Abstract: As described herein, a system, method, and computer program are provided for using metric valuations in anomaly scoring. In use, a score calculated for a metric used for anomaly detection is identified. Additionally, the score is weighted, based on a valuation defined for the metric, to form a weighted score. Further, at least one action is caused to be performed, based on the weighted score.

Abstract: As described herein, a system, method, and computer program are provided for anomaly detection in time-series data with mixed seasonality. In use, time-series data of a mixed seasonality type is received. Additionally, the time-series data is segmented, by a defined unit of time, to form a plurality of time-series data segments. Further, the plurality of time-series data segments are processed to determine one or more patterns across the plurality of time-series data segments. Still yet, the one or more patterns are stored and used to perform pattern matching for an input time-series.

Abstract: As described herein, a machine learning system, method, and computer program provide marketing segmentation of residential spaces. In use, network usage data is collected from each residential network router of a plurality of residential network routers operating in a different residential space of a plurality of residential spaces. Additionally, the network usage data is processed by a machine learning algorithm to segment the plurality of residential spaces into a plurality of segments. Further, the plurality of segments are output.

Abstract: As described herein, a machine learning system, method, and computer program are provided for inferring user presence in a residential space. In use, network usage data is collected from a residential network router operating in a residential space. Additionally, the network usage data is processed by a machine learning algorithm to infer whether a user is present in the residential space. Further, the inference is output for performing one or more related actions.

Abstract: As described herein, a system, method, and computer program are provided for generating insights from home network router data. In use, network usage/connection data is collected from a home network router operating in a residential space. Additionally, the network usage/connection data is processed to generate insights for the network usage/connection data. Further, the insights are output for display to one or more users.

Abstract: As described herein, a system, method, and computer program are provided for identifying foreign keys between distinct tables based on a statistical analysis of table values. In use, a plurality of candidate field combinations are determined between a first table and a second table. A statistical analysis of values stored in fields of each candidate field combination of the plurality of the candidate field combinations is performed. Foreign keys between the first table and the second table are identified, based on a result of the statistical analysis.

Abstract: A system, method, and computer program product are provided for automated resolution of free-text incidents, based on machine learning. In operation, a system receives incident information from at least one IT service management (ITSM) system. The system reads the incident information including free text and classifies an incident associated with the incident information to at least one automation flow. The system generates robotic process automation (RPA) compatible information from the incident information by parsing parameters associated with the incident from text into required fields based on the at least one automation flow. Further, the system sends the generated RPA compatible information to the at least one ITSM system or at least one RPA system.

Abstract: As described herein, a machine learning system, method, and computer program are provided for inferring user presence in a residential space. In use, network usage data is collected from a residential network router operating in a residential space. Additionally, the network usage data is processed by a machine learning algorithm to infer whether a user is present in the residential space. Further, the inference is output for performing one or more related actions.

Abstract: As described herein, a machine learning system, method, and computer program are provided for managing guest network access in a residential space. In use, network usage data is collected from a residential network router operating in a residential space. Additionally, a machine learning algorithm processes the network usage data to classify a user device connected to the residential network router as being operated by a guest of the residential space. Further, the classification is output for performing one or more related actions.

Abstract: A system, method, and computer program product are provided for efficiently automating software testing of business flows. In use, a business flow executed by a user is recorded by a testing system. The business flow is executed by the testing system utilizing a plurality of user selected parameters. Additionally, the recorded business flow is automatically parsed by the testing system into a plurality of activities associated with the business flow. Further, one or more existing automated activities in a test automation repository that correlate with one or more of the plurality of activities associated with the business flow are identified by the testing system (e.g. using a smart match algorithm). Moreover, an automated test for the business flow is generated by the testing system utilizing the one or more existing automated activities in the test automation repository.

Abstract: A system, method, and computer program product are provided for generating event tests associated with a testing project. In use, an indication of one or more event types is received for creating one or more events on which to perform event testing associated with at least one testing project. Additionally, an indication of one or more parameters associated with the one or more events on which to perform the event testing is received. Further, one or more event files are generated for testing the one or more events based on the one or more event types and the one or more parameters. In addition, the one or more event files are sent to one or more event processing systems for testing the one or more events, the testing of the one or more events including storing information associated with all faults resulting from the testing of the one or more events in a risky events repository that is capable of being utilized to generate testing rules for additional testing projects.

Abstract: A system, method, and computer program product are provided for automating activities associated with a testing project. In use, design of a testing project is initiated. Additionally, one or more activities associated with the testing project in which to automate are identified based on criteria associated with the one or more activities. Further, the identified one or more activities are automated such that the one or more activities are performed automatically during performance of the testing project.

Abstract: A system, method, and computer program product are provided for recommending a number of test cases and effort to allocate to one or more business processes associated with a software testing project. In use, one or more business processes associated with a software testing project are identified. A business priority and customization level is set for each of the one or more business processes associated with the software testing project Additionally, a number of defects are estimated for each of the one or more business processes associated with the software testing project. Further, a quality level is determined for each of the one or more business processes associated with the User Acceptance Testing software testing project.