Abstract: A framework provides a detailed explanation regarding specific aspects of a (complex) calculation produced by an application (e.g., an analytical application). An explainability engine receives a request for explanation of the calculation. The explainability engine traverses homogenous data clusters according to the request, in order to produce a final path. The final path is used to select and then populate a template comprising explanation note(s). The outcome (comprising the final path and the template) is processed with a ruleset according to a covariance (COV) function in order to provide a first intermediate outcome. The first intermediate result is then processed with a second input according to a correlation (COR) function to provide a second intermediate outcome. The second intermediate result is processed according to a challenge function to provide a challenged outcome, and feedback (e.g., reward or penalization) to the ruleset. The challenged outcome provides detailed explanation to the user.

Abstract: Explanation of an analytical result, is afforded to a user by a populating a template with the result of searching homogenous clusters. During a preliminary phase, configuration changes are asynchronously fetched from services of an analytic application, and then grouped into homogenous clusters. Then, during a synchronous phase, a request to explain a particular analytical result is received from the application. Based upon content of the explanation request, the clusters are traversed in order to create a final path. A template comprising an explanation note with blanks, is selected from a template store and then populated with data from the final path. The populated template and the final path are stored together as an outcome. The outcome is then processed according to a challenge function, with the resulting challenged outcome communicated back to the application and afforded to provide the user with an explanation of the analytical result.