Abstract: 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.

Abstract: 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.

Abstract: Disclosed herein is a method and system for real-time health data management and prediction of health trends for patients. The system receives patient data from patients, doctors treating patients and one or more external sources. Upon receiving the patient data, system generates three tables for storing, general information, health information and preference information of patients. Thereafter, the system generates a distributed ledger in real-time for each patient based on details of each patient from three tables. The distributed ledger comprises consolidated health data from all the three tables. The system provides a selectively authorized access to the distributed ledger based on biometric information of the patient. Further, based on the consolidated health data, the system manages health data of each of the one or more patients and predicts health trends of each of the one or more patients using Artificial Intelligence (AI) Machine Learning (ML) techniques.

Abstract: The present invention relates to a method of detecting false authentication of a user from a device connected to a network. The method includes receiving one or more parameters associated with the user while the user is logging in to at least one application in the device. Further, a score is generated by associating a binary value to the one or more parameters. Furthermore, reference parameters of the user is retrieved from a database and compared with the one or more parameters. Upon successful validation, the user may be allowed to access the device. Upon unsuccessful validation, one or more queries may be provided to the user. Based on a response received from the user, a false authentication of the user is determined and the user is denied access to the at least one application.

Abstract: 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.

Abstract: 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.

Abstract: 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.

Abstract: 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.

Abstract: 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.

Abstract: The present disclosure relates to field of retail environment. Accordingly, disclosed herein is a method and system for providing one or more purchase recommendations to a user. Purchase details corresponding to previous purchases by the user and user information are collected. Further, a plurality of optimal purchase parameters is determined by analyzing the purchase details based on the user information. Finally, one or more purchase recommendations are provided to the user based on the plurality of optimal purchase parameters. In an embodiment, the present method facilitates the user to identify a retail store that offers optimal savings on the purchase of a product of interest to the user. Also, the present method helps retailers to analyze purchase pattern of the user for predicting and determining appropriate products to be sold to the user on future purchases.

Abstract: Disclosed herein is a method and system for determining a plurality of project factors to achieve a quality associated with a project. The method comprises receiving, by an application server, input data from one or more external sources. Upon receiving the input data, determining a value corresponding to each of the plurality of project factors associated with the project using the input data. Also, the method comprises computing cost of quality (COQ) of the project using the value corresponding to the each of the plurality of project factors. Further, determining expected COQ of the project based on an ontology based process, using the computed COQ and data associated with a plurality of projects retrieved from a market research database.

Abstract: 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.

Abstract: The present disclosure relates to a method and a system for predicting stability of a project. A predictive analysis system receives data related to defect parameters, developer parameters, test case parameters, requirement parameters and production defect parameters of a project from one or more data sources. Thereafter, the predictive analysis system determines plurality of trends based on the received data. Further, the predictive analysis system determines a project release prediction value for the project based on at least one of the plurality of trends. Further, the predictive analysis system determines an impact value of the project based on at least one of the plurality of trends. Finally, the predictive analysis system determines a prediction result value based on the project release prediction value and the impact value for predicting the stability of the project.

Abstract: The present disclosure relates to a method and a system for optimizing stability of a project. A predictive analysis system receives data related to defect parameters, developer parameters, test case parameters, requirement parameters and production defect parameters of a project from data sources. Thereafter, the predictive analysis system determines plurality of trends based on the received data. Further, the predictive analysis system determines a project release prediction value for the project based on the plurality of trends. Further, the predictive analysis system determines an impact value of the project based on the plurality of trends. Further, the predictive analysis system determines a prediction result value based on the project release prediction value and the impact value for predicting the stability of the project. Further, the predictive analysis system dynamically performs one or more actions based on the prediction result value for optimizing the stability of the project.

Abstract: 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.

Abstract: 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.

Abstract: 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.

Abstract: The present disclosure relates to a method for determining effectiveness in marketing. A evaluation device receives marketing data from one or more data sources. The received marketing data is used to determine one or more scores corresponding to each of one or more end users. The one or more scores maybe a first score, a second score and a third score. The evaluation device uses the determined each of the one or more scores to determine an opportunity value that indicates the opportunity available to achieve a predefined target with respect to each of the one or more end users. The evaluation device also determines a revenue generation value that indicates revenue being generated with respect to each of the one or more end users. The opportunity value and revenue generation value are correlated to obtain an effectiveness result indicating the effectiveness in the marketing.

Abstract: Embodiments of the present disclosure disclose a method and a device for optimizing software testing process. The method comprises receiving input data from one or more test management systems and one or more project complexity systems. The method also comprises computing an effort index value by correlating the input data based on at least one parameter associated with the one or more project complexity systems. The method further comprises obtaining an effectiveness value based on the effort index value and the input data and optimizing the software testing process by computing a usefulness value associated with the input data and the effectiveness value.

Abstract: 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.