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 is in response to Application filed 09/29/23. Claims 1 – 20 has been amended and is pending.
Claim Rejections - 35 USC § 102
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.
Claim(s) 1 – 20 is/are rejected under 35 U.S.C. 102(a)(1) as being anticipated by Bronevetsky US 20230176838 A1.
Regarding claims 1, 8 and 15, Bronevetsky anticipates a computer-implemented method/A system (with processor and memory having instructions) /A computer program product comprising a computer readable storage medium (See FIG. 8 in prior art) comprising:
providing a team feature set for a team to a machine learning model, the team comprising at least two members [0023, shows a first team with multiple team members] and [0031, using a machine learning model]; wherein the team feature set input into the machine learning model comprises at least one of a team profile, a team operations, a team code, a team historical recommendations, or a team tag [0023, see team members making edits to codes and operations as well as directives], wherein using the machine learning model, a recommendation for the team, the recommendation being related to computer execution to perform a task [0003 shows, “…comprises a recommendation to implement the second edit…”, and 0024 shows utilizing machine learning models and edits of source code snippets]; and
in response to determining the recommendation for the team, causing the recommendation to be rendered to the team [0057, see “… GUI that may be presented to a user to recommend one or more auto edits……”] ;
wherein the recommendation comprises a code snippet; and causing execution of the code snippet to perform the task on a computer [0063 – 0068, shows making recommendation and executing].
Regarding claims 2, 9 and 16, the computer-implemented method/system and CRM of claims 1, 8 and 15 wherein:
the team feature set comprises attributes that characterize the team, the attributes accounting for the at least two members [0023 the attributes accounting for the team members is equivalent to, “..nodes that correspond to each member of a programming team…”].
Regarding claims 3, 10 and 17, the computer-implemented method/system and CRM of claims 1, 8 and 15, wherein:
the team feature set characterizes the team and another team feature set characterizes another team; and the machine learning model is configured to determine another recommendation for the another team [0023. Shows code edits and directives/recommendations for other team members] when the another team feature set is input into the machine learning model
Regarding claims 4, 11 and 18, the computer-implemented method/system and CRM of claims 1, 8 and 15,, wherein the machine learning model is initiated based on a trigger, the trigger being related to at least one of team operations, a new code snippet, an updated code snippet, a new reference architecture template, and updated architecture template [0003 – 0005, shows various code snippets e.g. First and second source code snippets].
Regarding claims 5, 12 and 19, the computer-implemented method/system and CRM of claims 1, 8 and 15, the computer-implemented method of claim 1, wherein the recommendation further comprises at least one of a code snippet and a reference architecture template [0058, see transformation template and code snippets].
Regarding claims 6, 13 and 20, the computer-implemented method/system and CRM of claims 1, 8 and 15,, the computer-implemented method of claim 1, wherein causing the recommendation to be rendered to the team comprises causing the recommendation to display in a graphical user interface for the team [0057, see “… GUI that may be presented to a user to recommend one or more auto edits…”].
Regarding claims 7 and 14, the computer-implemented method/system and CRM of claims 1, and 8, the computer-implemented method of claim 1, the machine learning model is trained on a plurality of team feature sets in which the plurality of team feature sets comprise at least one of a plurality of team profiles, a plurality of team operations, a plurality of team codes, a plurality of team historical recommendations, or a plurality of team tags [0063 – 0068, shows making recommendation and executing also see 0052 for the machine learning].
Response to Arguments
Applicant’s arguments with respect to claim(s) 1 – 20 have been considered but are moot because the new ground of rejection does not rely on any reference applied in the prior rejection of record for any teaching or matter specifically challenged in the argument.
Correspondence information
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 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.”
Any inquiry concerning this communication or earlier communications from the examiner should be directed to Chuck Kendall whose telephone number is 571-272-3698. The examiner can normally be reached on 10:00 am - 6:30pm.
If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, Hyung Sough can be reached on 571-272-6799. 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 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 questions on access to the Private PAIR system, contact the Electronic Business Center (EBC) at 866-217-9197 (toll-free).
/Chuck O Kendall/
Primary Examiner, Art Unit 2192
Prosecution Insights