Wipro Limited

Sumithra Sundaresan

Venkata Subramanian Jayaraman

Method and system for predicting failures in interconnected systems based on quantum computing is disclosed. The method may include identifying a set of unique patterns from input data received from a plurality of input data sources, determining a correlation between at least two input data sources, creating a plurality of sets of clusters corresponding to the plurality of input data sources based on the correlation, extracting data associated with each of the set of unique patterns based on the plurality of sets of clusters, predicting, based on the extracted data, a failure of at least one interconnected system using a trained ML model, processing the extracted data associated with each of the set of unique patterns and information associated with the predicted failure through a quantum computing layer, and generating, through the quantum computing layer, at least one corrective action for the at least one interconnected system.

Method and system for predicting failures in interconnected systems based on quantum computing

In one embodiment, a method for providing access to big data is disclosed. The method includes receiving biometric data of a user to provide access to columns of a table storing the big data, wherein one or more columns of the table are masked based on one or more data parameters and authenticating the user by comparing the biometric data of the user with pre-stored biometric data, wherein the pre-stored biometric data is retrieved from a biometric database. Further, the method includes providing upon the authentication, selective access to each column of the table based on a pre-defined user privilege for each column.

Methods and systems for providing secured access to big data

The present disclosure relates to a method and a system for identifying one or more test cases for penetration testing of an application associated with an entity. An application testing system receives data related to application from one or more data sources and uses the data to determine threat score, vulnerability score, human error score, business impact score and popularity score. Further, application testing system identifies threat quantifier value based on threat score, vulnerability score and human error score. The application testing system also determines impact quantifier value based on business score and popularity score. The application testing system then determines threat severity level and impact severity level based on threat quantifier value and impact quantifier value. Based on the determined threat severity level and the impact severity level, the application testing system identifies the one or more test cases for performing penetration testing of the application.

Method and system for identifying test cases for penetration testing of an application

A system and method for improving integration testing in a cloud computing environment includes collecting one or more input parameters associated with each of one or more products, deployed in cloud computing environment, from one or more external resources and test management systems. The input parameters include one or more defect parameters, user requirements, test parameters or performance parameters associated with the product. The integration testing improvement system determines one or more failure issues associated with the product and analyzes the behavior of the product over a predetermined time period to identify a failure pattern associated with the product. Each of the determined failure issues is mapped with the identified failure pattern to detect one or more critical scenarios in each of the products. Later the critical scenarios are automated by executing associated test scripts thereby improving the integration testing in the cloud computing environment.

System and method for improving integration testing in a cloud computing environment

Devices and methods for identifying relevant features of software product are described. The system retrieves requirement data, test case data and defect data associated with plurality of features of the software product. The requirement data comprises de-scoped requirements which indicate those requirements which are not required for performing the regression testing. The device further computes an impact score, a test effort score, and a weightage factor for each of the plurality of features based on the requirement data, the test case data and the defect data respectively. Based on the computed impact score, the test effort score, and the weightage factor, the device further determines a regression factor for each of the plurality of features. Further, the device identifies one or more relevant features amongst the plurality of features based on the regression factor. This way, the device facilitates structured regression planning which optimizes the overall performance of the device.

Software testing system and a method for facilitating structured regression planning and optimization

The present disclosure relates to a method for enhancing quality of requirements for an application development. The method comprises retrieving expertise information of each user of groups involved in identifying requirements, domain knowledge of each user, information on number of defects associated with requirements and information of requirements for application development from sources. Then, skill score of the groups is computed using expertise information and domain knowledge of each user of corresponding groups. Solidity score of each of requirements is determined using information of requirements and predetermined threshold solidity score. Weightage score of each of requirements is computed based on information of requirements and information on number of defects. The, using skill score of groups, solidity score of each of requirements and weightage score, strength score of each of requirements is computed for enhancing quality of requirements.

Method and system for enhancing quality of requirements for an application development

This disclosure relates generally to software release management, and more particularly to a system and method for optimizing risk during a software release. In one embodiment, a method is provided for determining a risk associated with a release of a software product. The method comprises gathering a plurality of parameters related to the software product, determining a plurality of complexity levels based on the plurality of parameters, determining a stability of the software product based on a stability of a baseline software product, determining an overall complexity level of the release of the software product based on the plurality of complexity levels and the stability of the software product, and determining the risk associated with the release of the software product based on the overall complexity level.

Growing community of inventors

Chennai, India

Sumithra Sundaresan