International Business Machines Corporation

Zhang Wu

Lu Yu

Xin Zhang

Yun Zhou

Da L Huang

Hui Wang

Ling Chen

Chen Geng

Systems, methods, and computer program products for automating the management of a tiered storage system, which improves the service life and costs of the flash-based storage devices that comprise the storage system. The systems, methods and program products utilize time series learning models to predict the write frequency of each data block for the next cycle of time. Using the write frequency predictions, management of the tiered flash-based storage system can automatically organize and migrate stored data based on storage costs, migration costs and frequency in which the data is accessed. Data that is more frequently accessed and updated is migrated to high-end flash-based storage devices, which are able to endure a greater number of program/erase cycles, while less frequently accessed data is migrated to less expensive, low-end flash-based storage devices, that have a lower maximum number program/erase cycles.

Tiered storage optimization and migration

The source code of a software artifact may be scanned, and a call tree model with leaf nodes may be generated based on the scan. A set of test cases can be executed against the software artifact and log data from the execution can be collected. A set of untested leaf nodes can be detected and a new set of test cases can be generated to test the untested nodes. The new set of test cases are executed and a subset of the test cases which cover the previously untested nodes are added to the existing set of test cases.

White box testing

Growing community of inventors

Shanghai, China

Zhang Wu