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 A filing date of 10/14/2022 is acknowledge. Claims 1 – 20 are pending. Claims 1 – 20 will be allowed after they are amended to correct claim informalities in section Claim Objections and overcome 101 rejections. Claim Objections Claim s 1 – 20 are objected to because of the following informalities: Claim 1 Line 18; should remove comma after “the container image chunk” for claim clarity. Amend l ine s 20 – last line as follow for claim clarity: --for the container image chunks having a the negative classification, generating a notification output specifying the container image chunks having the negative classification , their corresponding container image performance characteristic classifications, and the one or more reasons for the modification of the chunk. -- Claim 2 Line 1; insert --the-- before “extracting” , and change “a container image file” to --the container image file--. Line 5; change “container image files” to --the container image file--. Limitations (lines 6 – 7) “wherein the execution of the natural language processing computer model identifies a plurality of boundary indicators in the container image file ” seems redundant and should be removed because limitations (lines 3 – 5) “ executing, on the container image file, a natural language processing computer model, trained on a vocabulary database corresponding to a programming language of the container image file, to identify boundary indicators in container image files ” already identifies a plurality of boundary indicators in the container file. Claim 3 The claim is dependent claim of claim 2; therefore, it inherits issues of claim 2. Claim 4 Last line; insert --the-- before “boundary indicators” Claim 5 Line 4; remove “file” in front of “chunks” Line s 4 – 5 ; “ the at least one corresponding container image performance characteristic classifications ” lacks antecedent basis. Claim 6 The claim is dependent claim of claim 1; therefore, it inherits issues of claim 1. Claim 7 Line 6; insert --the-- before “container” and change “a negative” to --the negative--. Line 7; change “a reason for modification” to --the one or more reasons for the modification--. Remove “identified” after “based on the ” Claim 8 Line 2; remove “identified” before “one or more entries” and insert comma after “base” Line 3; change “the container image file” to --the container image chunks having a negative classification-- . Last line; insert --at least one-- before “recommendation” Claim 9 Line 2; insert --at least one-- before “recommendation” Claim 10 Line 1; insert --the-- before “extracting” Claim 1 1 Lines 6 ; “the container image chunks” lack antecedent basis. Line 20; should remove comma after “the container image chunk” for claim clarity. And, insert --in the at least subset-- after “the container image chunk” . Line 21 ; “the chunk” lacks antecedent basis. Amend lines 2 2 – last line as follow for claim clarity: -- for the container image chunks having a the negative classification, generat e a notification output specifying the container image chunks having the negative classification , their corresponding container image performance characteristic classifications, and the one or more reasons for the modification of the chunk. -- Last line; “the chunk” lacks antecedent basis. Claim 1 2 Line s 1 and 2 ; insert --the-- before “extracting”, and change “a container image file” to --the container image file--. Line 5; change “container image files” to --the container image file--. Claim 13 The claim is dependent claim of claim 12; therefore, it inherits issues of claim 12. Claim 1 4 Last line; insert --the-- before “boundary indicators” Claim 1 5 Line 4; remove “file” in front of “chunks” Lines 5 – 6 ; “ the at least one corresponding container image performance characteristic classifications ” lacks antecedent basis. Claim 1 6 The claim is dependent claim of claim 11; therefore, it inherits issues of claim 11. Claim 1 7 Line 5 ; “the container image chunk” lacks antecedent basis. Line 7 ; insert --the-- before “container” and change “a negative” to --the negative--. Line 8 ; change “a reason for modification” to --the one or more reasons for the modification--. “the chunk” lacks antecedent basis. Remove “identified” before “ one or ” Claim 1 8 Line 3 ; remove “identified” before “one or more entries” and insert comma after “base” . Line 4 ; change “the container image file” to -- the container image chunks having a negative classification --. Last line; insert --at least one-- before “recommendation” Claim 1 9 Last l ine; insert --at least one-- before “recommendation” Claim 20 Lines 7 ; “the container image chunks” lack antecedent basis. Line 21 ; should remove comma after “the container image chunk” for claim clarity. And, insert --in the at least subset-- after “the container image chunk”. Line 2 2 ; “the chunk” lacks antecedent basis. Amend lines 2 3 – last line as follow for claim clarity: -- for the container image chunks having a the negative classification, generat e a notification output specifying the container image chunks having the negative classification , their corresponding container image performance characteristic classifications, and the one or more reasons for the modification of the chunk. -- Last line; “the chunk” lacks antecedent basis. Appropriate correction is required. 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 a judicial exception (i.e., a law of nature, a natural phenomenon, or an abstract idea) without significantly more. Claim 1 Step 1 The claim is statutory because it is directed to a method. Step 2A, prong 1 The claim recites limitations “ inputting each container image chunk … , … classifies container image chunks, with regard to a plurality of container image performance characteristic classifications, into at least one corresponding container image performance characteristic classification ; determining whether the at least one corresponding container image performance characteristic classification is a negative classification; in response to the at least one corresponding container image performance characteristic classification being a negative classification, identifying one or more entries in a knowledge base having patterns of content matching content in the container image chunk, to identify one or more reasons for modification of the chunk specified in the one or more entries ” The se limitations are directed to steps for classifying container image chunks, recognizing negative classification, and identifying entries to identify reasons for modification . These steps fall into category of mental process as they rely on human observation , evaluation , and judgment to classify container image chunks, recognize negative classification, and identify reasons. Step 2A, prong 2 The claim recites additional limitations “ extracting a set of container image chunks from a container image file …; inputting each container image chunk into one or more trained machine learning computer models …; for the container image chunks having a negative classification, generating a notification output … ” These additional limitations obtain container image chunk from the container image file, deliver the container image chunk to the machine learning computer models, and generate a notification output. These additional limitations constitute insignificant extra solution activit ies that are not integrated into a practical application. The claim recites additional element s “ one or more trained machine learning computer models and a knowledge base . ” The additional element s are recited as high level of generality and used as a tool to perform the limitations. Thus, the additional element is not indicative of an integration into a practical application. Steps 2B The claim as a whole is not amounted to significantly more than the judicial exception. Claim 1 is directed to an abstract idea. Therefore, claim 1 is not patent eligible. Analysis of claims 2 – 10 as follow: Claim 2 The claim recites limitations “ executing, on the container image file, a natural language processing computer model, … to identify boundary indicators in container image files … ; and generating the set of container image chunks based on the identified boundary indicators in the container image file . ” The limitation s , as drafted, identify boundary indicators from the container image file and generate the set of container image chunks based on the boundary indicators . T he limitation s , under its broadest reasonable interpretation, covers performance of the limitation in the mind as they rely on human observation and evaluation to identify the boundary indicators and the set of container image chunks based on the boundary indicators. Thus, they are not integrated into a practical application because they do not impose any meaningful limits on practicing the abstract idea. So, it does not include any additional element that is sufficient to amount to significantly more than the judicial exception. Claim 3 The claim recites limitations “ the boundary indicators comprise at least one of key words, key phrases, or a predetermined chunk size .” The claim merely defines the boundary indicators. The limitation constitutes insignificant extra solution activit ies that are not integrated into a practical application. Claim 4 The claim recites limitation “ the natural language processing computer model is configured with a set of pre-defined rules that are implemented to identify key terms or key phrases in the programming language of the container image file as boundary indicators .” The claim merely defines configurations for the natural language processing computer model . The limitation is insignificant extra solution activit ies that are not integrated into a practical application. Claim 5 The claim recites limitation “ the one or more trained machine learning computer models comprises an ensemble of a plurality of trained machine learning computer models, and wherein each machine learning computer model in the ensemble is trained to classify container image file chunks into a different one of the at least one corresponding container image performance characteristic classifications .” The limitation merely defines the one or more trained machine learning computer models . The limitation is insignificant extra solution activit ies that are not integrated into a practical application. Claim 6 The claim recites limitation “ the container image performance characteristic classifications comprise a build time classification, a reproducibility classification, and a reliability classification .” The limitation merely defines the container image performance characteristic classifications . The limitation is insignificant extra solution activit ies that are not integrated into a practical application. Claim 7 The claim recites limitation s “storing, for each container image chunk, a corresponding container image performance characteristic classification … in a container image chunk data structure; and storing, in association with container image chunks having a negative classification, a reason for modification of the chunk … in the container image chunk data structure …” The limitation s collect and store container image performance characteristic classification and reason in container image chunk data structure . The limitation s are insignificant extra solution activit ies that are not integrated into a practical application. Claim 8 The claim recites limitations “generating, from the identified one or more entries in the knowledge base at least one recommendation for modifying the container image file; and outputting the recommendation as part of the notification output.” The limitations generate and output recommendation for modification of container image file . The limitations are insignificant extra solution activit ies that are not integrated into a practical application. Claim 9 The claim recites limitations “ automatically executing the recommended modification to the container image file to generate a modified container image file .” The limitations generate container image file. The limitations are insignificant extra solution activit ies that are not integrated into a practical application. Claim 10 The claim recites limitations “ … extracting the set of container image chunks such that each container image chunk has a measure of overlap of adjacent container image chunks in a sequence of container image chunks of the container image file .” The limitations extract the set of container image chunks . The limitations are insignificant extra solution activit ies that are not integrated into a practical application. Claims 11 and 20 Claim 11 is statutory because it is directed to a product. Claim 20 is statutory because it is directed to a device. These claims recite limitations in the same manner as claim 1; therefore, they are also rejected for the same reasons. C laim 11 recites additional elements “ a computer readable storage medium and a data processing system.” The additional elements are recited as high level of generality and used as a tool to perform the limitations. Thus, the additional element is not indicative of an integration into a practical application. C laim 20 recites additional elements “ at least one processor and at least one memory .” The additional elements are recited as high level of generality and used as a tool to perform the limitations. Thus, the additional element is not indicative of an integration into a practical application. Claims 12 – 19 Claims 12 – 19 recite limitations in the same manners as claims 2 – 9 respectively; therefore, they are also rejected for the same reasons. Allowable Subject Matter Claims 1 – 20 will be allowed after they are amended to correct claim informalities in section Claim Objections and overcome 101 rejections. Claim 1 LUO et al. (P ub. No. US 2019/0347121 A 1) t eaches “A method, in a data processing system, for improving performance of container images, the method comprising: extracting a set of container image chunks f rom a container image file, wherein each of the container image chunks represent a sequence of code in the container image file; inputting each container image chunk into one or more trained machine learning computer models , wherein each trained machine learning computer model classifies container image chunks, with regard to a plurality of container image performance characteristic classifications , into at least one corresponding container image performance characteristic classification ; and for each container image chunk, in at least a subset of the container image chunks: determining whether the at least one corresponding container image performance characteristic classification is a negative classification; in response to the at least one corresponding container image performance characteristic classification being a negative classification, identifying one or more entries in a knowledge base having patterns of content matching content in the container image chunk, to identify one or more reasons fo r modification of the chunk specified in the one or more entries ; and for the container image chunks having a negative classification, generating a notification output specifying the container image chunks, their corresponding container image performance characteristic classifications, and the reasons for modification of the chunk .” Nadgowda et al. (Patent No. US 11,163,552 B2) teaches “inputting each container image chunk i nto one or more trained machine learning computer models, wherein each trained machine learning computer model classifies container image chunks , with regard to a plurality of container image performance characteristic classifications, into at least one corresponding container image performance characteristic classification ; and for each container image chunk, in at least a subset of the container image chunks : determining whether the at least one corresponding container image performance characteristic classification is a negative classification; in response to the at least one corresponding container image performance characteristic classification being a negative classification, identifying one or more entries in a knowledge base having patterns of content matching content in the container image chunk, to identify one or more reasons for modification of the chunk specified in the one or more entries; and for the container image chunks having a negative classification, generating a notification output specifying the container image chunks, their corresponding container image performance characteristic classifications, and the reasons for modification of the chunk .” Sethi et al. (Pub. No. US 2023/0176837 A1) teaches “ in response to the at least one corresponding container image performance characteristic classification being a negative classification , identifying one or more entries in a knowledge base having patterns of content matching content in the container image chunk, to identify one or more reasons for modification of the chunk specified in the one or more entries ” Griffin et al. (Pub. No. US 2019/0310872 A1) teaches “ in response to the at least one corresponding container image performance characteristic classification being a negative classification, identifying one or more entries in a knowledge base having patterns of content matching content in the container image chunk, to identify one or more reasons for modification of the chunk specified in the one or more entries .” But LUO , Nadgowda , Sethi and Griffin do not teach limitations “ inputting each container image chunk into one or more trained machine learning computer models, wherein each trained machine learning computer model classifies container image chunks, with regard to a plurality of container image performance characteristic classifications, into at least one corresponding container image performance characteristic classification; and for each container image chunk, in at least a subset of the container image chunks: determining whether the at least one corresponding container image performance characteristic classification is a negative classification; in response to the at least one corresponding container image performance characteristic classification being a negative classification, identifying one or more entries in a knowledge base having patterns of content matching content in the container image chunk, to identify one or more reasons for modification of the chunk specified in the one or more entries; and for the container image chunks having a negative classification, generating a notification output specifying the container image chunks, their corresponding container image performance characteristic classifications, and the reasons for modification of the chunk . ” The limitations are not present in the prior art of record , would not have been obvious, and present subject matter that is novel. Thus, claim 1 is allowed. Claims 11 and 20 These claims recite limitations in the same manner as claim 1; therefore, they are also allowed for the same reasons. Conclusion Any inquiry concerning this communication or earlier communications from the examiner should be directed to FILLIN "Examiner name" \* MERGEFORMAT CUONG V LUU whose telephone number is FILLIN "Phone number" \* MERGEFORMAT (571)270-1733 . The examiner can normally be reached FILLIN "Work Schedule?" \* MERGEFORMAT 6:30 AM - 3:00 PM . Examiner interviews are available via telephone, in-person, and video conferencing using a USPTO supplied web-based collaboration tool. To schedule an interview, applicant is encouraged to use the USPTO Automated Interview Request (AIR) at http://www.uspto.gov/interviewpractice. If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, FILLIN "SPE Name?" \* MERGEFORMAT Hyung S. Sough can be reached at FILLIN "SPE Phone?" \* MERGEFORMAT (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 published or unpublished applications may be obtained from Patent Center. Unpublished application information in Patent Center is available to registered users. To file and manage patent submissions in Patent Center, visit: https://patentcenter.uspto.gov. Visit https://www.uspto.gov/patents/apply/patent-center for more information about Patent Center and https://www.uspto.gov/patents/docx for information about filing in DOCX format. For additional questions, contact the Electronic Business Center (EBC) at 866-217-9197 (toll-free). If you would like assistance from a USPTO Customer Service Representative, call 800-786-9199 (IN USA OR CANADA) or 571-272-1000. /CUONG V LUU/ Examiner, Art Unit 2192 /S. Sough/ SPE, Art Unit 2192