Prosecution Insights
Last updated: April 19, 2026
Application No. 18/663,436

SYSTEMS AND METHODS FOR MIGRATING APPLICATION FUNCTIONALITY USING ADVANCED COMPUTATIONAL MODELS FOR DATA ANALYSIS AND AUTOMATED PROCESSING

Non-Final OA §101§102
Filed
May 14, 2024
Examiner
MEHRMANESH, ELMIRA
Art Unit
2113
Tech Center
2100 — Computer Architecture & Software
Assignee
BANK OF AMERICA CORPORATION
OA Round
1 (Non-Final)
84%
Grant Probability
Favorable
1-2
OA Rounds
2y 11m
To Grant
90%
With Interview

Examiner Intelligence

Grants 84% — above average
84%
Career Allow Rate
612 granted / 732 resolved
+28.6% vs TC avg
Moderate +7% lift
Without
With
+6.8%
Interview Lift
resolved cases with interview
Typical timeline
2y 11m
Avg Prosecution
20 currently pending
Career history
752
Total Applications
across all art units

Statute-Specific Performance

§101
15.1%
-24.9% vs TC avg
§103
30.2%
-9.8% vs TC avg
§102
30.9%
-9.1% vs TC avg
§112
12.6%
-27.4% vs TC avg
Black line = Tech Center average estimate • Based on career data from 732 resolved cases

Office Action

§101 §102
DETAILED ACTION The application of Albero et al., for a “Systems and methods for migrating application functionality using advanced computational models for data analysis and automated processing” filed on May 14, 2024 has been examined. The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA . The information disclosure statement (IDS) submitted on August 28, 2024 has been considered. Claims 1-20 are presented for examination. Claims 9-16 are rejected under 35 USC § 101. Claims 1, 4, 6-9, 12, 14-17, and 20 are rejected under 35 USC § 102. Claims 2-3, 5, 10-11, 13, and 18-19 are objected to while containing allowable matter. Claim Rejections - 35 USC § 101 35 U.S.C. 101 reads as follows: Whoever invents or discovers any new and useful process, machine, manufacture, or composition of matter, or any new and useful improvement thereof, may obtain a patent therefor, subject to the conditions and requirements of this title. Claims 9-16 are rejected under 35 U.S.C. 101 because the claimed invention is directed to non-statutory subject matter. As per claims 9-16, the limitation of “A computer program product” is not limited to statutory subject matter. Computer programs claimed as computer listings per se, i.e., the descriptions or expressions of the programs, are not physical “things.” They are neither computer components nor statutory processes, as they are not “acts” being performed. Such claimed computer programs do not define any structural and functional interrelationships between the computer program and other claimed elements of a computer which permit the computer program’s functionality to be realized. “A computer program product” should be stored on a computer-readable storage medium to be tangible. As such, the claim is not limited to statutory subject matter and is therefore non-statutory. Examiner suggests changing claim 9, line 3 from “the computer program product comprising a non-transitory computer-readable medium” to “the computer program product comprising a non-transitory computer-readable storage medium” to overcome the 35 U.S.C. 101 rejection. Claim Rejections - 35 USC § 102 In the event the determination of the status of the application as subject to AIA 35 U.S.C. 102 and 103 (or as subject to pre-AIA 35 U.S.C. 102 and 103) is incorrect, any correction of the statutory basis for the rejection will not be considered a new ground of rejection if the prior art relied upon, and the rationale supporting the rejection, would be the same under either status. The following is a quotation of the appropriate paragraphs of 35 U.S.C. 102 that form the basis for the rejections under this section made in this Office action: A person shall be entitled to a patent unless – (a)(1) the claimed invention was patented, described in a printed publication, or in public use, on sale or otherwise available to the public before the effective filing date of the claimed invention. (a)(2) the claimed invention was described in a patent issued under section 151, or in an application for patent published or deemed published under section 122(b), in which the patent or application, as the case may be, names another inventor and was effectively filed before the effective filing date of the claimed invention. Claims 1, 4, 6-9, 12, 14-17, and 20 are rejected under 35 U.S.C. 102(a)(1)/(a)(2) as being anticipated by Verma et al. (U.S. PGPUB 20240248790). As per claims 1, 9, and 17, Verma discloses a system/a computer program product/a method ([0011], “Methods, computer program products, and systems are presented”) for migrating application functionality ([0049], “migrating one or more virtual machine to a new computing node 10”) using advanced computational models for data analysis and automated processing ([0041], “Predictive models can be trained with use of training data for return of action decisions by orchestrator 110.” and [0044], “orchestrator 110 performing fault detection with use of an artificial intelligence”), the system comprising: a processing device; a non-transitory storage device containing instructions when executed by the processing device ([0125]), causes the processing device to perform the steps of: receive, via a learning agent, a transaction incident associated ([0044], “fault detection events”) with a source application in a transaction ([0058], “At block 1201, computer environment 120A can be sending logging data for examination by orchestrator 110. Logging data sent at block 1201 can include logging data, e.g., obtained by use of hardware layer logging agents, system-level software logging agents and/or application layer logging agents. Orchestrator 110 on receipt of the described logging data can perform examining of logging data at block 1101. Logging data sent at block 1201 can include time series logging data. In one embodiment, logging data for a certain computer environment can be accumulated by a manager 115 associated to the computer environment being monitored and can be sent by the manager.”), wherein the transaction comprises one or more applications ([0030], “a large scale application, may consist of multiple sub-components each provided by a microservice. These components interact with each and forms the larger application service.”), and wherein the learning agent comprises learning the applications’ functionality ([0061]-[0062]); determine, using a real time incident listener, a scope of the transaction incident ([0061]-[0063]); access an application inventory to determine a target application, wherein the application inventory comprises a database of applications, and wherein the database of applications is associated with an entity that is associated with the system ([0037], “Data repository 108 in microservices registry 2121 can store data specifying attributes of microservices of system 100.”); generate, using a script generator, a script ([0049], “Examples of software remediations which can be deployed can include, e.g., spawning one or more new virtual machine (including one or more hypervisor based virtual machine and/or one more container based virtual machine)”), wherein the script comprises a source function associated with the source application ([0069], “Instances can refer to the number of containers of a microservice that are performing the same function.”) and ([0141], “new active instance of the VCE”); deploy the script to the target application ([0049], “Examples of software remediations which can be deployed can include, e.g., spawning one or more new virtual machine (including one or more hypervisor based virtual machine and/or one more container based virtual machine), migrating one or more virtual machine to a new computing node 10 provided by a physical computing node, reprovisioning one or more virtual machine”); and monitor the target application with a federated learning module ([0058], “Logging data sent at block 1201 can include logging data, e.g., obtained by use of hardware layer logging agents, system-level software logging agents and/or application layer logging agents…logging data for a certain computer environment can be accumulated by a manager 115 associated to the computer environment being monitored and can be sent by the manager”) and (Fig. 3, ORCHESTRATOR 110), wherein the federated learning module identifies issues ([0059], “orchestrator 110 can ascertain, based on the examining of logging data at block 1101, whether a fault has been identified”) associated with the target application ([0061]-[0063]). As per claims 4, 12, and 20, Verma discloses the script comprises generating instructions that, when executed by the target application, perform functions substantially similar to the source application’s functions ([0049], “Examples of software remediations which can be deployed can include, e.g., spawning one or more new virtual machine (including one or more hypervisor based virtual machine and/or one more container based virtual machine)”), wherein the script comprises a source function associated with the source application ([0069], “Instances can refer to the number of containers of a microservice that are performing the same function.”) and ([0141], “new active instance of the VCE”). As per claims 6 and 14, Verma discloses the target application comprises one or more of the applications associated with the application inventory ([0030], “a large scale application, may consist of multiple sub-components each provided by a microservice. These components interact with each and forms the larger application service.”) and ([0037], “Data repository 108 in microservices registry 2121 can store data specifying attributes of microservices of system 100.”). As per claims 7 and 15, Verma discloses deploying the script comprises transmitting, via the learning agent, data associated with the transaction to the target application for processing ([0049], “Examples of software remediations which can be deployed can include, e.g., spawning one or more new virtual machine (including one or more hypervisor based virtual machine and/or one more container based virtual machine), migrating one or more virtual machine to a new computing node 10 provided by a physical computing node, reprovisioning one or more virtual machine”). As per claims 8 and 16, Verma discloses each application associated with the transaction comprises a learning agent ([0044] and [0058], “Logging data sent at block 1201 can include logging data, e.g., obtained by use of hardware layer logging agents, system-level software logging agents and/or application layer logging agents.”). Allowable Subject Matter Claims 2-3, 5, 10-11, 13, and 18-19 are objected to as being dependent upon a rejected base claim, but would be allowable if rewritten in independent form including all of the limitations of the base claim and any intervening claims. Conclusion The prior art made of record and not relied upon is considered pertinent to applicant's disclosure. See included PTO-892. Any inquiry concerning this communication or earlier communications from the examiner should be directed to Elmira Mehrmanesh whose telephone number is (571)272-5531. The examiner can normally be reached on M-F from 10-6. If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, Bryce Bonzo, can be reached at telephone number (571) 272-3655. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300. Information regarding the status of an application may be obtained from Patent Center. Status information for published applications may be obtained from Patent Center. Status information for unpublished applications is available through Patent Center for authorized users only. Should you have questions about access to Patent Center, contact the Electronic Business Center (EBC) at 866-217-9197 (toll-free). Examiner interviews are available via telephone, in-person, and video conferencing using a USPTO supplied web-based collaboration tool. To schedule an interview, applicant is encouraged to use the USPTO Automated Interview Request (AIR) Form at https://www.uspto.gov/patents/uspto-automated- interview-request-air-form. /Elmira Mehrmanesh/ Primary Examiner, Art Unit 2113 /BRYCE P BONZO/Supervisory Patent Examiner, Art Unit 2113
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Prosecution Timeline

May 14, 2024
Application Filed
Mar 03, 2026
Non-Final Rejection — §101, §102 (current)

Precedent Cases

Applications granted by this same examiner with similar technology

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DYNAMIC REGISTRATION OF SOFTWARE COMPONENTS FOR DIAGNOSIS OF ROOT CAUSE OF FAILURE
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DATABASE SYSTEM INCIDENT EVALUATION, CLASSIFICATION, AND RESOLUTION SYSTEM
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Patent 12585518
ELECTRONIC APPARATUS FOR LOGGING, NON-TRANSITORY COMPUTER-READABLE RECORD MEDIUM FOR LOGGING, AND LOGGING METHOD
2y 5m to grant Granted Mar 24, 2026
Patent 12566691
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Patent 12566668
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2y 5m to grant Granted Mar 03, 2026
Study what changed to get past this examiner. Based on 5 most recent grants.

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Prosecution Projections

1-2
Expected OA Rounds
84%
Grant Probability
90%
With Interview (+6.8%)
2y 11m
Median Time to Grant
Low
PTA Risk
Based on 732 resolved cases by this examiner. Grant probability derived from career allow rate.

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