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 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 1-6 are rejected under 35 U.S.C. 101 as not falling within one of the four statutory categories of invention. Said claims are drawn to ‘a system’ whereby said claims and specification are silent as to the hardware/software configuration of the claimed system. A s such, the system is capable of reading on software and therefore does not fall into any statutory class of invention. 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” to be 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. See Lowry, 32 F.3d at 1583-84, 32 USPQ2d at 1035. Claim Rejections - 35 USC § 112 The following is a quotation of 35 U.S.C. 112(b): (b) CONCLUSION. The specification shall conclude with one or more claims particularly pointing out and distinctly claiming the subject matter which the inventor or a joint inventor regards as the invention. Claims 1, 7, 13 are rejected under 35 U.S.C. 112(b), as being indefinite for failing to particularly point out and distinctly claim the subject matter which the inventor or a joint inventor, or for pre-AIA the applicant regards as the invention. Claims 1, 7, 13 each recite s “ receive an instruction to check compatibility of an application executing on an application server with a machine learning scenario ” whereby it is unclear if the ‘machine learning scenario’ is used to check compatibility or if the ‘machine learning scenario’ simply resides on the application server. In addition, each claim recites ‘ instruct the application server to execute the logic of the first plurality of object instances and return corresponding first results’ whereby it is unclear who or what ‘instructs’ and where or to whom ‘results’ are returned. Appropriate c larification is required. Claim Rejections - 35 USC § 103 The following is a quotation of 35 U.S.C. 103 which forms the basis for all obviousness rejections set forth in this Office action: A patent for a claimed invention may not be obtained, notwithstanding that the claimed invention is not identically disclosed as set forth in section 102, if the differences between the claimed invention and the prior art are such that the claimed invention as a whole would have been obvious before the effective filing date of the claimed invention to a person having ordinary skill in the art to which the claimed invention pertains. Patentability shall not be negated by the manner in which the invention was made . The factual inquiries for establishing a background for determining obviousness under 35 U.S.C. 103 are summarized as follows: 1. Determining the scope and contents of the prior art. 2. Ascertaining the differences between the prior art and the claims at issue. 3. Resolving the level of ordinary skill in the pertinent art. 4. Considering objective evidence present in the application indicating obviousness or non-obviousness. Claims 1 -2 , 6-8 , 12- 1 4, 18 is/are rejected under 35 U.S.C. 103 as being unpatentable over SARFERAZ (US Pub. No.: 2021-0241168 ) in view of RAJASEKAR (US Pub. No.: 2022-0230091 ). As per Claim 1 SARFERAZ discloses A system comprising ( Figs. 1-12 [Abstract] ) : a memory storing processor-executable program code ( Figs. 1-12 [0010-0012] ) ; a processing unit to execute the processor-executable program code to cause the system to ( Figs. 1-12 [0010-0012] ) : receive an instruction to check compatibility of an application executing on an application server with a machine learning scenario ( Figs. 1- 10 and in at least Fig. 12 for check as compatibility / like-versions must be satisfied [0081] [0094-0095] ) , the machine learning scenario comprising a machine learning model and a training pipeline ( Figs. 1- 10 training pipeline 1040 [0081, 0083] and in at least Fig. 12 ML scenarios [0094] ) ; perform a prerequisite check associated with the machine learning scenario and the application ( Figs. 1-12 [0066] pre-requisite checks 911 for ML scenario in the business domain and encapsulated applications 913, 915, etc. as in Figs. 7-8 for scenarios 930 [0081] [0094] ) ; SARFERAZ does not disclose but RAJASEKAR discloses determine a first plurality of object instances associated with the machine learning scenario, each of the first plurality of object instances comprising logic executable to perform ( Figs. 1-5, 8-12 object instances 545 – ML scenario 532 [0057-0060] ) ; instruct the application server to execute the logic of the first plurality of object instances and return corresponding first results ( Figs. 1-5, 8-12 application servers 520, 540 – see at least operation for request to infer a value of a target – return results [005 7 -0060] [0069-0070] ) It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to include determine a first plurality of object instances associated with the machine learning scenario, each of the first plurality of object instances comprising logic executable to perform ; and instruct the application server to execute the logic of the first plurality of object instances and return corresponding first results as taught by RAJASEKAR into the system of SARFERAZ be cause of the benefit taught by RAJASEKAR to expand upon the ML scenario based system of SARFERAZ to include capturing, processing and analyzing multiple object instances per the machine learning scenario to expand and enhance said system with improvements in the same field of endeavor . As per Claim 2 SARFERAZ discloses A system according to claim 1, the processing unit to execute the processor-executable program code to cause the system to ( Figs. 1-12 [0010-0012] ) : perform a prerequisite check associated with the machine learning scenario and a machine learning service providing the machine learning scenario ( Figs. 1-10 and in at least Fig. 12 for check as compatibility / like-versions must be satisfied for application service [0081] [0094-0095] ) ; SARFERAZ does not disclose but RAJASEKAR discloses determine a second plurality of object instances associated with the machine learning scenario, each of the second plurality of object instances comprising logic executable to perform ( Figs. 1-5, 8-12 object instances of various object types [0024] [0041-0042] - object instances 545 per segment with a plurality of segments – ML scenario 532 [0057-0060] ) ; and instruct the machine learning service to execute the logic of the second plurality of object instances and return corresponding second results ( Figs. 1-5, 8-12 application servers 520, 540 – return results first/second dependent upon type of instance [0041-0042] [0057-0060] [0069-0070] ) ( The motivation that applied in Claim 1 applies equally to Claim 2 ) As per Claim 6 SARFERAZ discloses A system according to claim 1, wherein the prerequisite checks comprise a data quality check and a data quantity check ( Figs. 1-12 pre-requisite checks 911 quality and quantity check [0066] [0074] [0079-0081] ) As per Claim 7 SARFERAZ discloses A method comprising ( Figs. 1-12 [0010-0012] ) : receiving an instruction to check compatibility of an application executing on an application server with a machine learning scenario ( See said analysis for Claim 1 ) , the machine learning scenario comprising a machine learning model and a training pipeline ( See said analysis for Claim 1 ) ; perform a prerequisite check associated with the machine learning scenario and the application ( See said analysis for Claim 1 ) SARFERAZ does not disclose but RAJASEKAR discloses determin ing a first plurality of object instances associated with the machine learning scenario, each of the first plurality of object instances comprising logic executable to perform ( See said analysis for Claim 1 ) ; instruct ing the application server to execute the logic of the first plurality of object instances and return corresponding first results ( See said analysis for Claim 1 ) . As per Claim 8 SARFERAZ discloses A method according to claim 7, further comprising: perform a prerequisite check associated with the machine learning scenario and a machine learning service providing the machine learning scenario ( See said analysis for Claim 2 ) ; SARFERAZ does not disclose but RAJASEKAR discloses determining a second plurality of object instances associated with the machine learning scenario, each of the second plurality of object instances comprising logic executable to perform ( See said analysis for Claim 2 ) ; instructing a second object executor on the machine learning service to execute the logic of the second plurality of object instances and return corresponding second results ( See said analysis for Claim 2 ) . As per Claim 12 SARFERAZ discloses A method according to claim 7, wherein the prerequisite checks comprise a data quality check and a data quantity check ( Figs. 1-12 pre-requisite checks 911 quality and quantity check [0066] [0074] [0079-0081] ) . As per Claim 13 SARFERAZ discloses A non-transitory medium storing processor-executable program code executable by a processing unit of a computing system to cause the computing system to ( Figs. 1-12 [0010-0012] ) : receive an instruction to check compatibility of an application executing on an application server with a machine learning scenario ( See said analysis for Claim 1 ) , the machine learning scenario comprising a machine learning model and a training pipeline ( See said analysis for Claim 1 ) ; perform a prerequisite check associated with the machine learning scenario and the application ( See said analysis for Claim 1 ) ; SARFERAZ does not disclose but RAJASEKAR discloses an instruction from an operator ( Figs. 1-2, 6-7 [0012-0013] [0033] [0041-0044] ) ; determine a first plurality of object instances associated with the machine learning scenario ( See said analysis for Claim 1 ) , each of the first plurality of object instances comprising logic executable ( See said analysis for Claim 1 ) by a first object executor executing in the application server to ( Figs. 1-2, 6-7 executor management system 210 [0012-0013] [0030-0034] [0041-0044]) ; instruct the first object executor ( Figs. 1-2, 6-7 executor management system 210 [0012-0013] [0030-0034] [0041-0044]) to execute the logic of the first plurality of object instances and receive first results corresponding to the executed logic ( See said analysis for Claim 1 ) from the first object executor ( Figs. 1-2, 6-7 executor management system 210 [0012-0013] [0033] [0041-0044] ) (The motivation that applied in Claim 1 applies equally to Claim 13) As per Claim 14 SARFERAZ discloses A medium according to claim 13, the program code executable by a processing unit of a computing system to cause the computing system to ( See said analysis for Claim 13 ) : perform a prerequisite check associated with the machine learning scenario and a machine learning service providing the machine learning scenario ( See said analysis for Claim 2) SARFERAZ does not disclose but RAJASEKAR discloses determine a second plurality of object instances associated with the machine learning scenario ( See said analysis for Claim 2) , each of the second plurality of object instances comprising logic executable ( See said analysis for Claim 2) by a second object executor executing ( Figs. 1-2, 6-7 executor management system 210 per object instance [0012-0013] [0030-0034] [0041-0044]) to instruct the second object executor service ( Figs. 1-2, 6-7 executor management system 210 per object instance [0012-0013] [0030-0034] [0041-0044]) to execute the logic of the second plurality of object instances ( See said analysis for Claim 2 ) ; and receive second results corresponding to the executed logic of the second plurality of object instances ( Figs. 1-2, 6-7 executor management system 210 [0012-0013] [0033] [0041-0044] ) from the second object executor ( Figs. 1-2, 6-7 executor management system 210 per object instance [0012-0013] [0030-0034] [0041-0044]) (The motivation that applied in Claim 2 applies equally to Claim 14) . As per Claim 18 SARFERAZ discloses A medium according to claim 13, wherein the prerequisite checks comprise a data quality check and a data quantity check ( Figs. 1-12 pre-requisite checks 911 quality and quantity check [0066] [0074] [0079-0081] ) . Claims 5, 11, 17 is/are rejected under 35 U.S.C. 103 as being unpatentable over SARFERAZ (US Pub. No.: 2021-0241168) in view of RAJASEKAR (US Pub. No.: 2022-0230091), as applied in Claims 1-2, 6-8, 12-14, 18 , and further in view of SARFERAZ (US 2021-0342738, hereinafter ‘738). As per Claim 5 SARFERAZ discloses A system according to claim 1, wherein SARFERAZ and RAJASEKAR do not disclose but ‘738 discloses one of the first plurality of object instances is dependent on another one of the first plurality of object instances ( Figs. 1-2, 23-27 interdependencies [0057-0058] [0210-0212] ) It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to include one of the first plurality of object instances is dependent on another one of the first plurality of object instances as taught by ‘738 into the system of SARFERAZ and RAJASEKAR be cause of the benefit taught by ‘738 to further specify related improvements and features to both systems whereby both systems are in the same field of endeavor and would naturally benefit from expansion of techniques and capabilities in combining said related systems . As per Claim 11 SARFERAZ discloses A method according to claim 7, wherein SARFERAZ and RAJASEKAR do not disclose but ‘738 discloses one of the first plurality of object instances is dependent on another one of the first plurality of object instances ( See said analysis for Claim 5 ) . As per Claim 17 SARFERAZ discloses A medium according to claim 13, wherein SARFERAZ and RAJASEKAR do not disclose but ‘738 discloses one of the first plurality of object instances is dependent on another one of the first plurality of object instances ( See said analysis for Claim 5 ) . Allowable Subject Matter Claims 3 -4 , 9 -10 , 15 -16 is/are objected to as being dependent upon the 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 , and but for outstanding rejections under 35 U.S.C. section 101 and section 112(b) . Claims 3 -4 , 9 -10 , 15 -16 is/are allowed , but for outstanding rejections under 35 U.S.C. section 101 and section 112(b) . The following is an examiner’s statement of reasons for allowance: As per Claim 3 the prior art of record either alone or in reasonable combination fails to teach or suggest “ A system according to claim 2, the processing unit to execute the processor-executable program code to cause the system to: determine, prior to instructing the application server and based on one of the first plurality of object instances, that the prerequisite check performed by execution of the logic of the one of the first plurality of object instances requires a first parameter value; determine, prior to instructing the application server and based on one of the second plurality of object instances, that the prerequisite check performed by execution of the logic of the one of the second plurality of object instances requires a second parameter value; and request the first and second parameter values from an operator, wherein instruction of the application server to execute the logic of the first plurality of object instances and return corresponding first results comprises instruction of the application server to execute the logic of the one of the first plurality of object instances based on the first parameter value and instruction of the machine learning service to execute the logic of the one of the second plurality of object instances based on the second parameter value " These limitations in combination with the other limitations of the independent claim are thus deemed allowable . As per Claim 4 the prior art of record either alone or in reasonable combination fails to teach or suggest “ A system according to claim 1, the processing unit to execute the processor-executable program code to cause the system to: determine, prior to instructing the application server and based on one of the first plurality of object instances, that the prerequisite check performed by execution of the logic of the one of the first plurality of object instances requires a parameter value; and request the parameter value from an operator, wherein instruction of the application server to execute the logic of the first plurality of object instances and return corresponding first results comprises instruction of the application server to execute the logic of the one of the first plurality of object instances based on the parameter value " These limitations in combination with the other limitations of the independent claim are thus deemed allowable . As per Claim 9 the prior art of record either alone or in reasonable combination fails to teach or suggest “ A method according to claim 8, further comprising: determining, prior to instructing the application server and based on one of the first plurality of object instances, that the prerequisite check performed by execution of the logic of the one of the first plurality of object instances requires a first parameter value; determining, prior to instructing the application server and based on one of the second plurality of object instances, that the prerequisite check performed by execution of the logic of the one of the second plurality of object instances requires a second parameter value; and requesting the first and second parameter values from an operator, wherein instructing the application server to execute the logic of the first plurality of object instances and return corresponding first results comprises instructing the first object executor to execute the logic of the one of the first plurality of object instances based on the first parameter value and instructing the second object executor to execute the logic of the one of the second plurality of object instances based on the second parameter value " These limitations in combination with the other limitations of the independent claim are thus deemed allowable . As per Claim 10 the prior art of record either alone or in reasonable combination fails to teach or suggest “ A method according to claim 7, further comprising: determining, prior to instructing the application server and based on one of the first plurality of object instances, that the prerequisite check performed by execution of the logic of the one of the first plurality of object instances requires a parameter value; and requesting the parameter value from an operator, wherein instructing the application server to execute the logic of the first plurality of object instances and return corresponding first results comprises instructing the application server to execute the logic of the one of the first plurality of object instances based on the parameter value " These limitations in combination with the other limitations of the independent claim are thus deemed allowable . As per Claim 15 the prior art of record either alone or in reasonable combination fails to teach or suggest “ A medium according to claim 14, the program code executable by a processing unit of a computing system to cause the computing system to: determine, prior to instructing the application server and based on one of the first plurality of object instances, that the prerequisite check performed by execution of the logic of the one of the first plurality of object instances requires a first parameter value; determine, prior to instructing the application server and based on one of the second plurality of object instances, that the prerequisite check performed by execution of the logic of the one of the second plurality of object instances requires a second parameter value; and request the first and second parameter values from the operator, wherein instruction of the first object executor to execute the logic of the first plurality of object instances comprises instruction of the first object executor to execute the logic of the one of the first plurality of object instances based on the first parameter value and instruction of the second object executor to execute the logic of the one of the second plurality of object instances based on the second parameter value " These limitations in combination with the other limitations of the independent claim are thus deemed allowable . As per Claim 16 the prior art of record either alone or in reasonable combination fails to teach or suggest “ A medium according to claim 13, the program code executable by a processing unit of a computing system to cause the computing system to: determine, prior to instructing the application server and based on one of the first plurality of object instances, that the prerequisite check performed by execution of the logic of the one of the first plurality of object instances requires a parameter value; and request the parameter value from an operator, wherein instruction of the first object executor to execute the logic of the first plurality of object instances comprises instruction of the first object executor to execute the logic of the one of the first plurality of object instances based on the parameter value " These limitations in combination with the other limitations of the independent claim are thus deemed allowable . The closest prior art of record SARFERAZ discloses for Claims 3 -4 , 9 -10 , 15 -16 does not teach all the elements in combination with the other limitations of the independent claim. SARFERAZ discloses only discloses receiving an instruction to check compatibility of an application executing on an application server with a machine learning scenario such that the machine learning scenario comprises a machine learning model and a training pipeline. The prior art also discloses performing a prerequisite check associated with the machine learning scenario and the application. Any comments considered necessary by applicant must be submitted no later than the payment of the issue fee and, to avoid processing delays, should preferably accompany the issue fee. Such submissions should be clearly labeled “Comments on Statement of Reasons for Allowance.” Conclusion Any inquiry concerning this communication or earlier communications from the examiner should be directed to FILLIN "Examiner name" \* MERGEFORMAT EILEEN M ADAMS whose telephone number is 571-270-3688. The examiner can normally be reached on Monday-Friday from 8:30-5:00 EST. If attempts to reach the examiner by telephone are unsuccessful, the examiner's supervisor, William Vaughn can be reached on (571) 272-3922. The fax phone number for the organization where this application or proceeding is assigned is 571-270-4688. Information regarding the status of an application may be obtained from the Patent Application Information Retrieval (PAIR) system. Status information for published applications may be obtained from either Private PAIR or Public PAIR. Status information for unpublished applications is available through Private PAIR only. For more information about the PAIR system, see http://pair-direct.uspto.gov. Should you have any questions on access to the Private PAIR system, contact the Electronic Business Center (EBC) at 866-217-9197 (toll- free). If you would like assistance from a USPTO Customer Service. Representative or access to the automated information system, call 800-786-9199 (IN USA OR CANADA) or 571-272-1000. /EILEEN M ADAMS/ Primary Examiner, Art Unit 2481