DETAILED ACTION
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 .
This action is in response to response filed on 2/02/2026. This action is FINAL.
Claim Rejections - 35 USC § 112
The following is a quotation of the first paragraph of 35 U.S.C. 112(a):
(a) IN GENERAL.—The specification shall contain a written description of the invention, and of the manner and process of making and using it, in such full, clear, concise, and exact terms as to enable any person skilled in the art to which it pertains, or with which it is most nearly connected, to make and use the same, and shall set forth the best mode contemplated by the inventor or joint inventor of carrying out the invention.
The following is a quotation of the first paragraph of pre-AIA 35 U.S.C. 112:
The specification shall contain a written description of the invention, and of the manner and process of making and using it, in such full, clear, concise, and exact terms as to enable any person skilled in the art to which it pertains, or with which it is most nearly connected, to make and use the same, and shall set forth the best mode contemplated by the inventor of carrying out his invention.
Claims 4-6, 11-13 and 18-19 are rejected under 35 U.S.C. 112(a) or 35 U.S.C. 112 (pre-AIA ), first paragraph, as failing to comply with the written description requirement. The claim(s) contains subject matter which was not described in the specification in such a way as to reasonably convey to one skilled in the relevant art that the inventor or a joint inventor, or for applications subject to pre-AIA 35 U.S.C. 112, the inventor(s), at the time the application was filed, had possession of the claimed invention.
Claim 4 claims, “wherein the plurality of instructions further causes the one or more processors to enable the software developer to at least one of clarify the completed issue report via the issue tracker or update the completed issue report to describe a strategy for completing the software engineering task.”. The examiner has not been able to find anywhere in the specification that teaches or suggests “to enable the software developer to at least one of clarify the completed issue report via the issue tracker or update the completed issue report to describe a strategy for completing the software engineering task.”.
Claim 5 claims, ”wherein the plurality of instructions further causes the one or more processors to predict, by the machine-learning model, another completion of the completed issue report, based on a modification of the predicted completion of the issue report as received from the issue tracker associated with the software developer.”. The examiner has not been able to find anywhere in the specification that teaches or suggests the above claimed limitation.
Claim 6 claims, “cause the one or more processors to output the other completion of the completed issue report to the issue tracker associated with the software developer.”. The examiner has not been able to find anywhere in the specification that teaches or suggests the above claimed limitation.
Claims 11-13 and 18-19 contain similar limitations to claims 4-6 and are therefore rejected for similar reasons.
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 1-20 are rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without significantly more. Claim 1 recites, “transform context data…”, “predict…the completion of the incomplete issue report”, and “predict, by the machine learning model…source code changes for completing the software engineering task…”. The limitations of “transform” and “predict” as drafted are functions that, under their broadest reasonable interpretation, recite the abstract idea of a mental process. The limitations encompass a human mind carrying out the function through observation, evaluation, judgment and /or opinion, or even with the aid of pen and paper. Thus, this limitation recites and falls within the “Mental Processes” grouping of abstract ideas under Prong 1.
Under Prong 2, this judicial exception is not integrated into a practical application. The claim recites the following additional elements “retrieve context data”, “output a completed issue report” and “display a selectable and expandable compact representation of the predicted source code”. The additional elements of “retrieve context data” is an insignificant pre solution activity. The additional elements of “output” and “display”, are recited at a high level of generality and thus are insignificant extra-solution activities. See MPEP 2106.05(g). Further, the limitation “One or more processors” is recited at a high-level of generality such that it amounts no more than mere instructions to apply the exception using generic computer, and/or mere computer components, MPEP 2106.05(f). Accordingly, the additional elements do not integrate the recited judicial exception into a practical application and the claim is therefore directed to the judicial exception
Under Step 2B, the claims do not include additional elements that are sufficient to amount to significantly more than the judicial exception. As discussed above with respect to integration of the abstract idea into a practical application, the additional elements of “One or more processors” amounts to no more than mere instructions, or generic computer/computer components to carry out the exception, for the limitations of “output a completed issue report” and “display a selectable and expandable compact representation…” are identified as well-understood, routine, conventional activities (2106.05(d)) and for the limitations of “retrieve context data”, the courts have identified mere data gathering is also well-understood, routine and conventional activity. Se MPEP 2106.05(d) and MPEP 2106.05(f). The recitation of generic computer instruction and computer components to apply the judicial exception, and the well-understood, routine, conventional activities do not amount to significantly more, thus, cannot provide an inventive concept. Accordingly, claim 1 is not patent eligible under 35 USC 101.
Claim 2, Further defines the completed issue report. The additional elements are neither a practical application under prong 2, nor an inventive concept under step 2B.
Claim 4 claims, “clarify the completed issue report” or “update the completed issue report”. The steps of “clarify” and “update” are additional limitations of the abstract idea “Mental Process”. Nothing in the claimed limitations preclude the steps form being performed in the mind. The additional elements are neither a practical application under prong 2, nor an inventive concept under step 2B.
Claim 5, the “predict” step of claim 5 is an additional limitation of the abstract idea “Mental Process”. Nothing in the claimed limitation precludes the step from being performed in the mind. The additional elements are neither a practical application under prong 2, nor an inventive concept under step 2B.
Claim 6, claims a further outputting step that is identified as well-understood, routine, conventional activity (2106.05(d))
Claim 7, The additional elements are neither a practical application under prong 2, nor an inventive concept under step 2B.
Claims 8-9, 11-16 and 18-20, claim similar limitations to claim 1-7 and are therefore rejected for the same reasons.
The Applicant is advised to amend the claims to be similar to Core Wireless Licensing S.A.R.L., v. LG Electronics, Inc., 880 F.3d 1356, 1362-63, 125 USPQ2d 1436, 1440-41 (Fed. Cir. 2018), which was deemed an improved user interface for electronic devices that displays an application summary of unlaunched applications, where the particular data in the summary is selectable by a user to launch the respective application. The recited specification appears to give an understanding that the trained model of the claimed invention, when analyzing the code, it would predict source code locations that are ripe for correction due to possible mistakes, validation errors or due to completion. The issues are relayed to the code editor for fixing via underlining, bolding, etc. See specification paragraphs 0026-0033. Currently, the claims give a BRI of general display of a accepted completion report which is not considered to make a practical application of the claims or amount to significantly more.
Claim Rejections - 35 USC § 103
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 (i.e., changing from AIA to pre-AIA ) 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 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.
Claims 1-2,7-9,14-16 and 20 are rejected under 35 U.S.C. 103 as being unpatentable over Bahrami et al. (US 2020/0204431 A1) further in view of Childs et al. (US 9,430,194-B1).
As per claim 1 (Amended), Bahrami et al. teaches the invention as claimed including, “A system that assists with writing issue reports that describe software engineering tasks and issue information, the system comprising:
one or more processors; and
a non-transitory computer readable medium storing a plurality of instructions, which when executed, cause the one or more processors to:
retrieve context data that establishes a context for a software engineering task, in response to receiving one of an implicit request or an explicit request an issue report, the issue report describing
transform the context data to be compatible with a data format used to train a machine-learning model to assist with performing software engineering tasks;”
Bahrami et al. teaches, a ticket interface that is configured to receive information from the user and generate a ticket inquiry. The inquiry may include data and information related to an issue of the computing system (context). A REST API enables a ticket interface to communicate with the resolution system. The REST API reformats (transforms) the information provided by the user in a particular format that is acceptable by the resolution system (0038).
Bahrami et al. teaches, after the models are trained and tested (machine learning), the resolution system may then address new ticket inquiries (context data for task) that are submitted from the computer system. The resolution system may retrieve (implicit/explicit request) a ticket inquiry (context data) from the computer system and use the models to determine a problem statement representative of an issue of the ticket inquiry. The resolution system may then predict a solution to the issue (0017). The resolution module may generate a problem statement representative of the issue of the ticket inquiry (request). The resolution module may predict a solution to the generated problem statement (0046). The ticket inquiry may be received directly from the ticket interface, which may include a live user ticket interface or GUI (0065). The ticket inquiry (context)is received by a classifier module. The classifier module may be configured to detect the features of the computer system in the ticket of the ticket inquiry. Detection of the features (context) may be based on an analysis of text of the ticket inquiry. A priority feature can be detected. A problem statement is generated representative of the issue of the ticket. The problem statement may be associated with or specific to the features (context) of the ticket inquiry (0066-0067). Also see figure 2.
“predict, by the machine-learning model using the transformed context data, the completion of the
output a completed issue report based on the predicted completion of the issue report;”
The resolution module may generate a problem statement (completed issue report) representative of the issue of the ticket inquiry (request). The resolution module may predict a solution to the generated problem statement (0046).
The resolution system may retrieve (implicit/explicit request) a ticket inquiry (context data) from the computer system and use the models to determine a problem statement representative of an issue of the ticket inquiry. The resolution system may then predict a solution to the issue (0017). The resolution module may generate a problem statement representative of the issue of the ticket inquiry (request). The resolution module may predict a solution to the generated problem statement (0046).
A problem statement is generated representative of the issue of the ticket. The problem statement may be associated with or specific to the features (context) of the ticket inquiry (0066-0067)
predict, by the machine learning model based upon the completed issue report, source code changes to complete the software engineering task; and”
.”
Bahrami et al. teaches, the solutions models are configured to predict a solution to the problem statement (0068). The solution may include a set of directions to resolve the ticket or issue (0069). Also see figure 6. The solution may include a set of directions to resolve the ticket or issue and /or one or more characteristics. The set of directions may include specific portions of code, instructions, subroutines, human-readable instructions, and the like (0069). Also see figures 3 and 5. The resolution module may generate a problem statement representative of the issue of the ticket inquiry (request) (0046).
Bahrami et al. teaches the resolution system may provide a technical solution to issues that occur (0027). The directions may include specified code portions, instruction, subroutines, human-readable instructions, and the like (0069). However, Bahrami et al. does not explicitly appear to teach, “display a selectable and expandable compact representation of the predicted source code changes for completing the software engineering task based upon the completed issue report.
Childs et al. teaches graphically representing source code in a visual display that takes up less screen real-estate and is easy to read. Responsive to receiving user selections, embodiments of the present invention can generate and toggle between different views to expand or collapse blocks of source code (column 20, lines 30-36).
It would have been obvious to one of ordinary skill in the art before the effective filing date to modify Bhrami et al. with Childs et al. Bharami et al. teaches a predicted technical solution can include instructions including specified code portions. Childs et al. teaches an improved way of displaying source code which includes allowing one to select code to expand or collapse blocks. It would have been obvious to apply this known improvement to Bharami et al, to allow it to display code in a way that takes up less scree real-estate and is easier to read.
As per claim 2 (Amended), Bahrami et al. and Troutman et al. further teach, “The system of claim 1, wherein outputting the completed issue report comprises identifying at least one of a deletion or a replacement of a part of the
The resolution system may retrieve (implicit/explicit request) a ticket inquiry (context data) from the computer system and use the models to determine a problem statement representative of an issue of the ticket inquiry (0017). The resolution module may generate a problem statement representative of the issue of the ticket inquiry (request) (0046). A problem statement is generated representative of the issue of the ticket. The problem statement may be associated with or specific to the features (context) of the ticket inquiry (0066-0067). The examiner states that if the problem statement (completed issue report) is generated from the ticket inquiry then it if deleting/replacing the ticket inquiry with the problem statement.
As per claim 7, Bahrami et al. further teaches, “The system of claim 1, wherein the issue information comprises at least one of whether an issue is reproducible, a requirement to reproduce the issue, or a current priority associated with the issue.”
Bahrami et al. teaches, the ticket inquire is received by a classifier module. The classifier module may be configured to detect the features of the computer system in the ticket of the ticket inquiry. Detection of the features may be based on an analysis of text of the ticket inquiry. A priority feature can be detected. A problem statement is generated representative of the issue of the ticket. The problem statement may be associated with or specific to the features of the ticket inquiry (0066-0067).
The problem ticket can contain, operating system that the user is using, the relevant software that the user is using, a relevant program version of the software that is being utilized, an error code that has been encountered etc. (requirements to reproduce the issue) (column 6, lines 1-10).
As per claims 8-9, 14, 15-16 and 20¸ contain similar limitations to claims 1-2 and 7 and are therefore rejected for similar reasons.
Response to Arguments
Applicant's arguments filed 2/2/2026 have been fully considered but they are not persuasive.
Regarding 35 U.S.C 101
Applicants amendments do not overcome the current rejection. Please see the above rejection in light of new limitations.
Regarding 35 U.S.C 103
Applicant argues “Bahrami does not disclose requesting a predicted completion of an issue report or “context” data.”. The examiner respectfully disagrees. As claimed “in response to receiving one of an implicit request or an explicit request for a predicted completion”. Therefore, as claimed the request can be implicit and therefore implied. As stated above, Bahrami et al. teaches, a ticket interface that is configured to receive information from the user and generate a ticket inquiry. The inquiry may include data and information related to an issue of the computing system (context). A REST API enables a ticket interface to communicate with the resolution system. The REST API reformats (transforms) the information provided by the user in a particular format that is acceptable by the resolution system (0038). Therefore, the sending the ticket inquiry that contains context information to the resolution system is implicitly requesting a predicted completion.
Applicant further argues, “Bahrami does not disclose “transforming the context data to be compatible with a data format used to train a machine-learning model to assist with performing the software engineering tasks.” And “use the transformed context data to predict the completion of an issue report. The examiner disagrees. As stated in the above rejection, Bahrami et al. teaches, a ticket interface that is configured to receive information from the user and generate a ticket inquiry. The inquiry may include data and information related to an issue of the computing system (context). A REST API enables a ticket interface to communicate with the resolution system. The REST API reformats (transforms) the information provided by the user in a particular format that is acceptable by the resolution system (0038). Therefore, the context information of the ticket inquiry is reformatted to a format that is acceptable by the resolution system. The resolution system contains the trained models therefore, the reformatted ticket inquiry will now be acceptable to the models of the resolution system. Bahrami et al. further teaches, after the models are trained and tested (machine learning), the resolution system may then address new ticket inquiries (context data for task) that are submitted from the computer system. The resolution system may retrieve (implicit/explicit request) a ticket inquiry (context data) from the computer system and use the models to determine a problem statement representative of an issue of the ticket inquiry. The resolution system may then predict a solution to the issue (0017). The resolution module may generate a problem statement representative of the issue of the ticket inquiry (request). The resolution module may predict a solution to the generated problem statement (0046). Therefore, the reformatted ticket inquiry is sent to a trained mode to generate a problem statement (completed issue report) that is then sent to another trained model to predict a solution for the problem statement. For these reasons the current rejection stands.
Conclusion
Applicant's amendment necessitated the new ground(s) of rejection presented in this Office action. Accordingly, THIS ACTION IS MADE FINAL. See MPEP § 706.07(a). Applicant is reminded of the extension of time policy as set forth in 37 CFR 1.136(a).
A shortened statutory period for reply to this final action is set to expire THREE MONTHS from the mailing date of this action. In the event a first reply is filed within TWO MONTHS of the mailing date of this final action and the advisory action is not mailed until after the end of the THREE-MONTH shortened statutory period, then the shortened statutory period will expire on the date the advisory action is mailed, and any nonprovisional extension fee (37 CFR 1.17(a)) pursuant to 37 CFR 1.136(a) will be calculated from the mailing date of the advisory action. In no event, however, will the statutory period for reply expire later than SIX MONTHS from the mailing date of this final action.
Any inquiry concerning this communication or earlier communications from the examiner should be directed to MARK A GOORAY whose telephone number is (571)270-7805. The examiner can normally be reached Monday - Friday 10:00am - 6:00pm.
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If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, Lewis Bullock can be reached at 571-272-3759. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
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/MARK A GOORAY/ Examiner, Art Unit 2199
/LEWIS A BULLOCK JR/ Supervisory Patent Examiner, Art Unit 2199
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