公开(公告)号：US20230013748A1

公开(公告)日：2023-01-19

申请号：US17375651

申请日：2021-07-14

Applicant: Bank of America Corporation

Inventor： Deepan Kanagaraj ,  Magesh Sripathy ,  Sachin Thakral ,  Vishnuvardhan Rao Regalla ,  Prasanna K ,  Suki Ramasamy

IPC: G06F8/41 ,  G06N5/02 ,  G06F16/28

Abstract: Various aspects of this disclosure relate to determining mapping issues in object relational mapping (ORM). An artificial intelligence (AI) model may be trained to identify errors in mapping between relational databases and objects during code compilation. Multiple AI models may be used, with different models being associated with different programming frameworks, thereby making this technique framework agnostic.

公开(公告)号：US11829735B2

公开(公告)日：2023-11-28

申请号：US17375651

申请日：2021-07-14

Applicant: Bank of America Corporation

Inventor： Deepan Kanagaraj ,  Magesh Sripathy ,  Sachin Thakral ,  Vishnuvardhan Rao Regalla ,  Prasanna K ,  Suki Ramasamy

IPC: G06F9/44 ,  G06F8/41 ,  G06F16/28 ,  G06N5/022

CPC classification number: G06F8/41 ,  G06F16/284 ,  G06N5/022

Abstract: Various aspects of this disclosure relate to determining mapping issues in object relational mapping (ORM). An artificial intelligence (AI) model may be trained to identify errors in mapping between relational databases and objects during code compilation. Multiple AI models may be used, with different models being associated with different programming frameworks, thereby making this technique framework agnostic.

公开(公告)号：US20230018525A1

公开(公告)日：2023-01-19

申请号：US17375563

申请日：2021-07-14

Applicant: Bank of America Corporation

Inventor： Deepan Kanagaraj ,  Magesh Sripathy ,  Sachin Thakral ,  Vishnuvardhan Rao Regalla ,  Prasanna K ,  Suki Ramasamy

IPC: G06F8/20 ,  G06F16/22 ,  G06F16/28 ,  G06F40/226

Abstract: Various aspects of this disclosure relate to determining mapping issues in object relational mapping (ORM). An artificial intelligence (AI) model may be trained to identify errors in mapping between relational databases and objects during code compilation. Multiple AI models may be used, with different models being associated with different programming frameworks, thereby making this technique framework agnostic.