公开(公告)号：US11775878B2

公开(公告)日：2023-10-03

申请号：US17523607

申请日：2021-11-10

Applicant: SAS Institute Inc.

Inventor： Yan Gao ,  Joshua David Griffin ,  Yu-Min Lin ,  Bengt Wisen Pederson ,  Ricky Dee Tharrington, Jr. ,  Pei-Yi Tan ,  Raymond Eugene Wright

IPC: G06N20/20 ,  G06N7/01

CPC classification number: G06N20/20 ,  G06N7/01

Abstract: A computing device selects new test configurations for testing software. Software under test is executed with first test configurations to generate a test result for each test configuration. Each test configuration includes a value for each test parameter where each test parameter is an input to the software under test. A predictive model is trained using each test configuration of the first test configurations in association with the test result generated for each test configuration based on an objective function value. The predictive model is executed with second test configurations to predict the test result for each test configuration of the second test configurations. Test configurations are selected from the second test configurations based on the predicted test results to define third test configurations. The software under test is executed with the defined third test configurations to generate the test result for each test configuration of the third test configurations.

公开(公告)号：US20220198340A1

公开(公告)日：2022-06-23

申请号：US17523607

申请日：2021-11-10

Applicant: SAS Institute Inc.

Inventor： Yan Gao ,  Joshua David Griffin ,  Yu-Min Lin ,  Bengt Wisen Pederson ,  Ricky Dee Tharrington,, JR. ,  Pei-Yi Tan ,  Raymond Eugene Wright

IPC: G06N20/20 ,  G06N7/00

Abstract: A computing device selects new test configurations for testing software. Software under test is executed with first test configurations to generate a test result for each test configuration. Each test configuration includes a value for each test parameter where each test parameter is an input to the software under test. A predictive model is trained using each test configuration of the first test configurations in association with the test result generated for each test configuration based on an objective function value. The predictive model is executed with second test configurations to predict the test result for each test configuration of the second test configurations. Test configurations are selected from the second test configurations based on the predicted test results to define third test configurations. The software under test is executed with the defined third test configurations to generate the test result for each test configuration of the third test configurations.

公开(公告)号：US11635988B1

公开(公告)日：2023-04-25

申请号：US17820952

申请日：2022-08-19

Applicant: SAS Institute Inc.

Inventor： Yan Gao ,  Joshua David Griffin ,  Yu-Min Lin ,  Yan Xu ,  Seyedalireza Yektamaram ,  Amod Anil Ankulkar ,  Aishwarya Sharma ,  Girish Vinayak Kolapkar ,  Kiran Devidas Bhole ,  Kushawah Yogender Singh ,  Jorge Manuel Gomes da Silva

IPC: G06F9/455 ,  G06F9/48 ,  G06N20/10

Abstract: A computing device determines an optimal number of threads for a computer task. Execution of a computing task is controlled in a computing environment based on each task configuration included in a plurality of task configurations to determine an execution runtime value for each task configuration. An optimal number of threads value is determined for each set of task configurations having common values for a task parameter value, a dataset indicator, and a hardware indicator. The optimal number of threads value is an extremum value of an execution parameter value as a function of a number of threads value. A dataset parameter value is determined for a dataset. A hardware parameter value is determined as a characteristic of each distinct executing computing device in the computing environment. The optimal number of threads value for each set of task configurations is stored in a performance dataset in association with the common values.