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 .
Non-Final Office Action
DETAILED ACTION
Examiner’s Notes
(a) Claim date: 04/14/2023.
(b) Priority date: 08/15/2022.
(c) Invention: EDA tool using Machine learning for design feature optimization. Several claimed improvements seem enigmatic.
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.Claims 1-2, 4-12, 14-20, are rejected under 35 U.S.C. 102(a)(1) as being anticipated by the prior art of record “Bhunia” <US 20210097220 A1>.(As to claim 1, 7 and 15, Bhunia discloses):1. A computer-implemented method comprising:
under control of a computer hardware processor configured with computer executable instructions, receiving, via a first graphical user interface [Fig. 3],
a design file including at least a plurality of nets [0048: “the existing malicious design alteration storage device(s) 207 may include, without limitation, a plurality of trigger nets and payload nets”];
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generating, from the design file, a converted design file [Fig. 1, “New Trojan” is a converted version of the design file originated from “Trojan Templates” 135];
determining a feature vector based on the converted design file [Fig. 1, 150, Note: the original design (135) is being verified with the help of necessary feature vector (trigger, (150)];
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applying a machine learning model [Fig.6, 640], wherein input to the machine learning model includes at least the feature vector [Fig. 6, 625], wherein output of the machine learning model includes at least a plurality of ports [Fig. 6, 615], wherein each port of the plurality of ports is associated with a subset of the plurality of nets [Fig. 6, 615];
storing, in a data storage medium, the plurality of ports [Fig. 4, 420]; and
causing presentation, in a second graphical user interface, of at least a first port from the plurality of ports [Fig. 1, the “New Trojan” is a representation of first port (i.e. the original ports shown in 135). Note: it is understood by an ordinary skilled that each level of the display of EDA tool would require numerous graphical user interfaces, including the “second”].
(As to claim 2, 8, 16, Bhunia discloses):2. The computer-implemented method of Claim 1, wherein storing the plurality of ports further comprises:
generating a first data object including at least the first port; and storing, in the data storage medium, the first data object [042: “a computer-readable storage medium to perform certain steps or operation”].
(As to claim 4, 10, 18, Bhunia discloses):
4. The computer-implemented method of Claim 2, further comprising:
receiving, via the second graphical user interface, user input associated with the first port [Fig.1, 135];
generating a modified first port based at least in part on the user input; and storing, in the data storage medium, the modified first port [Fig. 1, “New Trojan”, which depicted to have been stored in a new storage medium with resect to the old medium (135)].
(As to claim 5 Bhunia discloses):
5. The computer-implemented method of Claim 1, wherein a first data format of the design file is different than a second data format of the converted design file [Fig. 645, which represent converted design after ML and showing different data format (see the curve), compared to the original (610)].
(As to claim 6, 12, Bhunia discloses):
6. The computer-implemented method of Claim 1, wherein each port of the plurality of ports is associated with a port type [Fig. 6, 615, 625 and 635, notice that the port types are presented differently].
(As to claim 9, Bhunia discloses):
9. The computer-implemented method of Claim 8, further comprising:
receiving, via the second graphical user interface, a user selection of the first data object [Fig. 6, 610]; and
adding the first data object to a data model, wherein the first data object is connected to a second data object in the data model and the first port of the first data object is compatible with a second port of the second data object [Fig. 6, 615 and 620].
(As to claim 11, 19, Bhunia discloses):
11. The computer-implemented method of Claim 10, further comprising:
generating an updated training data set based on the modified first port, wherein generating the updated training set further includes at least [Fig. 6, 645]:
adding a label associated with the modified first port to a training data set [Fig. 6, 630, “data labeling”]; and
training a second machine learning model based on the updated training data set [Fig. 6, 640].
(As to claim 14, Bhunia discloses):
14. The computer-implemented method of Claim 7, wherein the first machine learning model corresponds to at least one of a random forest model, a gradient boosted decision tree model, a support vector machine, or a neural network [Para. 88, 89. Note: “machine learning model” are well known to be corresponding the type of models mentioned].
(As to claim 17, Bhunia discloses):
17. The system of Claim 16, wherein the one or more computer hardware processors are configured to execute further computer-executable instructions to at least [Fig. 3]:
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receive, via the second graphical user interface, a user selection of the first data object [Fig. 8, 820]; and add the first data object to a data model representing a circuit [Fig. 8, 825], wherein the first data object is connected to a second data object in the data model [Fig. 8, 810] and the first port of the first data object is compatible with a second port of the second data object [Fig. 8, 810 and 820. Note: First, the claimed limitation is ambiguous, second, the data for the first (810) and the second (820) are compatible, as depicted using a bidirectional arrow].
(As to claim 20, Bhunia discloses):
20. The system of Claim 15, wherein determining the feature vector further includes at least: determining a plurality of features based on a first net in the design file, wherein the plurality of features includes at least: (i) a first feature for a name of the first net, (ii) a second feature based on the name of the first net, (iii) a third feature indicating a same type for the first net and a second net in the design file, (iv) a fourth feature for a connection between the first net and a first component or a first pin, and (v) a fifth feature based on a name of a pin connected to the first net [Fig. 6 depicting various features and nets combination. Note: claim limitation “first, second … fifth features and nets” are interpreted as many features and many nets, which is depicted in Fig. 6].
Allowable Subject Matter
The following claims would be allowable if all rejections/objections cited in this office action (if any) are overcome and rewritten to include all of the limitations of the base claim and any intervening claims.The reason for this allowance is: the claimed subject matter could not have been anticipated or obviated using any prior arts.Allowable claims are: 3 and 13.
Conclusion
The prior art made of record in the form PTO-892 are not relied upon is considered pertinent to applicant's disclosure.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). 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.Contact information:Any inquiry concerning this communication or earlier communications from the examiner should be directed to MOHAMMED ALAM whose telephone number is (571) 270-1507, email address: [mohammed.alam@uspto.gov] and fax number (571) 270-2507. The examiner can normally be reached on 10AM to 4PM (EST), Monday to Friday. If attempts to reach the examiner by telephone are unsuccessful, the Examiner's Supervisor, JACK CHIANG can be reached on (571) 272-7483. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300./Mohammed Alam/Primary Examiner, Art Unit 2851