Abstract: A method and system of matching an application program interface (API) code usage with an API specification are provided. A program having an API code usage is received and its features are extracted therefrom. Features from meta data of a plurality of API specifications are extracted. For each API specification of the plurality of API specifications, a match probability with the API code usage is determined. An API specification having a highest probability is determined. The API code usage is matched with the API specification having the highest probability.

Abstract: A computer-implemented method and system for authenticating API is provided. An API invocation request associated with a user is received. An API operation and the shareable API key includes validating API key credentials of the shareable API key associated with the API invocation request. There is an additional validation of user credentials of the user associated with the API invocation request. It is determined whether the user having the validated user credentials is authorized to use the shareable API key to invoke the API operation. The API operation is executed in response to determining the user having validated user credentials is authorized to use the shareable API key to invoke the API operation. The authentication integrates validation of the user and the shareable API key, and determines whether a user is a subscriber of a multi-tenant subscription service.

Abstract: Techniques for autonomously generating a code usage summary associated with a web application programming interface request are provided. In one example, a computer-implemented method can comprise evaluating, by a system operatively coupled to a processor, data from a data repository, wherein the evaluating is based on a defined machine learning process. Also, the computer-implemented method can comprise generating, by the system, a usage summary of the data, wherein the usage summary is based on a statistic derived from a web application programming interface request, and the web application programming interface request is associated with the data.

Abstract: A method and system of matching an application program interface (API) code usage with an API specification are provided. A program having an API code usage is received and its features are extracted therefrom. Features from meta data of a plurality of API specifications are extracted. For each API specification of the plurality of API specifications, a match probability with the API code usage is determined. An API specification having a highest probability is determined. The API code usage is matched with the API specification having the highest probability.

Abstract: A computer-implemented method and system for authenticating API is provided. An API invocation request associated with a user is received. An API operation and the shareable API key includes validating API key credentials of the shareable API key associated with the API invocation request. There is an additional validation of user credentials of the user associated with the API invocation request. It is determined whether the user having the validated user credentials is authorized to use the shareable API key to invoke the API operation. The API operation is executed in response to determining the user having validated user credentials is authorized to use the shareable API key to invoke the API operation. The authentication integrates validation of the user and the shareable API key, and determines whether a user is a subscriber of a multi-tenant subscription service.

Abstract: Techniques for autonomously generating a code usage summary associated with a web application programming interface request are provided. In one example, a computer-implemented method can comprise evaluating, by a system operatively coupled to a processor, data from a data repository, wherein the evaluating is based on a defined machine learning process. Also, the computer-implemented method can comprise generating, by the system, a usage summary of the data, wherein the usage summary is based on a statistic derived from a web application programming interface request, and the web application programming interface request is associated with the data.

Abstract: Techniques for autonomously generating a code usage summary associated with a web application programming interface request are provided. In one example, a computer-implemented method can comprise evaluating, by a system operatively coupled to a processor, data from a data repository, wherein the evaluating is based on a defined machine learning process. Also, the computer-implemented method can comprise generating, by the system, a usage summary of the data, wherein the usage summary is based on a statistic derived from a web application programming interface request, and the web application programming interface request is associated with the data.

Abstract: Techniques for autonomously generating a code usage summary associated with a web application programming interface request are provided. In one example, a computer-implemented method can comprise evaluating, by a system operatively coupled to a processor, data from a data repository, wherein the evaluating is based on a defined machine learning process. Also, the computer-implemented method can comprise generating, by the system, a usage summary of the data, wherein the usage summary is based on a statistic derived from a web application programming interface request, and the web application programming interface request is associated with the data.

Abstract: Techniques for autonomously generating a code usage summary associated with a web application programming interface request are provided. In one example, a computer-implemented method can comprise evaluating, by a system operatively coupled to a processor, data from a data repository, wherein the evaluating is based on a defined machine learning process. Also, the computer-implemented method can comprise generating, by the system, a usage summary of the data, wherein the usage summary is based on a statistic derived from a web application programming interface request, and the web application programming interface request is associated with the data.

Abstract: Techniques for autonomously generating a code usage summary associated with a web application programming interface request are provided. In one example, a computer-implemented method can comprise evaluating, by a system operatively coupled to a processor, data from a data repository, wherein the evaluating is based on a defined machine learning process. Also, the computer-implemented method can comprise generating, by the system, a usage summary of the data, wherein the usage summary is based on a statistic derived from a web application programming interface request, and the web application programming interface request is associated with the data.

Abstract: A system implementing a situation-oriented directory for retrieving a stakeholder identification includes a memory storing a relational database corresponding to the situation-oriented directory including a plurality of attribute-value combinations and a plurality of stakeholder identifications, wherein the plurality of attribute-value combinations are mapped to the plurality of stakeholder identifications such that for each attribute-value combination exactly one stakeholder is mapped, and a processor in communication with the memory for receiving a query and retrieving the stakeholder identification from among the plurality of stakeholder identifications based on the attribute-value combinations.

Abstract: A system implementing a situation-oriented directory for retrieving a stakeholder identification includes a memory storing a relational database corresponding to the situation-oriented directory including a plurality of attribute-value combinations and a plurality of stakeholder identifications, wherein the plurality of attribute-value combinations are mapped to the plurality of stakeholder identifications such that for each attribute-value combination exactly one stakeholder is mapped, and a processor in communication with the memory for receiving a query and retrieving the stakeholder identification from among the plurality of stakeholder identifications based on the attribute-value combinations.

Abstract: A method for automating the deployment and lifecycle management of an integration solution by using a deployment solution template to gather deployment information, where the integration solution combines components developed separately or on different platforms. The deployment information gathered includes the computing environment topology into which the integration solution is being deployed, as well as the resource requirements and non-functional requirements of the integration solution and its components. The method provides computer implemented models for analyzing the gathered deployment information, and identifying and optimizing deployment options. Choices for selection among identified and optimized options based on non-functional requirements of the integration solution may be displayed to a user of the deployment method.