Abstract: Provided are a computer program product, system, and method for modifying output code in source code to output compressed output statements. A codebook indicates replacement codes associated with strings in output code in source code. The output code is to generate output statements. The strings of the output code are replaced with the replacement codes associated with the strings to produce modified source code. Multiple instances of a same string in the output code are replaced by an associated same replacement code in the codebook. The modified source code, having the replacement codes replacing the strings, is compiled to produce an executable application. The executable application during runtime produces compressed output statements comprising the replacement codes that replaced the associated strings.

Abstract: A method, computer system, and a computer program product for providing gratuity recommendations is provided. The present invention may include receiving a service request from a user, wherein a service is to be provided according to the service request by a service provider. The present invention may include accessing data for the service request. The present invention may include determining a gratuity for the service request based on the data accessed for the service request. The present invention may include processing the gratuity according to preferences of the service provider.

Abstract: Embodiments relate to an intelligent computer platform to multi-dimensionally optimize device operation. Static hardware device data are acquired and dynamic hardware characteristic data are tracked over one or more temporal segments. A neural model (NM) is trained with corresponding device and network data. The acquired static and dynamic data are input into the NM, and locale processing patterns corresponding to the inputted data are identified. One or more data points and corresponding measurements of the tracked dynamic hardware characteristic data are temporally analyzed. A processing locale corresponding to the temporal analysis is identified and returned as output data, and one or more encoded actions in compliance with the identified processing locale are selectively implemented.

Abstract: Embodiments relate to an intelligent computer platform to multi-dimensionally optimize device operation. Static hardware device data is acquired and dynamic hardware characteristic data is tracked over one or more temporal segments. A neural model (NM) is trained with corresponding device and network data. The acquired static and dynamic data is populated into the MLM, and locale processing patterns corresponding to the populated data are identified. One or more data points and corresponding measurements of the tracked hardware device characteristic data are temporally analyzed. A processing locale corresponding to the temporal analysis is identified and returned as output data, and one or more encoded actions in compliance with the identified processing locale are selectively implemented.