Abstract: A computer-implemented method provides rewinding and switching to a new code-path after an error in a preferred code-path. The method includes identifying a first error during execution of an application. The method further includes determining, in response to the first error, a previous breakpoint in a first code-path of the application prior to the location of the first error. The method also includes rewinding the application from the first error to the previous breakpoint. The method includes initiating, in response to the rewinding, a second code-path available at the previous breakpoint. Further aspects of the present disclosure are directed to systems and computer program products containing functionality consistent with the method described above.

Abstract: Using cross-compilation to determine translation accuracy of artificial intelligence generated code includes receiving a first code portion of a first programming language, converting the first code portion to a second code portion of a second programming language by a generative artificial intelligence model, and converting the second code portion to a third code portion of the first programming language by the generative artificial intelligence model. A translation accuracy score of the converting of the first code portion to the second code portion is calculated.

Abstract: A multipathing code package including multiple code sections is provided. The multipathing code package includes at least different first and second versions of a particular code section among the multiple code sections. Processing circuitry of a data processing system executes the multipathing code package. Execution of the multipathing code packages includes executing a first version of the particular code section. Based on detecting an occurrence of an execution failure in the first version of the particular code section, the processing circuitry rewinds execution and replays the particular code section through execution of the second version.

Abstract: Self-healing multipathing code with AI reinforcement feedback, includes identifying, during execution an application including a portion of multipathing code comprising a first path and a second path, a first fault in an execution of the first path; generating, based on the first fault, a first prompt to an artificial intelligence (AI) language model; and applying a first modification to the first path based on an output of the AI language model in response to the first prompt.

Abstract: According to an aspect, a computer-implemented method includes configuring a disaster recovery computer system as a test environment of a mainframe computer system as a mirror image of a production environment, where the disaster recovery computer system is a backup of a primary production computer system. Test cases are executed in the test environment of the disaster recovery computer system. A stress and load impacts can be monitored on a plurality of computer system resources of the disaster recovery computer system based on execution of the test cases. The test environment can be disabled, and the disaster recovery computer system can be reconfigured as a production system based on a failure of the primary production computer system.

Abstract: According to an aspect, a computer-implemented method includes configuring a disaster recovery computer system as a test environment of a mainframe computer system as a mirror image of a production environment, where the disaster recovery computer system is a backup of a primary production computer system. Test cases are executed in the test environment of the disaster recovery computer system. A stress and load impacts can be monitored on a plurality of computer system resources of the disaster recovery computer system based on execution of the test cases. The test environment can be disabled, and the disaster recovery computer system can be reconfigured as a production system based on a failure of the primary production computer system.