Intelligent API content governance framework
In one aspect, an example methodology implementing the disclosed techniques includes receiving a new application programming interface (API) specification and extracting one or more keywords from the new API specification. The method also includes identifying, using a trained machine learning (ML) model, one or more existing API specifications that are similar to the new API specification based on the one or more keywords from the new API specification and, responsive to the identification, outputting information regarding the one or more existing API specifications that are similar to the new API specification.
1. A computer implemented method comprising:
receiving a new application programming interface (API) specification, wherein the new API specification corresponds to a new API that is being designed and not yet developed;
extracting one or more keywords from the new API specification;
identifying, using a trained machine learning (ML) model, one or more existing API specifications that are similar to the new API specification based on the one or more keywords from the new API specification, wherein the trained ML model includes a set of feature vectors corresponding to a plurality of existing API specifications; and
responsive to the identification, outputting information regarding the one or more existing API specifications that are similar to the new API specification.
2. The method of claim 1 , wherein the new API specification corresponds to a new API that is being designed.
3. The method of claim 1 , wherein the outputting includes ordering the one or more existing API specifications according to similarity to the new API specification.
4. The method of claim 1 , wherein the one or more extracted keywords are indicative of a context and intent of the new API specification.
5. The method of claim 1 , wherein the identifying one or more existing API specifications further comprises:
generating a feature vector based on the extracted one or more keywords; and
using the feature vector and the trained ML model to predict the one or more existing API specifications that are similar to the new API specification.
6. The method of claim 5 , wherein generating the feature vector includes using Term Frequency-Inverse Document Frequency (TF-IDF).
7. The method of claim 1 , wherein the identifying one or more existing API specifications is based on cosine similarity.
8. The method of claim 1 , wherein the new API specification is received from an API marketplace associated with an organization.
9. The method of claim 1 , wherein the new API specification is received from an API design tool associated with an organization.
10. The method of claim 1 , wherein the new API specification is received from an API runtime associated with an organization.
11. A system comprising:
one or more non-transitory machine-readable mediums configured to store instructions; and
one or more processors configured to execute the instructions stored on the one or more non-transitory machine-readable mediums, wherein execution of the instructions causes the one or more processors to carry out a process comprising:
receiving a new application programming interface (API) specification, wherein the new API specification corresponds to a new API that is being designed and not yet developed;
extracting one or more keywords from the new API specification;
identifying, using a trained machine learning (ML) model, one or more existing API specifications that are similar to the new API specification based on the one or more keywords from the new API specification, wherein the trained ML model includes a set of feature vectors corresponding to a plurality of existing API specifications; and
responsive to the identification, outputting information regarding the one or more existing API specifications that are similar to the new API specification.
12. The system of claim 11 , wherein the outputting includes to order the one or more existing API specifications according to similarity to the new API specification.
13. The system of claim 11 , wherein the one or more extracted keywords are indicative of a context and intent of the new API specification.
14. The system of claim 11 , wherein the identifying one or more existing API specifications further comprises:
generating a feature vector based on the extracted one or more keywords; and
using the feature vector and the trained ML model to predict the one or more existing API specifications that are similar to the new API specification.
15. The system of claim 14 , wherein generating the feature vector includes using Term Frequency-Inverse Document Frequency (TF-IDF).
16. The system of claim 11 , wherein the identifying one or more existing API specifications is based on cosine similarity.
17. The system of claim 11 , wherein the new API specification is received from one of an API marketplace, an API design tool, or an API runtime associated with an organization.
18. A non-transitory computer-readable medium storing program instructions that are executable to:
receive, by a computing device, a new application programming interface (API) specification, wherein the new API specification corresponds to a new API that is being designed and not yet developed;
extract, by the computing device, one or more keywords from the new API specification;
identify, by the computing device using a trained machine learning (ML) model, one or more existing API specifications that are similar to the new API specification based on the one or more keywords from the new API specification, wherein the trained ML model includes a set of feature vectors corresponding to a plurality of existing API specifications; and
responsive to the identification, output, by the computing device, information regarding the one or more existing API specifications that are similar to the new API specification.