Operations may include obtaining a buggy code snippet of source code of a software program in which the buggy code snippet includes a particular error. The operations may also include determining a respective first similarity between the buggy code snippet and a plurality of bug patterns of previously identified bug scenarios. In addition, the operations may include selecting a particular bug pattern based on a determined particular first similarity between the particular bug pattern and the buggy code snippet. Moreover, the operations may include determining a respective second similarity between the particular bug pattern and example code snippets obtained from a plurality of posts. The operations may also include selecting a particular post as providing a potential solution to correct the particular error based on a determined particular second similarity between the particular bug pattern and a particular example code snippet of the particular post.

A software robot is designed to carry out an activity (e.g., a mouse click, a text input, etc.) on a target element (e.g., a button, an input field, etc.) of a user interface. The robot's code specification is configured to include an on-screen image of the target element and a text displayed by the target element. The robot is configured to automatically identify the target element at runtime according to an element ID specified in the source-code of the user interface, and when such identification fails, to identify the target element according to the text and image stored in the robot's code.

A system and method for automatically generating scenario patterns are disclosed. The system includes a processor; and a memory operatively connected to the processor via a communication interface. The processor receives a request to create new features in connection with development and/or testing of one or more applications; automatically generates scenario patterns corresponding to the new features by utilizing an automatic scenario patterns generating tool; outputs the scenario patterns in a predefined file format providing an end-2-end (E2E) view spanning multiple applications, state models and events; uploads the scenario patterns in the predefined file format onto a system different from the automatic scenario patterns generating tool; deploys corresponding application programming interface (API) on a private cloud to request the scenario patterns in the predefined file format from the system; and implements the requested scenario patterns to create the new features.

Embodiments provide enhanced performance diagnosis in a network computing environment. In response to an occurrence of a performance issue for a node while under operating conditions, common logs for applications on the node are analyzed. The applications are respectively registered in advance for diagnosis services. The applications each register rules in advance for the diagnosis services. At a time of the performance issue, debug programs are automatically issued to generate debug level logs respectively for the applications. Debug level logs are analyzed according to the rules to determine a root cause of the performance issue. A potential solution to the root cause of the performance issue is determined using the rules, without having to recreate the operating conditions occurring during the performance issue. The potential solution to rectify the root cause of the performance issue is executed without having to recreate the operating conditions occurring during the performance issue.

Various aspects of the disclosure relate to test automation systems with pre-compilers to validate various steps associated with a test script. An artificial intelligence (AI)-based pre-compiler may use natural language processing (NLP) to validate various steps associated with a test script associated with an application. Other aspects of this disclosure relate to automated encryption and mocking of test input data associated with test scripts.

A system for detecting errors in task workflows from a real time video feed records. The video feed that shows a plurality of steps being performed to accomplish a plurality of tasks through an automation process system. The system splits the video feed into a plurality of video recordings which are valid breakpoints determined through cognitive Machine Learning Engine, where each video recording shows a single task. For each task from among the plurality of tasks, the system determines whether the task fails and the exact point of failure for that task. If the system determines that the task fails, the system determines a particular step where the task fails. The system flags the particular step as a failed step. The system reports the flagged step for troubleshooting.

Systems and methods for performing a complete assessment of a disconnected environment to determine if any prerequisite components (dependencies) necessary for the installation of cloud infrastructure are missing from the disconnected environment and generating a report based on the assessment are provided. An offline bundle having an assessment playbook may be imported into the disconnected environment. The assessment playbook may determine whether the disconnected environment includes each of a set of prerequisite components of the cloud infrastructure and generate a report indicating one or more of the set of prerequisite components that are missing from the disconnected environment. An automation playbook may be generated based on the report, wherein the automation playbook installs each of the one or more of the set of prerequisite components that are missing from the disconnected environment.

A system that automatically reduces test cycle time to save resources and developer time. The present system selects a subset of tests from a full test plan that should be selected for a particular test cycle, rather than running the entire test plan. The subset of tests is intelligently selected using metrics such as tests associated with changed code and new and modified tests.

Various aspects of the disclosure relate to test automation systems with pre-compilers to validate various steps associated with a test script. An artificial intelligence (AI)-based pre-compiler may use natural language processing (NLP) to validate various steps associated with a test script associated with an application. Other aspects of this disclosure relate to automated encryption and mocking of test input data associated with test scripts.

A system and a method for recommending a modification to a test package for a software under test. A release note package associated to a feature of a software is received. The release note package is analysed in real time using machine learning based models. Further, a keyword is extracted from the release note package using a keyword extraction technique. The keyword corresponds to the feature of the software. The keyword is compared with nomenclatures present in a test package using a pattern matching technique. The test package is associated to the feature of the software. Finally, a modification to the test package is recommended based on the comparison. The modification comprises addition, deletion, or updating an existing element of the test package. It may he noted that the modification is recommended using an Artificial Intelligence (AI) technique.