Abstract: Building binary packages for software products, particularly large-scale software products, is a highly computation intensive process. Thus, it is desirable to distribute the workload over a large number of computing nodes so as to have the build process complete in an optimal period of time. One environment providing compute resources that can be utilized for a highly available and dynamically scalable distributed build process is an elastic compute cloud. In such an environment, virtual machines can be instantiated and destroyed as the resource requirements of the build process dictate. This has the advantage that dedicated hardware is unneeded, and excess capacity on the hardware employed can be employed for other computation tasks when the build process is idle. Presented herein are systems, methods and computer storage media for distributing a highly available and scalable build service, suitable for use in an elastic compute environment or other distributed environment.

Abstract: An automated drilling rig control system in which one or more intelligent algorithms are in two-way communication with a rig control system and are configured to provide continuous external control over the a rig control system includes a safety logic module deployed between the intelligent algorithms and the rig control system. The safety logic module is configured to automatically close a communication pathway between the intelligent algorithms and the rig control system thereby preventing the intelligent algorithms from controlling the rig control system when an unsafe condition is detected.

Abstract: This disclosure relates to generating integrates test scenarios. The method includes creating a test process model comprising a plurality of processes and one or more interaction paths amongst the plurality of processes based on business process information; identifying a plurality of test scenarios based on an analysis of the plurality of processes and the one or more interaction paths amongst the plurality of processes, wherein each of the plurality of test scenarios comprises a unique process flow path; determining a risk weight and a criticality weight associated with each of the plurality of test scenarios; and identifying at least one test scenario from the plurality of test scenarios based on a comparison of the risk weight and the criticality weight determined for each of the plurality of test scenarios with an associated threshold weight.