherein the metadata-linked subgraph is associated with the runtime identifier.