IP Library Granted Patent US 12,493,452
Granted Patent B2
US 12,493,452 · App. 18/085,525 · Granted Dec 9, 2025

Code advisory system

Inventors: Edson Gomes Pereira (Sao Paulo, BR); Adriano Augusto Rolfini (Sao Paulo, BR); Lucas Coelho de Almeida (Brasilia, BR); Maria Augusta Bastos Torres (Rio de Janeiro, BR)
Assignee: Kyndryl, Inc.
G06F8/33G06F8/10
View Patent ↗
Loading inventors, assignments & file history…
Monitor This Case
Get email alerts when status or documents change.
Order Certified Copies
Most orders are placed with the USPTO same day — all within 24 business hours.
Order via The Patent Place →
Pre-filled with this patent's details
Quick Facts
Patent No.
US 12,493,452
App. No.
18/085,525
Granted
Dec 9, 2025
Kind
B2
Abstract

An example operation may include one or more of storing code that adheres to predefined coding standards of one or more programming languages within a data store, reading source code from a code file, comparing the source code to the code stored within the data store to determine one or more recommended code changes to the source code, and displaying the one or more recommended code changes via a user interface.

Claims (35)

1 . An apparatus comprising:

a data store configured to store code that adheres to predefined coding standards of one or more programming languages; and

a processor configured to:

read source code from a code file, wherein the code file comprises a header, the header comprising an identification of a programming language of the source code and a description of the source code;

compare the source code to programming statements stored in the data store which adhere to the predefined coding standards to determine one or more recommended code changes to the source code;

display the one or more recommended code changes with the source code via a user interface;

generate a readability score for the source code; and

in response to the readability score failing to meet a threshold, provide suggestions that improve a human readability of the source code.

2 . The apparatus of claim 1 , wherein the data store is configured to store a plurality of code files in a plurality of different programming languages which adheres to a plurality of predefined coding standards, respectively.

3 . The apparatus of claim 2 , wherein the processor is configured to compare the source code to code within the data store which adheres to a predefined coding standard of the identified programming language and configured to offer best practices based on the description in the header.

4 . The apparatus of claim 1 , wherein the processor is configured to identify one or more variables within the source code which do not adhere to the predefined coding standards and recommend one or more conforming variables identified from the data store.

5 . The apparatus of claim 1 , wherein the processor is configured to identify one or more class names within the source code which do not adhere to the predefined coding standards and recommend one or more conforming class names identified from the data store.

6 . The apparatus of claim 1 , wherein the processor is further configured to execute a search of the data store based on the source code to identify a similar pattern of code that adheres to the predefined coding standards and compare the source code to the similar pattern of code to determine the one or more recommended code changes.

7 . A method comprising:

storing code that adheres to predefined coding standards of one or more programming languages within a data store;

reading source code from a code file, wherein the code file comprises a header, the header comprising an identification of a programming language of the source code and a description of the source code;

comparing the source code to programming statements stored in the data store which adhere to the predefined coding standards to determine one or more recommended code changes to the source code, wherein the comparing comprises identifying one or more programming statements which do not adhere to the predefined coding standards within the source code and recommending the one or more conforming programming statements identified from the data store; and

displaying the one or more recommended code changes with the source code via a user interface.

8 . The method of claim 7 , wherein the data store is configured to store a plurality of code files in a plurality of different programming languages which adheres to a plurality of predefined coding standards, respectively.

9 . The method of claim 8 , wherein the reading further comprises comparing the source code to code within the data store which adheres to a predefined coding standard of the identified programming language.

10 . The method of claim 7 , wherein the comparing comprises identifying one or more variables within the source code which do not adhere to the predefined coding standards and recommending one or more conforming variables identified from the data store.

11 . The method of claim 7 , wherein the comparing comprises identifying one or more class names within the source code which do not adhere to the predefined coding standards and recommending one or more conforming class names identified from the data store.

12 . The method of claim 7 , wherein the comparing comprises executing a search of the data store based on the source code to identify a similar pattern of code that adheres to the predefined coding standards and comparing the source code to the similar pattern of code to determine the one or more recommended code changes.

13 . A computer-readable storage medium comprising instructions, that when read by a processor, cause the processor to perform a method comprising:

storing code that adheres to predefined coding standards of one or more programming languages within a data store;

reading source code from a code file, wherein the code file comprises a header, the header comprising an identification of a programming language of the source code and a description of the source code;

comparing the source code to predefined programming statements within the code stored the data store to determine one or more recommended code changes to the source code;

displaying the one or more recommended code changes with the source code via a user interface;

generating a readability score for the source code; and

in response to the readability score failing to meet a threshold, providing suggestions that improve a human readability of the source code.

14 . The computer-readable storage medium of claim 13 , wherein the data store is configured to store a plurality of code files in a plurality of different programming languages which adheres to a plurality of predefined coding standards, respectively.

15 . The computer-readable storage medium of claim 14 , wherein the reading further comprises comparing the source code to code within the data store which adheres to a predefined coding standard of the identified programming language.

16 . The computer-readable storage medium of claim 13 , wherein the comparing comprises identifying one or more variables within the source code which do not adhere to the predefined coding standards and recommending one or more conforming variables identified from the data store.

17 . The computer-readable storage medium of claim 13 , wherein the comparing comprises identifying one or more class names within the source code which do not adhere to the predefined coding standards and recommending one or more conforming variables identified from the data store.

18 . The computer-readable storage medium of claim 13 , wherein the comparing comprises executing a search of the data store based on the source code to identify a similar pattern of code that adheres to the predefined coding standards and comparing the source code to the similar pattern of code to determine the one or more recommended code changes.

Assignments (1)
ASSIGNMENT OF ASSIGNOR'S INTEREST Recorded Dec 20, 2022
From: GOMES PEREIRA, EDSON; ROLFINI, ADRIANO AUGUSTO; DE ALMEIDA, LUCAS COELHO; BASTOS TORRES, MARIA AUGUSTA
To: KYNDRYL, INC.
Reel/Frame 062165/0239 →
Continuity (1)
Related Publication 20240201955A1 · Jun 20, 2024
References Cited (55)
US 7231343B1 · Treadgold et al. · 2007 [cited by applicant]
US 8356278B2 · Drissi et al. · 2013 [cited by applicant]
US 8826237B2 · Balasubramanian · 2014 [cited by examiner]
US 8903711B2 · Lundberg · 2014 [cited by examiner]
US 9235494B2 · Gautam · 2016 [cited by examiner]
US 10268753B2 · Bar-Or et al. · 2019 [cited by applicant]
US 10635566B1 · Talluri · 2020 [cited by examiner]
US 11042361B1 · Espostio · 2021 [cited by examiner]
US 11579868B1 · Zhang · 2023 [cited by examiner]
US 11704099B1 · Morse · 2023 [cited by examiner]
US 11714611B2 · Makkar · 2023 [cited by examiner]
US 11763078B2 · Wilson-Thomas · 2023 [cited by examiner]
US 11914993B1 · Garg · 2024 [cited by examiner]
US 12045609B1 · Sawant · 2024 [cited by examiner]
US 12190081B1 · Visser · 2025 [cited by examiner]
US 20050223354A1 · Drissi · 2005 [cited by examiner]
US 20160034275A1 · Abuelsaad · 2016 [cited by examiner]
US 20160162527A1 · Freed · 2016 [cited by examiner]
US 20170315903A1 · David · 2017 [cited by examiner]
US 20170351511A1 · Bar-Or et al. · 2017 [cited by applicant]
US 20180196731A1 · Moorthi et al. · 2018 [cited by applicant]
US 20180253285A1 · Howard · 2018 [cited by examiner]
US 20190339947A1 · Mccune · 2019 [cited by examiner]
US 20200201627A1 · Pham · 2020 [cited by examiner]
US 20210034335A1 · Svyatkovskiy · 2021 [cited by examiner]
US 20210042638A1 · Novotny · 2021 [cited by examiner]
US 20210081182A1 · Seshadri et al. · 2021 [cited by applicant]
US 20210318865A1 · Farivar · 2021 [cited by examiner]
US 20210349698A1 · Wilson-Thomas · 2021 [cited by examiner]
US 20220012018A1 · Trim · 2022 [cited by examiner]
US 20220012019A1 · Wilson-Thomas · 2022 [cited by examiner]
US 20220147345A1 · Lake · 2022 [cited by examiner]
US 20220179403A1 · Miller · 2022 [cited by examiner]
US 20220334835A1 · Gottschlich · 2022 [cited by examiner]
US 20220358286A1 · Wilson-Thomas · 2022 [cited by examiner]
US 20230081509A1 · Banipal · 2023 [cited by examiner]
US 20230281005A1 · Groenewegen · 2023 [cited by examiner]
US 20230315400A1 · Tabachnyk · 2023 [cited by examiner]
US 20230385037A1 · Jayaraman · 2023 [cited by examiner]
US 20230418565A1 · Arumugam Selvaraj · 2023 [cited by examiner]
US 20240012909A1 · Young · 2024 [cited by examiner]
US 20240184570A1 · Fu · 2024 [cited by examiner]
CN 115390806A · 2022 [cited by examiner]
CN 115905501A · 2023 [cited by examiner]
WO WO2021231058A1 · 2021 [cited by examiner]
Gu, Hareesh, and Sanjay Kumar Dubey. “Academic coding guideline model-OCG.” 2014 International Conference on Computing for Sustainable Global Development (INDIACom). IEEE, 2014. [cited by examiner]
Fowkes, Jaroslav, et al. “Autofolding for source code summarization.” IEEE Transactions on Software Engineering 43.12 (2017). [cited by examiner]
Anonymous, Method and Process for Automatically Generating Development and Test Estimates From Early Text Descriptions of the Product, An IP.com Prior Art Database Technical Disclosure, Jun. 20, 2005. [cited by applicant]
Anonymous, Method to reduce the risk of regression associated to a set of changes in software code based on repository items suggestions, An IP.com Prior Art Database Technical Disclosure, Jul. 19, 2019. [cited by applicant]
Fu et al., Code Review and Cooperative Pair Programming Best Practice, Schlumberger Information Solutions AS, Stavanger, Norway, Jun. 7, 2017. [cited by applicant]
Allamanis et al., “Learning Natural Coding Conventions”, arXiv:1402.4182v3 [cs.SE] Apr. 7, 2014, 13 pages. [cited by applicant]
Anonymous, “Codacy”, URL: https://www.codacy.com, Retrieved: Jul. 9, 2024, 11 pages. [cited by applicant]
Anonymous, “Code Climate”, URL: https://codeclimate.com, Retrieved: Jul. 9, 2024, 5 pages. [cited by applicant]
Anonymous, “SonarQube”, URL: https://www.sonarqube.org, Retrieved: Jul. 9, 2024, 11 pages. [cited by applicant]
Scalabrino et al., “Improving Code Readability Models with Textual Features”, 2016 IEEE 24th International Conference on Program Comprehension (ICPC), 2016, pp. 1-10. [cited by applicant]