Abstract: Present technology is directed to preferred processing and the verification of diagnostic signatures for a plurality of network defect. The disclosed optimization process is based on expressing each Diagnostic Signature as a minimal sum of product Boolean function of associated network commands, followed by ranking of each command reference in the product terms of the Boolean expression as well as each Boolean product terms of the SOP Boolean expressions, and constructing a decision tree based on the provided rankings to thereby determine a minimum set of commands along with an preferred command dispatch sequence for evaluating a Diagnostic Signature. Further aspects include the translation of both the optimization computation (interpretation of network conditions associated with a network defect) and the computed workflow (dispatch of the command) into a series of declarative rules that can be processed by a machine reasoning engine to thereby automate the optimization process.

Abstract: The present technology addresses a need in the art for a closed-loop automation system of a managed network that detects and fixes an issue in the managed network with minimal to no human intervention. The closed-loop automation system employs a domain-independent semantic machine reasoning engine as an underlying engine. After detecting the issue in the managed network, the system searches through a knowledge base to find a match for the detected issue. The knowledge base includes previously collected knowledge from subject matter experts and maintenance teams. The system then proposes a remedial action to a user of the managed network for approval. After approval by the user, the system implements the remedial action.

Abstract: The present technology addresses a need in the art for a closed-loop automation system of a managed network that detects and fixes an issue in the managed network with minimal to no human intervention. The closed-loop automation system employs a domain-independent semantic machine reasoning engine as an underlying engine. After detecting the issue in the managed network, the system searches through a knowledge base to find a match for the detected issue. The knowledge base includes previously collected knowledge from subject matter experts and maintenance teams. The system then proposes a remedial action to a user of the managed network for approval. After approval by the user, the system implements the remedial action.

Abstract: This disclosure describes techniques for diagnostic tools rendering auditable reasoning of underlying rule engines. A method includes a computing system running a software tool executing an iteration of an underlying rule engine of the software tool to compute at least one input fact; sending a command over a communication interface to a fact source and obtaining an output from the fact source over the communication interface; recording the output from the fact source in a diagnostic event construct; recording a reference to the diagnostic event construct in an inference construct; displaying information of the inference construct in a conclusion view user interface; and displaying information of the diagnostic event construct referenced by the inference construct in an expanded view user interface.

Abstract: Present technology is directed to preferred processing and the verification of diagnostic signatures for a plurality of network defect. The disclosed optimization process is based on expressing each Diagnostic Signature as a minimal sum of product Boolean function of associated network commands, followed by ranking of each command reference in the product terms of the Boolean expression as well as each Boolean product terms of the SOP Boolean expressions, and constructing a decision tree based on the provided rankings to thereby determine a minimum set of commands along with an preferred command dispatch sequence for evaluating a Diagnostic Signature. Further aspects include the translation of both the optimization computation (interpretation of network conditions associated with a network defect) and the computed workflow (dispatch of the command) into a series of declarative rules that can be processed by a machine reasoning engine to thereby automate the optimization process.