Granted Patent B2

US 12,561,132 · App. 18/225,211 · Granted Feb 24, 2026

Inventors: Deepak Suresh Dhokane (Maharashtra, IN); Debraj Goswami (Telangana, IN); Satish S. Kekane (Maharashtra, IN); Mohan Kishore Kolli (McKinney, TX)

Assignee: BANK OF AMERICA CORPORATION

G06F8/71G06F11/3684G06F11/3688

Abstract

Claims (79)

1 . A system for self-adjusting robotic build infrastructure for software application development, the system comprising:

a memory device with computer-readable program code stored thereon;

at least one processing device operatively coupled to the at least one memory device and the at least one communication device, wherein executing the computer-readable code is configured to cause the at least one processing device to:

receive a set of input parameters associated with a planned build;

analyze the set of input parameters associated with the planned build;

determine a robotic build infrastructure from a robotic build infrastructure database using the analyzed set of input parameters associated with the planned build;

compile an image test of the planned build based on the robotic build infrastructure determined from the robotic build infrastructure database;

validate the image test through a performance test;

adjust the image test based on the analyzed set of input parameters and the performance test validation;

initiate a final build of the robotic build infrastructure based on the adjusted image test; and

certify the final build of the robotic build infrastructure.

2 . The system of claim 1 , wherein determination of the robotic build infrastructure from the robotic build infrastructure database further comprises:

compare the analyzed set of input parameters against a standards information base;

define a set of compliance guidelines through a governance module;

compare the analyzed set of input parameters against the robotic build infrastructure database; and

select the robotic build infrastructure from the robotic build infrastructure database using a plurality of advanced computational models for data analysis and automated decision making, comparisons of the standards information base, and the set of compliance guidelines defined by the governance module.

3 . The system of claim 1 , wherein validating the image test comprises performing regressive validation on the image test.

4 . The system of claim 1 , wherein adjusting the image test comprises:

define a set of performance criteria based on the analyzed set of input parameters associated with the planned build;

load a test case scenario from a test case repository;

execute the test case scenario; and

analyze the set of performance criteria resulting from the test case scenario.

5 . The system of claim 4 , wherein adjusting the image test further comprises:

transmit a request to an end user to revise the test image based on a test iteration;

revise the test image upon receipt of approval from the end user to revise the test image based on the test iteration; and

generate an adjusted image test through a plurality of advanced computational models for data analysis and automated decision making.

6 . The system of claim 1 , wherein initiating a final build comprises storing the adjusted image test within the robotic build infrastructure database.

7 . The system of claim 1 , wherein initiating the final build comprises balancing a local traffic management (LTM) and a global traffic management (GTM).

8 . A computer program product for self-adjusting robotic build infrastructure for software application development, the computer program product comprising at least one non-transitory computer-readable medium having computer-readable program code embodied therein, the computer-readable program code comprising instructions that, when executed by at least one processor, cause the processor to:

receive a set of input parameters associated with a planned build;

analyze the set of input parameters associated with the planned build;

determine a robotic build infrastructure from a robotic build infrastructure database using the analyzed set of input parameters associated with the planned build;

compile an image test of the planned build based on the robotic build infrastructure determined from the robotic build infrastructure database;

validate the image test through a performance test;

adjust the image test based on the set of analyzed input parameters and the performance test validation;

initiate a final build of the robotic build infrastructure based on the adjusted image test; and

certify the final build of the robotic build infrastructure.

9 . The computer program product of claim 8 , wherein determination of the robotic build infrastructure from the robotic build infrastructure database further comprises:

compare the analyzed set of input parameters against a standards information base;

define a set of compliance guidelines through a governance module;

compare the analyzed set of input parameters against the robotic build infrastructure database; and

select the robotic build infrastructure from the robotic build infrastructure database using a plurality of advanced computational models for data analysis and automated decision making, comparisons of the standards information base, and the set of compliance guidelines defined by the governance module.

10 . The computer program product of claim 8 , wherein validating the image test comprises performing regressive validation on the image test.

11 . The computer program product of claim 8 , wherein adjusting the image test comprises:

define a set of performance criteria based on the analyzed set of input parameters associated with the planned build;

load a test case scenario from a test case repository;

initiate the test case scenario; and

analyze the set of performance criteria resulting from the test case scenario.

12 . The computer program product of claim 11 , wherein adjusting the image test further comprises:

transmit a request to an end user to revise the test image based on a test iteration;

revise the test image upon receipt of approval from the end user to revise the test image based on the test iteration; and

generate an adjusted robotic build infrastructure through a plurality of advanced computational models for data analysis and automated decision making.

13 . The computer program product of claim 8 , wherein initiating a final build comprises storing the adjusted image test within the build infrastructure database.

14 . The computer program product of claim 8 , wherein initiating the final build comprises balancing a local traffic management (LTM) and a global traffic management (GTM).

15 . A method for self-adjusting robotic build infrastructure for software application development, the method comprising:

receiving a set of input parameters associated with a planned build;

analyzing the set of input parameters associated with the planned build;

determining a robotic build infrastructure from a build infrastructure database using the analyzed set of input parameters associated with the planned build;

compiling an image test of the planned build based on the robotic build infrastructure determined from the robotic build infrastructure database;

validating the image test through a performance test;

adjusting the image test based on the set of input parameters and the performance test validation;

initiating a final build of the robotic build infrastructure based on the adjusted image test; and

certifying the final build of the robotic build infrastructure.

16 . The method of claim 15 , wherein determining the robotic build infrastructure from the robotic build infrastructure database further comprises:

comparing the analyzed set of input parameters against a standards information base;

defining a set of compliance guidelines through a governance module;

comparing the analyzed set of input parameters against the robotic build infrastructure database; and

selecting the robotic build infrastructure from the robotic build infrastructure database using a plurality of advanced computational models for data analysis and automated decision making, comparisons of the standards information base, and the set of compliance guidelines defined by the governance module.

17 . The method of claim 15 , wherein validating the image test comprises performing regressive validation on the image test.

18 . The method of claim 15 , wherein adjusting the image test comprises:

defining a set of performance criteria based on the analyzed set of input parameters associated with the planned build;

loading a test case scenario from a test case repository;

executing the test case scenario; and

analyzing the set of performance criteria resulting from the test case scenario.

19 . The method of claim 18 , wherein adjusting the image test comprises:

transmitting a request to an end user to revise the test image based on a test iteration;

revising the test image upon receipt of approval from the end user to revise the test image based on the test iteration; and

generating an adjusted robotic build infrastructure through a plurality of advanced computational models for data analysis and automated decision making.

20 . The method of claim 15 , wherein initiating a final build comprises storing the adjusted image test within the build infrastructure database.

Assignments (1)

Continuity (1)

References Cited (28)