US 12,298,891 B2
Machine-based source code assessment
Alexander Hoole, Vancouver (CA); James Wesley Rabon, Montgomery, AL (US); and Peter Thomas Blay, Santa Clara, CA (US)
Assigned to Micro Focus LLC, Santa Clara, CA (US)
Filed by MICRO FOCUS LLC, Santa Clara, CA (US)
Filed on Apr. 8, 2022, as Appl. No. 17/716,869.
Prior Publication US 2023/0325306 A1, Oct. 12, 2023
Int. Cl. G06F 11/36 (2006.01); G06F 11/3668 (2025.01); G06N 3/08 (2023.01)
CPC G06F 11/3688 (2013.01) [G06F 11/3696 (2013.01); G06N 3/08 (2013.01)] 20 Claims
OG exemplary drawing
 
1. A computer-implemented method of training a dynamic application testing component, comprising:
accessing an application under test (AUT);
identifying a set of available tests associated with the AUT, wherein each test, of the set of available tests, corresponds to at least one executable environment;
analyzing a source code corresponding to the AUT to determine at least one target executable environment of the AUT;
determining an exclusion category comprising tests, of the set of available tests, that comprise a corresponding at least one executable environment that excludes the at least one target executable environment; and
configuring the dynamic application testing component to test the AUT comprising tests selected from the set of available tests excluding tests that are determined to be members of the exclusion category; and
wherein each test, of the set of available tests, corresponds to the at least one executable environment, determined by providing the test and at least one target environment to a neural network and receiving therefrom a determination identifying at least one of each test that corresponds to the at least one executable environment or each test that does not correspond to any of the at least one executable environment.