Abstract: A method and a testing tool for automated testing of HMI applications includes: identifying, at least one vehicle from a plurality of vehicles as HMI enabled vehicle, and a HMI application installed on an electronic device corresponding to the at least one vehicle; identifying one or more errors in one or more additional features being integrated with the HMI application; generating test data based on one or more test scripts related to the one or more additional features and historical test analysis of the HMI application; and executing the one or more test scripts on the HMI application based on the test data for automated testing of Human Machine Interface (HMI) applications associated with vehicles. The disclosed method and the testing tool provide a common framework for testing HMI applications of various vehicles.

Abstract: In one embodiment, a method for automating regression testing of a software application is disclosed. The method includes receiving, by a test automation system, input data associated with the regression testing of the software application and predicting, by the test automation system, a test automation framework for execution of a regression test suite by analyzing the input data. Further, the method includes obtaining, by the test automation system, test scenarios from execution of historical regression test suites upon predicting the test automation framework and identifying, by the test automation system, availability of devices for executing each test scenario based on one or more device parameters. Further, the method includes transmitting, by the test automation system, information corresponding to the test scenarios to the identified devices based on the availability to automate the regression testing of the software application.

Abstract: A method and a testing tool for automated testing of HMI applications includes: identifying, at least one vehicle from a plurality of vehicles as HMI enabled vehicle, and a HMI application installed on an electronic device corresponding to the at least one vehicle; identifying one or more errors in one or more additional features being integrated with the HMI application; generating test data based on one or more test scripts related to the one or more additional features and historical test analysis of the HMI application; and executing the one or more test scripts on the HMI application based on the test data for automated testing of Human Machine Interface (HMI) applications associated with vehicles. The disclosed method and the testing tool provide a common framework for testing HMI applications of various vehicles.

Abstract: A method, device, and non-transitory computer readable medium for testing mobile applications in a mobile application testing system is disclosed. The method includes creating at least one Docker container in the mobile application testing system. After creating the at least one docker container, the method identifies a mobile application for testing. The method automatically generates at least one test artifact in response to identifying the mobile application for testing. Thereafter, the method installs the at least one test artifact for the mobile application for testing in the at least one Docker container. Further, the method selects at least one mobile device in response to installing the at least one test artifact for the mobile application for testing in the at least one Docker container. Thereafter, the method executes the at least one test artifact for the at least one selected mobile device in the at least one Docker container.

Abstract: In one embodiment, a method for automating regression testing of a software application is disclosed. The method includes receiving, by a test automation system, input data associated with the regression testing of the software application and predicting, by the test automation system, a test automation framework for execution of a regression test suite by analyzing the input data. Further, the method includes obtaining, by the test automation system, test scenarios from execution of historical regression test suites upon predicting the test automation framework and identifying, by the test automation system, availability of devices for executing each test scenario based on one or more device parameters. Further, the method includes transmitting, by the test automation system, information corresponding to the test scenarios to the identified devices based on the availability to automate the regression testing of the software application.

Abstract: A method, device, and non-transitory computer readable medium for testing mobile applications in a mobile application testing system is disclosed. The method includes creating at least one Docker container in the mobile application testing system. After creating the at least one docker container, the method identifies a mobile application for testing. The method automatically generates at least one test artifact in response to identifying the mobile application for testing. Thereafter, the method installs the at least one test artifact for the mobile application for testing in the at least one Docker container. Further, the method selects at least one mobile device in response to installing the at least one test artifact for the mobile application for testing in the at least one Docker container. Thereafter, the method executes the at least one test artifact for the at least one selected mobile device in the at least one Docker container.

Abstract: The present disclosure relates to a method for predicting estimations of project factors in software development environment. The method comprises receiving first input data including at least one type of first software development model and associated one or more first project data from a user. The method further comprises identifying one or more first software agents based on the at least one type of the first software development model. The method further comprises processing the one or more first project data using the identified one or more first software agents to identify one or more first intermediate data required for project factors estimation. The method further comprises calculating estimations of the project factors using the identified one or more first intermediate data.