| CPC G06F 8/75 (2013.01) [G06F 8/10 (2013.01); G06F 8/34 (2013.01); G06F 8/423 (2013.01); G06F 8/433 (2013.01); G06F 8/72 (2013.01); G06F 16/319 (2019.01); G06F 18/2113 (2023.01); G06F 18/2178 (2023.01); G06F 40/284 (2020.01); G06N 3/04 (2013.01)] | 20 Claims |

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1. A method, comprising:
training a machine learning model to predict to which one among a plurality of program architecture layer classifications a program code component module belongs, including by:
forming a training dataset, wherein:
the training dataset includes a training program code component module and an assignment of the training program code component module to a program architecture layer classification included in the plurality of program architecture layer classifications;
the program architecture layer classification included in the plurality of program architecture layer classifications identifies a functionality within a computer program that the training program code component module performs;
the plurality of program architecture layer classifications includes a first layer corresponding to a first architectural role and a second layer corresponding to a second architectural role; and
using the training dataset to train the machine learning model; and
outputting the trained machine learning model.
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