Abstract: Techniques for UNDO and REDO operations in a computer-user interface are disclosed. The techniques enables users to configure entities for UNDO and REDO operations. The techniques also enable users to roll back individual entity to an immediate previous state in one UNDO operation and subsequently to the other previous states. Other entities are not affected by the UNDO operations to the entity.

Abstract: Techniques for configuring autosave triggers in a computing environment based on environment and data conditions are disclosed. A system trains a machine learning model based on data attributes and environmental attributes to generate autosave value triggers for a computing environment. The autosave value triggers are triggered by different conditions. For example, one autosave trigger may be triggered when an error condition is detected. Another may be triggered when a certain number of operations are performed. The machine learning model generates autosave trigger values scores for one or more autosave triggers. The system may implement the autosave triggers in the computing environment based on the autosave trigger values.

Abstract: Systems, methods, and other embodiments associated with a configurable identification mechanism of debug parameters are described. In one embodiment, a method includes generating a graphical user interface (GUI) for a debugging program, where the GUI is configured to provide options to configure naming rules for threads during debugging of a computer process that includes multiple threads. The options to configure the naming rules may include configuring a naming rule that adds one or more context identifiers to a thread name. The thread name may be generated by automatically populating one or more of the context identifiers with a variable value that occurs during execution of the thread that corresponds to the one or more context identifiers. A conditional breakpoint may be controlled during debugging that is thread-specific based on a condition including at least one context identifier that matches a portion of the thread name.

Abstract: Techniques for configuring autosave triggers in a computing environment based on environment and data conditions are disclosed. A system trains a machine learning model based on data attributes and environmental attributes to generate autosave value triggers for a computing environment. The autosave value triggers are triggered by different conditions. For example, one autosave trigger may be triggered when an error condition is detected. Another may be triggered when a certain number of operations are performed. The machine learning model generates autosave trigger values scores for one or more autosave triggers. The system may implement the autosave triggers in the computing environment based on the autosave trigger values.

Abstract: Techniques for UNDO and REDO operations in a computer-user interface are disclosed. The techniques enables users to configure entities for UNDO and REDO operations. The techniques also enable users to roll back individual entity to an immediate previous state in one UNDO operation and subsequently to the other previous states. Other entities are not affected by the UNDO operations to the entity.

Abstract: Techniques for UNDO and REDO operations in a computer-user interface are disclosed. The techniques enables users to configure entities for UNDO and REDO operations. The techniques also enable users to roll back individual entity to an immediate previous state in one UNDO operation and subsequently to the other previous states. Other entities are not affected by the UNDO operations to the entity.

Abstract: Techniques for UNDO and REDO operations in a computer-user interface are disclosed. The techniques enables users to configure entities for UNDO and REDO operations. The techniques also enable users to roll back individual entity to an immediate previous state in one UNDO operation and subsequently to the other previous states. Other entities are not affected by the UNDO operations to the entity.

Abstract: Techniques for configuring autosave triggers in a computing environment based on environment and data conditions are disclosed. A system trains a machine learning model based on data attributes and environmental attributes to generate autosave value triggers for a computing environment. The autosave value triggers are triggered by different conditions. For example, one autosave trigger may be triggered when an error condition is detected. Another may be triggered when a certain number of operations are performed. The machine learning model generates autosave trigger values scores for one or more autosave triggers. The system may implement the autosave triggers in the computing environment based on the autosave trigger values.

Abstract: A library uplift tool may automatically identify changes to elements of an between different versions of a software library interface. The public interfaces of the two versions may be compared to identify changes to datatypes, variable or function names, parameter names, parameter lists, and other elements of the library interface. Locations in application source code using the software library may then be identified and linked with the changes between the library versions. A report or user interface may then display specific locations in the application source code that are affected by the changes to the library versions. For each change, a suggested action may be presented in the interface, and an example of modified source code may be generated. The interface may be interactive such that modified source code may be automatically propagated to source code files for compatibility with the new library version.

Abstract: A library uplift tool may automatically identify changes to elements of an between different versions of a software library interface. The public interfaces of the two versions may be compared to identify changes to datatypes, variable or function names, parameter names, parameter lists, and other elements of the library interface. Locations in application source code using the software library may then be identified and linked with the changes between the library versions. A report or user interface may then display specific locations in the application source code that are affected by the changes to the library versions. For each change, a suggested action may be presented in the interface, and an example of modified source code may be generated. The interface may be interactive such that modified source code may be automatically propagated to source code files for compatibility with the new library version.