公开(公告)号：US11886329B2

公开(公告)日：2024-01-30

申请号：US17840745

申请日：2022-06-15

Applicant: SAS Institute Inc.

Inventor： Steven Joseph Gardner ,  Connie Stout Dunbar ,  David Bruce Elsheimer ,  Gregory Scott Dunbar ,  Joshua David Griffin ,  Yan Gao

IPC: G06F11/36

CPC classification number: G06F11/3684 ,  G06F11/3688

Abstract: A computing device selects new test configurations for testing software. (A) First test configurations are generated using a random seed value. (B) Software under test is executed with the first test configurations to generate a test result for each. (C) Second test configurations are generated from the first test configurations and the test results generated for each. (D) The software under test is executed with the second test configurations to generate the test result for each. (E) When a restart is triggered based on a distance metric value computed between the second test configurations, a next random seed value is selected as the random seed value and (A) through (E) are repeated. (F) When the restart is not triggered, (C) through (F) are repeated until a stop criterion is satisfied. (G) When the stop criterion is satisfied, the test result is output for each test configuration.

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.

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：US20220308989A1

公开(公告)日：2022-09-29

申请号：US17840745

申请日：2022-06-15

Applicant: SAS Institute Inc.

Inventor： Steven Joseph Gardner ,  Connie Stout Dunbar ,  David Bruce Elsheimer ,  Gregory Scott Dunbar ,  Joshua David Griffin ,  Yan Gao

IPC: G06F11/36

Abstract: A computing device selects new test configurations for testing software. (A) First test configurations are generated using a random seed value. (B) Software under test is executed with the first test configurations to generate a test result for each. (C) Second test configurations are generated from the first test configurations and the test results generated for each. (D) The software under test is executed with the second test configurations to generate the test result for each. (E) When a restart is triggered based on a distance metric value computed between the second test configurations, a next random seed value is selected as the random seed value and (A) through (E) are repeated. (F) When the restart is not triggered, (C) through (F) are repeated until a stop criterion is satisfied. (G) When the stop criterion is satisfied, the test result is output for each test configuration.

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：US10963802B1

公开(公告)日：2021-03-30

申请号：US17120340

申请日：2020-12-14

Applicant: SAS Institute Inc.

Inventor： Steven Joseph Gardner ,  Joshua David Griffin ,  Yan Xu ,  Yan Gao

IPC: G06N5/04 ,  G06N20/00

Abstract: A computing device selects decision variable values. A lower boundary value and an upper boundary value is defined for a decision variable. (A) A plurality of decision variable configurations is determined using a search method. The value for the decision variable is between the lower boundary value and the upper boundary value. (B) A decision variable configuration is selected. (C) A model of the model type is trained using the decision variable configuration. (D) The model is scored to compute an objective function value. (E) The computed objective function value and the selected decision variable configuration are stored. (F) (B) through (E) is repeated for a plurality of decision variable configurations. (G) The lower boundary value and the upper boundary value are updated using the objective function value and the decision variable configuration stored. Repeat (A)-(F) with the lower boundary value and the upper boundary value updated in (G).