US 12,298,972 B2
System and method for recursive transliteration of machine interpretable languages
Maharaj Mukherjee, Poughkeepsie, NY (US); Utkarsh Raj, Charlotte, NC (US); Carl M. Benda, Charlotte, NC (US); Suman Roy Choudhury, Jersey City, NJ (US); and Elvis Nyamwange, Little Elm, TX (US)
Assigned to Bank of America Corporation, Charlotte, NC (US)
Filed by Bank of America Corporation, Charlotte, NC (US)
Filed on Dec. 21, 2021, as Appl. No. 17/557,366.
Claims priority of provisional application 63/272,263, filed on Oct. 27, 2021.
Prior Publication US 2023/0127193 A1, Apr. 27, 2023
This patent is subject to a terminal disclaimer.
Int. Cl. G06F 16/2452 (2019.01); G06F 16/21 (2019.01); G06F 16/242 (2019.01); G06F 16/2453 (2019.01); G06F 16/248 (2019.01); G06F 16/25 (2019.01); G06F 40/205 (2020.01)
CPC G06F 16/2452 (2019.01) [G06F 16/214 (2019.01); G06F 16/2425 (2019.01); G06F 16/2433 (2019.01); G06F 16/2448 (2019.01); G06F 16/24534 (2019.01); G06F 16/248 (2019.01); G06F 16/258 (2019.01); G06F 40/205 (2020.01)] 19 Claims
OG exemplary drawing
 
1. A computing platform comprising:
at least one processor;
a communication interface communicatively coupled to the at least one processor; and memory storing computer-readable instructions that, when executed by the at least one processor, cause the computing platform to:
receive a query, wherein the query is formatted in a first format for execution on a first database, wherein the first format comprises a first machine interpretable language;
translate the query to a second format for execution on a second database, wherein the second format comprises a second machine interpretable language, wherein the query comprises a SQL query and wherein the translated query comprises a non-SQL query, and wherein translating the query comprises:
extracting non-essential parameters from the query to create a query key;
storing the non-essential parameters;
executing a lookup function on a query library to identify a translated query corresponding to the query key;
based on identifying that the query library includes portions of the query key rather than the query key, recursively identifying the translated query by nesting the portions of the query key, wherein recursively identifying the translated query comprises:
identifying a first stored query key corresponding to a first portion of the query key,
identifying a second stored query key corresponding to a second portion of the query key, and
combining the first stored query key with the second stored query key to create a combination query key that matches the query key, wherein the translated query comprises the combination query key, wherein the combination query key includes the second stored query key nested within the first stored query key;
and inputting the non-essential parameters into the translated query to create an output query;
execute the output query on the first database to produce a first query result:
execute the output query on the second database to produce a second query result;
compare the second query result to the first query result;
based on identifying a discrepancy between the first query result and the second query result, update a query translation model used to produce the output query, wherein updating the query translation model causes the query translation model to adjust for the discrepancy, and wherein the query translation model is trained, maintained, and refined by a machine learning engine; and
based on identifying that the first query result matches the second query result, validate the output query.