US 12,461,743 B2
System and method for optimized generation of microservices
Parasu Pillai Iyappan Velammal, Chennai (IN); Manoj Chakri Shekaran, Bengaluru (IN); Vinitha Yogish Pai, Bengaluru (IN); Sivakumar Ellappan, Chennai (IN); Jeyashree Pandian Duraipandian, Chennai (IN); and Pramod Subrayappa, Bangalore (IN)
Assigned to COGNIZANT TECHNOLOGY SOLUTIONS INDIA PVT. LTD., Chennai (IN)
Filed by Cognizant Technology Solutions India Pvt. Ltd., Chennai (IN)
Filed on Feb. 22, 2023, as Appl. No. 18/112,623.
Claims priority of application No. 202241072008 (IN), filed on Dec. 13, 2022.
Prior Publication US 2024/0192932 A1, Jun. 13, 2024
Int. Cl. G06F 8/76 (2018.01); G06F 8/30 (2018.01); G06F 8/40 (2018.01)
CPC G06F 8/76 (2013.01) [G06F 8/30 (2013.01); G06F 8/40 (2013.01)] 24 Claims
OG exemplary drawing
 
1. A method for generation of domain driven microservices-based architecture from application source codes, wherein the method is implemented by a processor executing program instructions stored in a memory, the method comprising:
creating a control flow structure based on technical rules extracted from an application source code;
extracting metadata by parsing the control flow structure in real time;
identifying a first data associated with a plurality of source entities and corresponding attributes;
identifying a second data associated with a plurality of target entities based on an operation type;
identifying a third data associated with a plurality of technical data in the application source code on the basis of an action performed by a user via an application corresponding to the application source code;
generating a data trace between the source entities and target entities from the first data, the second data and the third data, wherein the data trace is generated by:
detecting run-time parameters of the first data, the second data and the third data, ascertaining source variables associated with the source entity and target variables associated with the target entity, wherein the data trace is retrieved in the event of a match between the source variables and the target variables;
grouping the first data, the second data and the third data into a plurality of domains and sub-domains to create grouped domain blocks based on the generated data trace, wherein the grouped domain blocks comprise one or more domain control flow structures;
creating boundaries in the form of bounded context associated with the domains and sub-domains; and
establishing correlations between the bounded contexts to generate a microservices code-based architecture code, wherein memory space is automatically identified as per the domain based on non-functional requirements as the microservices architecture code is deployed and reserve memory is allocated as per peak time usage.