US 2019/0095318 A1 · TEST-ASSISTED APPLICATION PROGRAMMING INTERFACE (API) LEARNING

Abstract

A method of test-assisted application programming interface (API) learning includes generating a machine-readable API specification (API spec). The API spec is based on application of machine learning and regular expression processes to an API documentation. The method includes comparing the API spec to other API specifications. Based on the comparison, the method includes identifying a set of similar API specifications. The method includes generating API test inputs based on the set of similar API specifications and the API spec. The method includes calling a native API system using a first API test input of the API test inputs. The method includes receiving a response indicative of whether the first API test input successfully interacts with the native API system. Based on the response, the method includes generating a feedback indicative of an alteration to the API test inputs or to the machine learning or the regular expression processes.

Claims20

Dependent claims

A method of test-assisted application programming interface (API) learning, the method comprising:

generating a machine-readable API specification based on application of a machine learning process and a regular expression process to an API documentation;
comparing the generated machine-readable API specification to other machine-readable API specifications;
based on a comparison between the generated machine-readable API specification and the other machine-readable API specifications, identifying a set of similar API specifications;
generating API test inputs that include API endpoints based on the set of similar API specifications and the generated machine-readable API specification;
calling a native API system using a first API test input of the generated API test inputs;
receiving a response from the native API system, the response being indicative of whether the first API test input successfully interacts with the native API system;
and
based on the response from the native API system, generating a feedback that is indicative of an alteration to one or more or a combination of the machine learning process, the regular expression process, and the API test inputs.

5 more elements

A non-transitory computer-readable medium having encoded therein programming code executable by one or more processors to perform or control performance of operations comprising:

generating a machine-readable API specification based on application of a machine learning process and a regular expression process to an API documentation;
comparing the generated machine-readable API specification to other machine-readable API specifications;
based on a comparison between the generated machine-readable API specification and the other machine-readable API specifications, identifying a set of similar API specifications;
generating API test inputs that include API endpoints based on the set of similar API specifications and the generated machine-readable API specification;
calling a native API system using a first API test input of the generated API test inputs;
receiving a response from the native API system, the response being indicative of whether the first API test input successfully interacts with the native API system;
and
based on the response from the native API system, generating a feedback that is indicative of an alteration to one or more or a combination of the machine learning process, the regular expression process, and the API test inputs.

5 more elements

Dependencies are inferred from the claim text.

Test-assisted application programming interface (api) learning

Life of this patent

Test-assisted application programming interface (api) learning

Life of this patent

Abstract

Claims20