Dell Products Inc.

Shanir Anshul

Shibi Panikkar

Dong Ji

Sudeshna Dash

Tuck Meng Chin

Xiang Cao

In product testing, a script prioritization tool () is used to intelligently prioritize the execution sequence of test scripts. This tool creates a repository of test outputs from the executions of test scripts and analyzes the outputs to train and deploy a machine learning, ML, model that defines the priority of the scripts that may need to be executed and the scripts whose execution may be skipped without affecting the quality of testing. Scripts that are more likely to fail and/or are time consuming to execute are prioritized, while other scripts may be skipped. The ML model ranks the scripts based on the average execution time of the script, a count of the execution failures of the script, a count of the number of execution retries for the script, and the most recent failure time of the script. The scripts can be executed based on their rankings for efficiency and time-saving.

Smart selection of test scripts for commodity testing on manufacturing floor

A system for testing electrical components comprising a supplier test system operating on a first processor and configured to generate test data for a component and to store the component test data on a block chain. A board level test system operating on a second processor and configured to generate test data for a board and to store the board test data on the block chain. A test tracking system configured to request a first key to access to the component test data and a second key to access the board test data and to store the first key and the second key.

Component life cycle test categorization and optimization

An information handling system may include a processor and a memory communicatively coupled to the processor. The information handling system may be configured to: receive, for each of a plurality of target information handling systems, information regarding software to be burned to the respective target information handling system; receive, for each of the target information handling systems, information regarding testing time; based on a statistical analysis of the information regarding the testing time, determine a predicted burn time for each target information handling system; and based on the respective predicted burn times, determine a desired order in which the target information handling systems are to be burned with the software.

Growing community of inventors

Hyderabad Telangana, India

Shanir Anshul