Notice of Pre-AIA or AIA Status
The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA .
DETAILED ACTION
Status of the Application
Claims 1-20 have been examined in this application. This communication is the first action on the merits.
Information Disclosure Statement
The information disclosure statements (IDS) submitted on 12/09/2024, 12/09/2024, 12/09/2024, 4/16/2025, 7/30/2025, 7/14/2026, 8/12/20226 are in compliance with the provisions of 37 CFR 1.97. Accordingly, the information disclosure statements are being considered by the examiner.
35 USC 101 Analysis
The following is a statement of reasons for the indication of allowable subject matter: Claims 1-
20 are eligible under 35 USC 101. Under Step 1 of the analysis, pending independent claims 1, 13, 17 are
directed to a method, system, and CRM, thus meeting the Step 1 eligibility criterion. Under Prong One of Revised Step 2A of the 2019 PEG, pending independent claims 1, 13, 17 do not recite a judicial exception – i.e. a mathematical concept, method of organizing human activity, or mental process.
Therefore, based on these findings of fact, the Examiner understands the claimed subject matter of pending claims 1-20 to be patent-eligible.
Double Patenting
The nonstatutory double patenting rejection is based on a judicially created doctrine grounded in public policy (a policy reflected in the statute) so as to prevent the unjustified or improper timewise extension of the “right to exclude” granted by a patent and to prevent possible harassment by multiple assignees. A nonstatutory double patenting rejection is appropriate where the conflicting claims are not identical, but at least one examined application claim is not patentably distinct from the reference claim(s) because the examined application claim is either anticipated by, or would have been obvious over, the reference claim(s). See, e.g., In re Berg, 140 F.3d 1428, 46 USPQ2d 1226 (Fed. Cir. 1998); In re Goodman, 11 F.3d 1046, 29 USPQ2d 2010 (Fed. Cir. 1993); In re Longi, 759 F.2d 887, 225 USPQ 645 (Fed. Cir. 1985); In re Van Ornum, 686 F.2d 937, 214 USPQ 761 (CCPA 1982); In re Vogel, 422 F.2d 438, 164 USPQ 619 (CCPA 1970); In re Thorington, 418 F.2d 528, 163 USPQ 644 (CCPA 1969).
A timely filed terminal disclaimer in compliance with 37 CFR 1.321(c) or 1.321(d) may be used to overcome an actual or provisional rejection based on nonstatutory double patenting provided the reference application or patent either is shown to be commonly owned with the examined application, or claims an invention made as a result of activities undertaken within the scope of a joint research agreement. See MPEP § 717.02 for applications subject to examination under the first inventor to file provisions of the AIA as explained in MPEP § 2159. See MPEP § 2146 et seq. for applications not subject to examination under the first inventor to file provisions of the AIA . A terminal disclaimer must be signed in compliance with 37 CFR 1.321(b).
The filing of a terminal disclaimer by itself is not a complete reply to a nonstatutory double patenting (NSDP) rejection. A complete reply requires that the terminal disclaimer be accompanied by a reply requesting reconsideration of the prior Office action. Even where the NSDP rejection is provisional the reply must be complete. See MPEP § 804, subsection I.B.1. For a reply to a non-final Office action, see 37 CFR 1.111(a). For a reply to final Office action, see 37 CFR 1.113(c). A request for reconsideration while not provided for in 37 CFR 1.113(c) may be filed after final for consideration. See MPEP §§ 706.07(e) and 714.13.
The USPTO Internet website contains terminal disclaimer forms which may be used. Please visit www.uspto.gov/patent/patents-forms. The actual filing date of the application in which the form is filed determines what form (e.g., PTO/SB/25, PTO/SB/26, PTO/AIA /25, or PTO/AIA /26) should be used. A web-based eTerminal Disclaimer may be filled out completely online using web-screens. An eTerminal Disclaimer that meets all requirements is auto-processed and approved immediately upon submission. For more information about eTerminal Disclaimers, refer to www.uspto.gov/patents/apply/applying-online/eterminal-disclaimer.
Claim 1 is rejected on the ground of nonstatutory double patenting as being unpatentable over claim 1 of U.S. Patent No. 11650909. Although the claims at issue are not identical, they are not patentably distinct from each other because the difference is the following:
Limitations in Instant Application:
A computer-implemented method comprising:
collecting, by one or more data collecting agents and at a first time, first system state information corresponding to a first application;
intercepting, by a testing agent during a testing period at a second time, a first call in a computing system to a first Application Programming Interface (API) based on determining that the first call originated from the first application;
modifying, by the testing agent, the first call by mutating at least one attribute of the first call, wherein the mutation to the at least one attribute comprises at least one of: a change to a function name associated with the first API, a change to a parameter included in the first call, or a change to a destination, container, or scope associated with the first API;
causing the computing system to process the modified first call and return a result to the first application based on the mutation to the at least one attribute; collecting, by the one or more data collecting agents, during the testing period, and after causing the computing system to process the modified first call, second system state information corresponding to a state of the first application based on returning the result of the modified first call to the first application;
training a machine learning model based on the first system state information and the second system state information, wherein the trained machine learning model is configured to determine a pattern of performance associated with the first application and the first API that indicates a potential correlation between performance of the first API and performance of the first application;
collecting, by the one or more data collecting agents, third system state information corresponding to the first application and the first API;
and generating, using the trained machine learning model and based on the pattern of performance, a report associated with the performance of the first application based on the third system state information.
Limitation in Patent No. 11650909:
A computer-implemented method comprising:
collecting, by one or more data collecting agents and at a first time, first system state information corresponding to a first application and at least one dependency of the first application;
intercepting, by a testing agent, a first call in a computing system from the first application to a first Application Programming Interface (API) during a testing period and at a second time;
modifying, by the testing agent, the first call by mutating at least one attribute of the first call, wherein the mutation to the at least one attribute causes the first call to fail;
causing the computing system to process the modified first call and return a result to the first application based on the mutation to the at least one attribute;
collecting, by the one or more data collecting agents and after causing the computing system to process the modified first call, second system state information corresponding to the first application and the at least one dependency;
training a machine learning model based on the first system state information and the second system state information, wherein the trained machine learning model is configured to determine a pattern of performance associated with the first application and the at least one dependency that indicates a potential correlation between performance of the first API and performance of the first application;
collecting, by the one or more data collecting agents, third system state information corresponding to the first application and the at least one dependency;
and generating, using the trained machine learning model and based on the pattern of performance, a report associated with the performance of the first application based on the third system state information.
However, it would have been obvious to one having ordinary skill in the art to make the changes that are apparent above, in order to cover slightly broader limitations. Furthermore, the claimed elements perform the same function as before.
The prior art of record does not teach neither singly nor in combination the limitations of claims 1-20.
The most relevant prior art identified, Henftling (20030005416), teaches a fault search method and apparatus for simplified use and control of fault search in a system with several different models such as, for example, a hardware model, a software program and a test bench model, including: a system simulated by several different simulation models, where the system is described in individual simulation models by description languages of different classes, and where allocated to the individual simulation models are different first fault search facilities for tracing a fault in each case by means of access to the corresponding simulation model, the method comprising: automatically detecting a user input using a second fault search facility which is of a higher order than the first fault search facilities, and automatically controlling the first fault search facilities by the second fault search facility depending on the user input, in order to find a system fault by access to a relevant simulation model. However, it lacks the combination of claimed elements of pending independent claims 1, 13, 17.
Merritt (10990516 ) teaches methods, systems, apparatuses, and computer program products for selecting a test suite for an API, comprising : receive test patterns and heuristics; receive an input API, wherein the input API comprises a set of subroutine definitions, protocols, and tools for building a software application; parse the input API to extract API specifications; and based at least in part on the extracted API specifications, the test patterns, and the heuristics, programmatically generate a test suite based at least in part on a machine learning model, wherein programmatically generating the test suite comprises selecting one or more tests for inclusion in the test suite from a plurality of recommended tests, wherein the one or more tests are selected for inclusion in the test suite based at least in part on the one or more tests being assigned a high importance indicator, and wherein the test suite comprises one or more test routines, one or more data values, and one or more expected results. However, it lacks the combination of claimed elements of pending independent claims 1, 13, 17.
When taken as a whole, the claims are not rendered obvious as the available prior art does not
suggest or otherwise render obvious the noted features nor does the available prior art suggest or
otherwise render obvious further modification of the evidence at hand. Such modifications would require substantial reconstruction relying solely on improper hindsight bias, and thus would not be
obvious.
Conclusion
Any inquiry concerning this communication or earlier communications from the examiner should be directed to Alexandru Cirnu whose telephone number is (571) 272-7775. The examiner can normally be reached on 8:00 AM - 5:00 PM. 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) at http://www.uspto.gov/interviewpractice.
If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, Ilana Spar can be reached on (571) 270-7537. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
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/Alexandru Cirnu/
Primary Patent Examiner, Art Unit 3622
9/11/2026
Prosecution Insights