Abstract: A method, system and apparatus for configuring programmatic objects for cache co-location. The method can include the steps of counting a frequency of access for individual fields in the object in a static analysis, rearranging the fields in the object based upon the counted frequency in the static analysis, and executing the object. Subsequently, a frequency of access for the individual fields in the object further can be counted in a dynamic analysis. Consequently, the fields in the object can be further rearranged based upon the counted frequency in the dynamic analysis to produce an optimal grouping for placement in cache memory. In a preferred aspect of the invention, access types for the individual fields can be identified. Subsequently, the rearranging step and the further rearranging step can be performed based both upon the counted frequency and also upon the access types.

Abstract: A method, system and apparatus for configuring programmatic objects for cache co-location. The method can include the steps of counting a frequency of access for individual fields in the object in a static analysis, rearranging the fields in the object based upon the counted frequency in the static analysis, and executing the object. Subsequently, a frequency of access for the individual fields in the object further can be counted in a dynamic analysis. Consequently, the fields in the object can be further rearranged based upon the counted frequency in the dynamic analysis to produce an optimal grouping for placement in cache memory. In a preferred aspect of the invention, access types for the individual fields can be identified. Subsequently, the rearranging step and the further rearranging step can be performed based both upon the counted frequency and also upon the access types.

Abstract: The present invention a synchronous peer to peer transfer model that utilizes all available network bandwidth to deploy application code to an entire cluster as fast as it can be sent to one machine. A method in accordance with an embodiment of the present invention includes: determining a number N of simultaneous connections that should be opened to the cluster members to maximize network bandwidth; and synchronously deploying the application to the cluster members using the N simultaneous connections.

Abstract: The “API Usage Tool” (AUT) comprises an Interactive Developer Environment Plug-in (IDEP) and a Web Service Component (WSC). The IDEP opens the source code file containing API method calls, identifies the API method calls in the source code, and saves the identified API method calls to an API usage log. The WSC searches API usage data sheets for usage, best practices and known bugs for each identified API method call. The WSC generates an API usage compilation based on the identified API method calls. The IDEP compares the API usage compilation to the dynamic data in the usage log, looking for conflicts between the compiled usage and the actual usage in the source code. The IDEP marks any API method calls in the source code that do not comport with the compiled usage guidelines.

Abstract: The present invention a synchronous peer to peer transfer model that utilizes all available network bandwidth to deploy application code to an entire cluster as fast as it can be sent to one machine. A method in accordance with an embodiment of the present invention includes: determining a number N of simultaneous connections that should be opened to the cluster members to maximize network bandwidth; and synchronously deploying the application to the cluster members using the N simultaneous connections.

Abstract: The “API Usage Tool” (AUT) comprises an Interactive Developer Environment Plug-in (IDEP) and a Web Service Component (WSC). The IDEP opens the source code file containing API method calls, identifies the API method calls in the source code, and saves the identified API method calls to an API usage log. The WSC searches API usage data sheets for usage, best practices and known bugs for each identified API method call. The WSC generates an API usage compilation based on the identified API method calls. The IDEP compares the API usage compilation to the dynamic data in the usage log, looking for conflicts between the compiled usage and the actual usage in the source code. The IDEP marks any API method calls in the source code that do not comport with the compiled usage guidelines.

Abstract: An optimal set of devices is allocated to a package of device requests. In one embodiment, for each device request within the package of requests, a determination is made as to one or more eligible devices capable of satisfying each of the device requests and for each eligible device, a preference value is obtained. The preference values are then used to assign devices to a package of device requests such that the sum of the preference values of the assigned devices satisfies a specific optimizing function. The assigned devices provide global optimization of device allocation for a package of requests, thereby improving system throughput and performance.