Abstract: A system for analyzing one or more process of software defect handling using one or more percentile-based statistical metric is provided herein. The system may include: a monitoring unit that is configured to monitor one or more processes of software defect handling, to yield monitored samples. The system further includes a percentile-based generator configured to generate one or more statistical metric that are at least partially based on percentile, further based on the monitored samples and further responsive to user selection; and a statistical calculation unit configured to apply the generated one or more statistical metric to real-time handling time samples obtained from the one or more processes of software defect handling, to yield a percentile-based analysis of the processes of software defect handling. The system may further include and a visual representation unit configured to visually present the percentile-based analysis responsive to preferences specified by the user.

Abstract: A method and associated systems for the environmentally aware load-balancing of components of a multi-component power-consuming system. The environmentally aware load-balancer receives continually updated values from at least two environmental sensors that monitor and report the values of environmental metrics that characterize components of the power-consuming system and the environments within which those components are located. When the load-balancer receives a task request directed to the power-consuming system, the load-balancer selects a balanced workload allocation as a function of the values of the received environmental metrics and communicates that balanced workload allocation to a routing mechanism. The routing mechanism then uses the communicated balanced workload allocation to determine which component or components of the power-consuming system should receive the task request.

Abstract: A system and associated method for automatically assessing maturity for a custom application in a cloud computing environment in accordance with a standard application model. A data fabric analyzer automatically calculates a logical data model compliance level to a process model for the custom application, and a maturity level the logical data model against a standard logical data model. If the logical data model is mature, the data fabric analyzer transforms the logical data model to a physical data model for implementation by a distillation process and a shearing process. If the logical data model is immature, the process model maturity is assessed to employ a standard physical model for implementing the custom application. The data fabric analyzer subsequently computes non-compliance levels for the physical model and calculates a capital expenditure cost caused by non-compliance of the custom physical model to a standard physical model.

Abstract: A method and associated systems for the environmentally aware load-balancing of components of a multi-component power-consuming system. The environmentally aware load-balancer receives continually updated values from at least two environmental sensors that monitor and report the values of environmental metrics that characterize components of the power-consuming system and the environments within which those components are located. When the load-balancer receives a task request directed to the power-consuming system, the load-balancer selects a balanced workload allocation as a function of the values of the received environmental metrics and communicates that balanced workload allocation to a routing mechanism. The routing mechanism then uses the communicated balanced workload allocation to determine which component or components of the power-consuming system should receive the task request.

Abstract: A system for analyzing one or more process of software defect handling using one or more percentile-based statistical metric is provided herein. The system may include: a monitoring unit that is configured to monitor one or more processes of software defect handling, to yield monitored samples. The system further includes a percentile-based generator configured to generate one or more statistical metric that are at least partially based on percentile, further based on the monitored samples and further responsive to user selection; and a statistical calculation unit configured to apply the generated one or more statistical metric to real-time handling time samples obtained from the one or more processes of software defect handling, to yield a percentile-based analysis of the processes of software defect handling. The system may further include and a visual representation unit configured to visually present the percentile-based analysis responsive to preferences specified by the user.