Software library usage optimization

Patent metadata

Field	Value
Publication number	US-2025077204-A1
Application number	US-202318458926-A
Country	US
Kind code	A1
Filing date	Aug 30, 2023
Priority date	Aug 30, 2023
Publication date	Mar 6, 2025
Grant date	—

Abstract

An example operation may include one or more of training a generative artificial intelligence (GenAI) model based on execution of the GenAI model on software libraries and descriptions of intent of the software libraries, receiving a first set of software libraries and a second set of software libraries, identifying a first software library within the first set of software libraries that includes redundant functionality with a second software library within the second set of software libraries based on execution of a generative artificial intelligence (GenAI) model on the first and second sets of libraries, and displaying an identifier of the first and second software libraries via a user interface.

First claim

What is claimed is:

1 . An apparatus comprising:
a processor configured to
train a generative artificial intelligence (GenAI) model based on execution of the GenAI model on software libraries and descriptions of intent of the software libraries,
receive a first set of software libraries and a second set of software libraries,
identify a first software library within the first set of software libraries that includes redundant functionality with a second software library within the second set of software libraries based on execution of a generative artificial intelligence (GenAI) model on the first and second sets of libraries, and
display an identifier of the first and second software libraries via a user interface.

2 . The apparatus of claim 1 , wherein the processor is configured to determine that the first software library and the second software library include the redundant functionality based on execution of the GenAI model on naming conventions of the first and second software libraries.

3 . The apparatus of claim 1 , wherein the processor is further configured to determine an intent of the first software library based on execution of the GenAI model on source code of the first software library and determine an intent of the second software library based on execution of the GenAI model on source code of the second software library.

4 . The apparatus of claim 3 , wherein the processor is configured to identify that the first software library and the second software library include redundant functionality based on the intents of the first and second software libraries determined by the GenAI model.

5 . The apparatus of claim 1 , wherein the processor is configured to read a description of the first software library from a first software repository and read a description of the second software library from a second software repository and identify that the first software library and the second software library include redundant functionality based on execution of the GenAI model on the descriptions of the first and second software libraries.

6 . The apparatus of claim 1 , wherein the processor is further configured to determine an efficiency of the first software library and an efficiency of the second software library based on execution of the GenAI model.

7 . The apparatus of claim 6 , wherein the processor is further configured to determine that the first software library and the second software library include redundant functionality based on the efficiency of the first software library and the efficiency of the second software library.

8 . The apparatus of claim 1 , wherein the processor is further configured to receive feedback about the identifier of the first and second software libraries via the user interface and retrain the GenAI model based on execution of the GenAI model on the feedback about the identifier of the first and second software libraries.

9 . A method comprising:
training a generative artificial intelligence (GenAI) model based on execution of the GenAI model on software libraries and descriptions of intent of the software libraries; receiving a first set of software libraries and a second set of software libraries; identifying a first software library within the first set of software libraries that includes redundant functionality with a second software library within the second set of software libraries based on execution of a generative artificial intelligence (GenAI) model on the first and second sets of libraries; and displaying an identifier of the first and second software libraries via a user interface.

10 . The method of claim 9 , wherein the identifying comprises determining that the first software library and the second software library include the redundant functionality based on execution of the GenAI model on naming conventions of the first and second software libraries.

11 . The method of claim 9 , wherein the method further comprises determining an intent of the first software library based on execution of the GenAI model on source code of the first software library and an intent of the second software library based on execution of the GenAI model on source code of the second software library.

12 . The method of claim 11 , wherein the identifying comprises identifying that the first software library and the second software library include redundant functionality based on the determined intents of the first and second software libraries determined by the GenAI model.

13 . The method of claim 9 , wherein the method further comprises reading a description of the first software library from a first software repository and reading a description of the second software library from a second software repository, wherein the identifying comprises identifying that the first software library and the second software library include redundant functionality based on execution of the GenAI model on the descriptions of the first and second software libraries.

14 . The method of claim 9 , wherein the method further comprises determining an efficiency of the first software library and an efficiency of the second software library based on execution of the GenAI model.

15 . The method of claim 14 , wherein the method further comprises determining that the first software library and the second software library include redundant functionality based on the efficiency of the first software library and the efficiency of the second software library.

16 . The method of claim 9 , wherein the method further comprises receiving feedback about the identifier of the first and second software libraries via the user interface and retraining the GenAI model based on execution of the GenAI model on the feedback about the identifier of the first and second software libraries.

17 . A computer-readable medium comprising instructions stored therein which, when executed by a processor, cause the processor to perform:
training a generative artificial intelligence (GenAI) model based on execution of the GenAI model on software libraries and descriptions of intent of the software libraries; receiving a first set of software libraries and a second set of software libraries; identifying a first software library within the first set of software libraries that includes redundant functionality with a second software library within the second set of software libraries based on execution of a generative artificial intelligence (GenAI) model on the first and second sets of libraries; and displaying an identifier of the first and second software libraries via a user interface.

18 . The computer-readable medium of claim 17 , wherein the identifying comprises determining that the first software library and the second software library include the redundant functionality based on execution of the GenAI model on naming conventions of the first and second software libraries.

19 . The computer-readable medium of claim 17 , wherein the instructions, when executed by the processor, cause the processor to perform determining an intent of the first software library based on execution of the GenAI model on source code of the first software library and an intent of the second software library based on execution of the GenAI model on source code of the second software library.

20 . The computer-readable medium of claim 19 , wherein the identifying comprises identifying that the first software library and the second software library include redundant functionality based on the determined intents of t

Assignees

• Toronto Dominion Bank

Inventors

• Guttridge Francis James Alexander
• D'Agostino Dino Paul
• Pratten A Warren
• Mohammed Shahzad
• Chikkalavalasa Arvind
• Nawaz Waqas

Classifications

• G06F8/36

  Software reuse · CPC title

• G06F8/4435 Primary

  Detection or removal of dead or redundant code · CPC title

• G06F8/75 Primary

  Structural analysis for program understanding · CPC title