An example includes the following operations: identifying parameters associated with a test program, where the parameters are based on at least one of a device under test (DUT) to be tested by the test program or a type of test to be performed on the DUT by the test program; assigning weights to the parameters; generating a numerical value for the test program based on the parameters, the weights, and equations that are based on the parameters and the weights, where the numerical value is indicative of a complexity of the test program; and using the numerical value to obtain information about effort needed to develop future test programs.

Techniques may involve determining, according to determination that a received system alarm corresponds to a predefined to-be-monitored alarm, the received system alarm as a target system alarm. The techniques may further involve determining a system module corresponding to the target system alarm based on a predefined mapping relationship between the system alarm and the system module. In addition, the techniques may further involve acquiring the system diagnostic information of the system module which is associated with the target system alarm. In this way, time for collecting system diagnostic information can be reduced and user experience can be improved.

A memory check method, a memory check device and a memory check system are disclosed. The method includes the following. A debug file is generated according to a source code, where the debug file carries symbol information related to a description message in the source code. Memory data generated by a memory storage device in execution of a firmware is received. The debug file is loaded to automatically analyze the memory data. In addition, an analysis result is presented by an application program interface, where the analysis result reflects a status of the firmware with assistance of the symbol information.

A virtual environment system for validating executable data using authorized hash outputs is provided. In particular, the system may generate a virtual environment using a virtual environment device, where the virtual environment is logically and/or physically separated from other devices and/or environments within the network. The system may then open a specified set of executable data within the virtual environment and perform a set of commands or processes with respect to the executable data. If the system determines that the executable data is unsafe to run, the system may generate a hash output of the executable data and store the hash output in a database of unauthorized executable data. In this way, the system may securely generate a repository of authorized and unauthorized hashes such that the system may ensure that unsafe executable data is blocked from being processed within a network environment.

An information handling system includes a delay controller having an analytics engine configured to analyze telemetry data associated with an installation of a program, to calculate a confidence index based upon the analyzed telemetry data, and to generate a recommendation corresponding to the calculated confidence index. A download controller receives an end-user recommendation selection, and delays the installation of the program based upon a delay time in the received end-user recommendation selection.

Techniques for implementing user interfaces, systems, and processes for multidimensional clustering and analysis are described herein. In one aspect, an application or cloud service receives a request to cluster a set of records where the request identifies a first set of one or more dimensions to use for clustering and a second set of one or more dimensions to analyze for correlation patterns. Responsive to receiving the request to cluster the set of records, the system generates clusters based at least in part on variances in the first set of one or more dimensions, wherein each cluster includes at least one record from the set of records. The system may generate, for each respective cluster, an analytic result that identifies how strongly the second set of one or more dimensions correlate to the respective cluster. The system may present the clusters and analytic results for further processing.

Example implementations relate to data monitoring. An example non-transitory machine-readable medium can include instructions executable by a processor to request, from an agent device on a particular computing device of a plurality of computing devices, monitoring of a particular piece of data associated with the particular computing device. The instructions can be executable to retrieve the event responsive to the agent device detecting an event including a change in the particular piece of data during the monitoring and report the event via a graphical user interface.

A computer platform for hosting applications utilizes a computing device to manage seasonal performance metric alerts. The computer device may include a memory and at least one processor coupled to the memory. The computer device may collect a time series of an application performance metric for a period of less than two weeks. The computer device may determine a daily distributions each day within the period. The computer device may apply a radial basis function (RBF) kernel-based change point detection to the time series to determine that the daily distributions include a weekend time period that has a different daily distribution than a time period before or after the weekend time period. The computer device may adjust a baseline prediction of the metric for the weekend time period. The computer device may send an alert based on a deviation of a value of the metric from the adjusted baseline prediction.

In one aspect, a first device may download at least one disk image and then provide the disk image to second and third devices through a fourth device that controls connections to the second and third devices. The first device may then run computer diagnostics concurrently on the second and third devices through the fourth device and using the image provided to each of the second and third devices. In some examples, communication between the devices may occur using USB ports.

Embodiments of the invention are directed to a system, method, or computer program product structured for determining platform stability and resiliency. In some embodiments, the system is structured for, for each of a plurality of applications deployed or scheduled to be deployed on a platform, gathering data, evaluating stability factor(s), evaluating resiliency factor(s), determining an overall stability score for the application from the stability factor(s) and overall resiliency score for the application from the resiliency factor(s), and determining a data quality score and criticality score for the application from the stability factor(s) and resiliency factor(s); generating a first GUI including selectable filters; receiving a selection of at least one filter; identifying a subset of applications using the selected filter(s); determining an aggregated stability score, resiliency score, data quality score, and criticality score for the identified subset; and generating a second GUI including the aggregated scores.