Abstract: Systems, computer program products, and methods are described herein for automatically correlating data of unstructured datasets from disparate disclosure sources. The present disclosure is configured to identify application metadata associated with at least one application; access at least one database comprising a plurality of unstructured datasets; input the application metadata and the plurality of unstructured datasets to a graph synthesizer; generate, by the graph synthesizer, a correlation score between the application metadata and the plurality of unstructured datasets; and determine, based on the correlation score, the at least one application is highly correlated to at least one unstructured dataset of the plurality of unstructured datasets or is low correlated to the plurality of unstructured datasets.

Abstract: Embodiments of the invention are directed to a system, method, or computer program product for dynamic latency reduction through edge computation based on a multi-layered mechanism. In this regard, the invention is structured for proactive de-centralized monitoring and resolution of network issue events and cross-pollination of resolutions of network issue events between network components and dynamic reallocation of technology resources therebetween for load balancing. In some embodiments, the invention comprises an entity communication network comprising a plurality of network device groups, one or more edge nodes, and a central server system. The invention determines, via an edge node, a first resolution vector for a first network issue event. The invention is configured to implement, via a micro edge adaptor of a first component system, the first resolution vector at a component system.

Abstract: A software defect detection tool determines a modification in a software code at a first time and analyzes an execution of the software code to detect a performance issue at a second time. The software defect detection tool detects a defect in the software code by a comparison of the first time and a second time. A software defect analysis tool generates a cause/category combination for a software code defect. The software defect analysis tool determines whether the cause/category combination is an approved combination and whether the software code defect is a false positive. The software defect analysis tool generates a corrective action plan indicating measures to implement to reduce software defects.

Abstract: A software defect detection tool determines a modification in a software code at a first time and analyzes an execution of the software code to detect a performance issue at a second time. The software defect detection tool detects a defect in the software code by a comparison of the first time and a second time. A software defect analysis tool generates a cause/category combination for a software code defect. The software defect analysis tool determines whether the cause/category combination is an approved combination and whether the software code defect is a false positive. The software defect analysis tool generates a corrective action plan indicating measures to implement to reduce software defects.