DETAILED ACTION
A request for continued examination under 37 CFR 1.114 was filed in this application after appeal to the Patent Trial and Appeal Board, but prior to a decision on the appeal. Since this application is eligible for continued examination under 37 CFR 1.114 and the fee set forth in 37 CFR 1.17(e) has been timely paid, the appeal has been withdrawn pursuant to 37 CFR 1.114 and prosecution in this application has been reopened pursuant to 37 CFR 1.114. Applicant’s submission filed on 12/26/2025 has been entered.
Claims 1, 11/12, 17, and 20 appear to have been amended. Claims 1-23 are pending in the case. Claims 1, 17, and 20 are independent claims.
Examiner’s Notes
The markup required under 37 C.F.R. § 1.121(c)(2) is inaccurate in several places, including the duplication of claim 11 (the second one apparently should have corresponded to the original claim 12) and marking the status of amended claim 20 as “(Previously Presented).” Currently there does not appear to be any deceptive intent, however future arguments that rely upon past inaccurate markup may be considered deceptive in violation of MPEP § 2001 and 37 C.F.R. § 1.56.
The numbering of claims (i.e. two claim 11s and then jumping to claim 13) is not in accordance with 37 CFR 1.126. The presented claims must be numbered consecutively beginning with the number next following the highest numbered claims previously presented. A series of singular dependent claims is permissible in which a dependent claim refers to a preceding claim which, in turn, refers to another preceding claim. A claim which depends from a dependent claim should not be separated by any claim which does not also depend from said dependent claim. It should be kept in mind that a dependent claim may refer to any preceding independent claim. See MPEP § 608.01(n) and 37 CFR 1.75(g): “(t)he least restrictive claim should be presented as claim number 1, and all dependent claims should be grouped together with the claim or claims to which they refer…”
These amendments do not comply with 37 CFR 1.121, which explicitly states that “All claims being currently amended in an amendment paper shall be presented in the claim listing, indicate a status of "currently amended," and be submitted with markings to indicate the changes that have been made relative to the immediate prior version of the claims. The text of any added subject matter must be shown by underlining the added text. The text of any deleted matter must be shown by strike-through except that double brackets placed before and after the deleted characters may be used to show deletion of five or fewer consecutive characters. The text of any deleted subject matter must be shown by being placed within double brackets if strike-through cannot be easily perceived.”
These amendments do not comply with 37 CFR 1.121, which explicitly states that “the status of every claim must be indicated after its claim number by using one of the following identifiers in a parenthetical expression: (Original), (Currently amended), (Canceled), (Withdrawn), (Previously presented), (New), and (Not entered).”
Claim Objections
Claims 1-23 are objected to because of the following informalities:
Claim 1:
Line 8 recites “the set of strategies” where “the set of provisional strategies” was apparently intended.
This same issue applies to all the dependent claims that repeat the same error, including claims 2, 5, 7, 9, (former) 12, and 13-16.
Claim 11:
As outlined above, there are now two claim 11s. It appears that former claim 12 was mistakenly changed to a second claim 11.
Claim 17:
Line 7 recites “the set of strategies” where “the set of provisional strategies” was apparently intended.
This same issue applies to all the dependent claims that repeat the same error, including claim 18.
Claim 20:
Line 8 recites “the set of strategies” where “the set of provisional strategies” was apparently intended.
This same issue applies to all the dependent claims that repeat the same error, including claims 21-23.
Appropriate correction is required.
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 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.
This application currently names joint inventors. In considering patentability of the claims the examiner presumes that the subject matter of the various claims was commonly owned as of the effective filing date of the claimed invention(s) absent any evidence to the contrary. Applicant is advised of the obligation under 37 CFR 1.56 to point out the inventor and effective filing dates of each claim that was not commonly owned as of the effective filing date of the later invention in order for the examiner to consider the applicability of 35 U.S.C. 102(b)(2)(C) for any potential 35 U.S.C. 102(a)(2) prior art against the later invention.
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 1-7 and 10-20 are rejected under 35 U.S.C. § 103 as being unpatentable over Budurean et al. (US Patent Application Pub. No. 2018/0267885, hereinafter “Budurean”) in view of Ang (US Patent Application Pub. No. 2019/0018675, hereinafter “Ang”).
As to independent claims 1, 17, and 20, Budurean shows a method for discovering one or more processes for automation by examining user interfaces of one or more application programs [¶ 09], an apparatus [¶ 102], and a concomitant non-transitory computer-readable storage medium [¶ 49], comprising:
obtaining a set of views [e.g. one or more screenshots (¶ 05)] of user interfaces for an application and a set of metadata associated with the set of views [“A system generates screenshots of a graphical user interface (GUI) of an application that is displayed by target devices testing the application. Each screenshot includes an image of the GUI and metadata indicative of elements of the GUI present in the image or a state of the application or target device when the image is generated. {…}” (Abstract)];
applying a set of provisional strategies to a subset of the set of views of the user interfaces to generate groupings [e.g. clusters] of user interfaces, wherein each strategy of the set of strategies comprises one or more rules for identifying user interfaces [“{…} the example test system may automatically group screenshots from among the different sets into clusters of similar screenshots. A cluster may include screenshots that share similar elemental structures as defined by the metadata of the screenshots, as opposed to necessarily sharing common image features. In other words, a cluster may include screenshots of a GUI that is defined, in the metadata of the screenshots, by a particular elemental structure {…}” (¶ 06)];
determining whether a specified one of the groupings of user interfaces is associated with a first user interface of the set of views of user interfaces; and in response to determining that the specified grouping is associated with the first user interface, generating an application strategy [e.g., notification/indication of grouping] based on the set of provisional strategies [“{…} The system determines, based on the metadata of a screenshot from a first set of the screenshots and the metadata of a screenshot from a second set of the screenshots, whether the screenshots are similar and if so, the system assigns the screenshot from the second set of screenshots to a cluster that includes the screenshot from the first set of screenshots. The system outputs an indication of the cluster (e.g., a notification or graphical indication) indicative of the similarity or discrepancy between the screenshots.” (Abstract)],
wherein generating the application strategy includes:
[Budurean shows generating the application strategy based on the set of provisional strategies in response to identifying the first user interface with a predetermined threshold level of accuracy (¶¶ 36-38 & 61-62).],
wherein the application strategy being configured to identify occurrences of the first user interface in user interfaces of one or more applications [The application strategy is configured to identify occurrences (GUI elements/characteristics) of the first user interface in user interfaces of one or more applications (¶¶ 34 & 55-56).].
Budurean does not appear to explicitly recite a “promoting the set of provisional strategies to the application strategy” as apparently intended. In an analogous art, Ang shows:
wherein generating the application strategy [a set of application-related tasks to be performed by a bot (¶ 06)] includes: promoting the set of provisional strategies to the application strategy in response to identifying the first user interface with a predetermined threshold level of accuracy [Ang shows the operability to promote a set of provisional strategies to a “live” or “verified” application strategy in response to identifying the first user interface with a predetermined threshold level of accuracy (¶¶ 11, 18, & 51)],
wherein the application strategy being configured to identify occurrences of the first user interface in user interfaces of one or more applications [The application strategy is configured to identify occurrences of the first user interface in user interfaces of one or more applications (¶¶ 08-11, 18, & 51)].
One of ordinary skill in the art, having the teachings of Budurean and Ang before them prior to the effective filing date of the claimed invention, would have been motivated to incorporate Ang’s “promoting” capabilities into Budurean. The rationale for doing so would have been to avoid releasing a subpar service until it can be ensured that it will behave as intended, which in turn would ultimately “alleviate the need for programmers to code and test automated software controls {and} enable an end user to enjoy automated control of various software programs without the need to manually program such controls” (Ang: ¶ 24) and also “enables any updates to the machine's control software to be automatically detected, assessed, and for a new automated control to be introduced without the need for human intervention (or intervention at only the highest levels). This automated process could potentially save enormous sums of money and eliminate or minimize the need for costly skilled workers (e.g., software automation engineers)” (Ang: ¶ 25). Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to combine the teachings of Budurean and Ang (hereinafter, the “Budurean-Ang” combination) in order to obtain the invention as recited in claims 1, 17, and 20.
As to dependent claim 2, Budurean-Ang further shows:
wherein each strategy in the set of strategies comprises a set of parameters and the set of parameters comprises one or more of: a set of tabs that should be in the set of views; a set of user interface elements that should be in the set of views [“{…} one or more elements of the GUI (e.g., a layout, a button, a background, a drawer or sidebar, or another component of the GUI) {…}” (Budurean: ¶ 34)]; a set of labels for the set of user interface elements [“{…} the metadata of one of screenshots 164 may include information about a graphical button of a GUI as well as the size, position, location, color, label, or other information about the graphical button” (Budurean: ¶ 34)]; a first set of words that should be in the set of views [e.g. text that should be in the set of views (Budurean: ¶ 43)]; a second set of words that should not be in the set of views [e.g. text that should not be in the set of views (Budurean: ¶ 74)]; a set of colors that should be in the set of views [“{…} the metadata of one of screenshots 164 may include information about a graphical button of a GUI as well as the size, position, location, color, label, or other information about the graphical button” (Budurean: ¶ 34)]; and a set of thresholds for grouping views [“{…} The application test system may group similar screenshots based on certain structural thresholds for similarity{…}” (Budurean: ¶ 04)].
As to dependent claims 3 and 19, Budurean-Ang further shows:
in response to determining that the specified grouping is not associated with the first user interface, applying another set of strategies to another subset of the set of views to generate another set of groupings of user interfaces [“{…} If the highest similarity score does not satisfy the minimum scoring threshold, clustering module 284 may treat that screenshot as an unmatched screenshot and create a new cluster within clusters 290 that includes the unmatched screenshot. When adding a screenshot to a cluster or creating a new cluster, clustering module 284 may append an indication of the screenshots to the third layer of the cluster.” (Budurean: ¶ 61)
“Responsive to determining that the first and second screenshots are not similar (306, NO), ATS 260 may create a new cluster that includes the second screenshot (312), and may output, for display, a graphical indication of the second cluster. The graphical indication of the second cluster may include the portion of the image of the second screenshot, the graphical indication of the second cluster may be different than the graphical indication of the first cluster, and the second cluster may be different than the first cluster. For example, clustering module 284 may create a new cluster that includes an indication of the second screenshot so that when UI module 280 causes a graphical indication of the clusters to be displayed (e.g., as part of a graphical user interface of a service accessed by a client computing device such as computing device 110), the graphical indication of the new cluster that includes the second screenshot may includes at least a portion of the image of the second screenshot.” (Budurean: ¶ 71)
For even further context/examples of applying another set of strategies to another subset of views to generate another set of groupings of user interfaces, see also Budurean: ¶¶ 36-38, 68, & 76.].
As to dependent claim 4, Budurean-Ang further shows:
applying the application strategy to the set of views of user interfaces for the application [e.g. outputting/executing the results of positively determining that the specified grouping/cluster is associated with the first user interface/screenshot (Budurean: ¶¶ 42 & 61)].
As to dependent claim 5, Budurean-Ang further shows:
wherein applying the set of strategies to the subset of the set of views comprises: generating one or more of a set of vectors and a set of hashes based on the subset of the set of views [e.g. applying the set of strategies to the subset of views comprises: generating at least a set of vectors (similarity score/Hamming distance parameters) based on the subset of the set of views (Budurean: ¶¶ 36-39 & 61-64)].
As to dependent claims 6 and 18, Budurean-Ang further shows:
wherein generating one or more of the set of vectors and the set of hashes comprises: generating the set of vectors based on a machine learning model and the subset of the set of views, wherein the set of vectors represent one or more of visual features and textual features of the subset of the set of views [e.g. generating the set of vectors, which represent either visual and/or textual features of the subset of views (Budurean: ¶¶ 34 & 43), based on a machine learning model (such as a similarity score machine learning model and/or a Hamming distance-based machine learning model) and the subset of views (Budurean: ¶¶ 36-39 & 61-64)].
As to dependent claim 7, Budurean-Ang further shows:
wherein applying the set of strategies to the subset of views comprises: determining clusters of visual features based on the set of vectors; and determining the groupings of user interfaces based on the clusters of visual features [applying the set of strategies to the subset of views also comprises determining clusters of visual features (Budurean: ¶¶ 36 & 39) based on the set of vectors and determining the set of groupings based on said clusters (Budurean: ¶¶ 34-39, 43, & 61-64)].
As to dependent claim 10, Budurean-Ang further shows:
wherein determining whether the specified grouping is associated with the first user interface comprises: providing the groupings of user interfaces to a user; and determining, based on user input received in response to providing the groupings of user interfaces, whether the specified grouping is associated with the first user interface [e.g. the groupings/clusters may be output/provided to a user, with which the user may then interact with, thus confirming said grouping (Budurean: ¶¶ 30, 33, & 60)].
As to dependent claim 11, Budurean-Ang further shows:
wherein determining whether the specified grouping is associated with the first user interface comprises: determining whether the specified grouping is associated with the first user interface based on a machine learning model [e.g. determining whether the specified grouping is associated with the first user interface may be based on a machine learning model (such as a similarity score machine learning model and/or a Hamming distance-based machine learning model) (Budurean: ¶¶ 36-39 & 61-64)].
As to dependent claim 12, Budurean-Ang further shows:
generating one or more identifiers for the subset of the set of views based on the set of strategies [e.g. the subset of views/screenshots has one or more identifiers generated based on the strategy utilized to identify their association (Budurean: ¶¶ 55-59)].
As to dependent claim 13, Budurean-Ang further shows:
wherein the set of strategies are applied to the subset of the set views sequentially [the set of strategies may be applied to subset of views sequentially at least in the sense that one strategy may be applied after another (Budurean: ¶¶ 57, 61, & 71)].
As to dependent claim 14, Budurean-Ang further shows:
wherein a plurality of the set of strategies are applied to the subset of the set of views in parallel [the set of strategies may be applied to the subset of views in parallel/simultaneously (Budurean: ¶ 66)].
As to dependent claim 15, Budurean-Ang further shows:
wherein the applying the set of strategies to the subset of the set of views of the user interfaces comprises: applying a first strategy to the subset of the set views to identify a first grouping of user interfaces; and applying a second strategy to the first grouping of user interfaces to determine the specified grouping [multiple clustering strategies may be applied to the same subset of views to identify a given grouping of user interfaces (Budurean: ¶¶ 34-39 & 61-64)].
As to dependent claim 16, Budurean-Ang further shows:
wherein the applying the set of strategies to the subset of the set of views of the user interfaces comprises: applying a first strategy to first portions of the subset of the set of views; and applying a second strategy to second portions of the subset of the set of views [different strategies may be applied to different screenshots and/or portions of the screenshots (Budurean: ¶¶ 28, 33-39, 41, & 69)].
Claims 8-9 and 21-23 are rejected under 35 U.S.C. § 103 as being unpatentable over Budurean-Ang in further view of Xue et al. (US Patent Application Pub. No. 2013/0301935, hereinafter “Xue”).
As to dependent claim 8, Budurean-Ang shows how its clustering/grouping strategies/rules include taking into account each view of the subset of views as well as text detected in the subset of views (Budurean: ¶¶ 07, 43, & 74). Nonetheless, even though Budurean-Ang explicitly shows determining Hamming distances (which were well known in the art at the time to be done via corresponding hashes, as will be corroborated below) between its subsets of views for grouping purposes (Budurean: ¶ 39), Budurean-Ang does not appear to explicitly recite actively hashing said contents, and thus does not appear to explicitly recite the alternative of parent claim 5 of “generating a set of hashes” as apparently intended. In an analogous art, Xue shows:
wherein generating the set of hashes comprises one or more of: hashing each view of the subset of the set of views; and hashing text detected in the subset of the set of views [“A user may submit an image and request from a server one or more images that are similar to the submitted image. The server may generate an image signature based on the content of the submitted image. The server may conduct a Hash operation to the image signature to generate one or more Hash values. These Hash values may be used to identify one or more candidate images similar to the image in a Hash table. These candidate images may be sorted and outputted to the user based on similarity. The similarity between each of the candidate images and the image may be determined using at least one of Hamming distance or Euclidean distance.” (Xue: Abstract)].
One of ordinary skill in the art, having the teachings of Budurean, Ang, and Xue before them prior to the effective filing date of the claimed invention, would have been motivated to incorporate Xue’s hashing techniques into Budurean-Ang’s existing subset of views (including the text detected in said subset of views). The rationale for doing so would have been that at the time, it would have been desirable to avoid the scenario when “conventional technologies of similar image retrieval {like Budurean-Ang} may present some problems (e.g., poor compatibility and fault tolerance problems) {such as when} two images that have identical content but saved in different formats (e.g., bmp, jpeg, png, or gif) may be considered as different images” (Xue: ¶ 03), especially when Budurean-Ang already explicitly taught utilizing the same Hamming distance-based techniques (Budurean: ¶ 39) as Xue (Xue: ¶ 06). Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to combine the teachings of Budurean, Ang, and Xue (hereinafter, the “Budurean-Ang-Xue” combination) in order to obtain the invention as recited in claim 8.
As to dependent claim 9, Budurean-Ang-Xue further shows:
wherein applying the set of strategies to the subset of the set of views comprises: determining the set of groupings based on hamming distances between pairs of hashes in the set of hashes [“A user may submit an image and request from a server one or more images that are similar to the submitted image. The server may generate an image signature based on the content of the submitted image. The server may conduct a Hash operation to the image signature to generate one or more Hash values. These Hash values may be used to identify one or more candidate images similar to the image in a Hash table. These candidate images may be sorted and outputted to the user based on similarity. The similarity between each of the candidate images and the image may be determined using at least one of Hamming distance or Euclidean distance.” (Xue: Abstract)
“Other clustering techniques may be used by developer service module 162 to cluster similar screenshots taken by different test target devices 166. For example, developer service module 162 may apply hamming distance techniques to metadata associated with screenshots taken by test target device 166A and test target device 166N. Developer service module 162 may determine a hamming distance between two sets of metadata associated with screenshots taken by test target devices 166A and 166N and determine that the similar screenshots are those with the smallest hamming distance between them. Other clustering techniques may be used as well. In short, developer service module 162 takes metadata from screenshots 164 as input, and applies clustering techniques to the metadata to generate as output, clusters or groupings of screenshots 164 taken between different target test devices 166.” (Budurean: ¶ 39)].
As to dependent claim 21, Budurean-Ang shows:
wherein to apply the set of strategies to the subset of the set of views of the user interfaces to generate the groupings of user interfaces, the processing device is configured to at least: generate a set of vectors {…} [e.g. applying the set of strategies to the subset of views comprises: generating at least a set of vectors (similarity score/Hamming distance parameters) based on the subset of the set of views (Budurean: ¶¶ 36-39 & 61-64)]
Nonetheless, even though Budurean-Ang explicitly shows determining Hamming distances (which were well known in the art at the time to be done via corresponding hashes, as will be corroborated below) between its subsets of views for grouping purposes (Budurean: ¶ 39), Budurean-Ang does not appear to explicitly recite actively hashing said contents, and thus does not appear to explicitly recite to “generate {..} a set of hashes” as apparently intended. In an analogous art, Xue shows:
wherein generating the set of hashes comprises one or more of: hashing each view of the subset of the set of views; and hashing text detected in the subset of the set of views [“A user may submit an image and request from a server one or more images that are similar to the submitted image. The server may generate an image signature based on the content of the submitted image. The server may conduct a Hash operation to the image signature to generate one or more Hash values. These Hash values may be used to identify one or more candidate images similar to the image in a Hash table. These candidate images may be sorted and outputted to the user based on similarity. The similarity between each of the candidate images and the image may be determined using at least one of Hamming distance or Euclidean distance.” (Xue: Abstract)].
One of ordinary skill in the art, having the teachings of Budurean, Ang, and Xue before them prior to the effective filing date of the claimed invention, would have been motivated to incorporate Xue’s hashing techniques into Budurean-Ang’s existing grouping functionalities. The rationale for doing so would have been that at the time, it would have been desirable to avoid the scenario when “conventional technologies of similar image retrieval {like Budurean-Ang} may present some problems (e.g., poor compatibility and fault tolerance problems) {such as when} two images that have identical content but saved in different formats (e.g., bmp, jpeg, png, or gif) may be considered as different images” (Xue: ¶ 03), especially when Budurean-Ang already explicitly taught utilizing the same Hamming distance-based techniques (Budurean: ¶ 39) as Xue (Xue: ¶ 06). Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to combine the teachings of Budurean, Ang, and Xue (hereinafter, the “Budurean-Ang-Xue” combination) in order to obtain the invention as recited in claim 21.
As to dependent claim 22, Budurean-Ang-Xue further shows:
wherein to generate the set of vectors and/or the set of hashes, the processing device is configured to at least: generate the set of vectors based on a machine learning model and the subset of the set of views, wherein the set of vectors represent at least one or more of visual features and textual features of the subset of the set of views [e.g. generating the set of vectors, which represent either visual and/or textual features of the subset of views (Budurean: ¶¶ 34 & 43), based on a machine learning model (such as a similarity score machine learning model and/or a Hamming distance-based machine learning model) and the subset of views (Budurean: ¶¶ 36-39 & 61-64)].
As to dependent claim 23, Budurean-Ang-Xue further shows:
in response to determining that the specified grouping is not associated with the first user interface, apply a second set of strategies to a second subset of views to generate a second set of groupings of user interfaces [“{…} If the highest similarity score does not satisfy the minimum scoring threshold, clustering module 284 may treat that screenshot as an unmatched screenshot and create a new cluster within clusters 290 that includes the unmatched screenshot. When adding a screenshot to a cluster or creating a new cluster, clustering module 284 may append an indication of the screenshots to the third layer of the cluster.” (Budurean: ¶ 61)
“Responsive to determining that the first and second screenshots are not similar (306, NO), ATS 260 may create a new cluster that includes the second screenshot (312), and may output, for display, a graphical indication of the second cluster. The graphical indication of the second cluster may include the portion of the image of the second screenshot, the graphical indication of the second cluster may be different than the graphical indication of the first cluster, and the second cluster may be different than the first cluster. For example, clustering module 284 may create a new cluster that includes an indication of the second screenshot so that when UI module 280 causes a graphical indication of the clusters to be displayed (e.g., as part of a graphical user interface of a service accessed by a client computing device such as computing device 110), the graphical indication of the new cluster that includes the second screenshot may includes at least a portion of the image of the second screenshot.” (Budurean: ¶ 71)
For even further context/examples of applying a second set of strategies to a second subset of views to generate a second set of groupings of user interfaces, see also Budurean: ¶¶ 36-38, 68, & 76.].
Response to Arguments
Applicant’s prior art arguments have been fully considered but are moot in view of the new grounds of rejection presented above.
Conclusion
It is noted that any citation to specific pages, columns, lines, or figures in the prior art references and any interpretation of the references should not be considered to be limiting in any way. A reference is relevant for all it contains and may be relied upon for all that it would have reasonably suggested to one having ordinary skill in the art. In re Heck, 699 F.2d 1331, 1332-33, 216 U.S.P.Q. 1038, 1039 (Fed. Cir. 1983) (quoting In re Lemelson, 397 F.2d 1006, 1009, 158 U.S.P.Q. 275, 277 (C.C.P.A. 1968)).
Any inquiry concerning this communication or earlier communications from the examiner should be directed to ALVARO R CALDERON IV whose telephone number is (571) 272-1818. The examiner can normally be reached on Monday - Friday (8:30am - 5pm).
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/ALVARO R. CALDERON IV/
Examiner
Art Unit 2171
/KIEU D VU/Supervisory Patent Examiner, Art Unit 2171