US 12,153,664 B2
System and method for detection of patterns in application for application transformation and applying those patterns for automated application transformation
Sameer Karmarkar, Pune (IN); Ameya Varade, Pune (IN); and Abhijit Anant Joshi, Pune (IN)
Assigned to CLOUDHEDGE TECHNOLOGIES PRIVATE LIMITED, Maharashtra (IN)
Filed by CLOUDHEDGE TECHNOLOGIES PRIVATE LIMITED, Maharashtra (IN)
Filed on Feb. 3, 2022, as Appl. No. 17/591,956.
Prior Publication US 2022/0245274 A1, Aug. 4, 2022
Int. Cl. G06F 21/50 (2013.01); G06F 9/455 (2018.01); G06F 16/174 (2019.01); G06F 18/21 (2023.01); G06F 18/214 (2023.01); G06F 21/62 (2013.01)
CPC G06F 21/50 (2013.01) [G06F 9/45558 (2013.01); G06F 16/174 (2019.01); G06F 18/214 (2023.01); G06F 18/2193 (2023.01); G06F 21/6236 (2013.01); G06F 2009/45579 (2013.01); G06F 2009/45587 (2013.01); G06F 2221/2143 (2013.01)] 8 Claims
OG exemplary drawing
 
1. A system for detection of patterns in application for application transformation and applying those patterns for automated application transformation, the system being configured on a computing device, the system comprising:
a monitoring module, the monitoring module configured to collect new datasets about an application under observation, wherein meta-data of the application under observation is collected;
a data collection module, the data collection module configured to classify and clean the data received from the monitoring module, wherein the data collection module collects all requisite files required for independent execution of the application that is being containerized;
a data analyzing module, the data analyzing module configured to analyze in an automated manner the cleaned data received from the data collection module and determine patterns and antipatterns in a process of application transformation;
a pattern recognition module, the pattern recognition module configured to detect new applications or new application postures, wherein the pattern recognition module looks and analyses a new unknown information for identifying new applications;
a training module, the training module configured to receive new patterns identified along with old patterns from the pattern recognition module, and generate rules and a statistical model to recognize the applications;
a feature generation module, the feature generation module configured to generate new capabilities for detecting new applications or refining existing understanding of applications based on the new statistical model and training data; and
a feedback module, the feedback module configured to apply machine learning from newer data points and code the data points into application transformation;
wherein the data collection module collects information of the computing device, hosts and components associated therewith, and data provided by users about the computing device.