Disclosed is a method of as you type error checking of a spreadsheet formula as a user types the formula in a cell, including analyzing, as you type, the cell contents of the spreadsheet formula and throwing an error message when the cell contents are not valid in the formula being typed. The error message identifies/emphasizes a token or group of tokens that cause the error. Also disclosed is selecting and populating into a spreadsheet formula a formulaic data field to be evaluated, starting from a position in the spreadsheet formula where the formulaic data field to be evaluated is to be populated, and responding to typed inputs and/or UI selection by displaying a list of selectable formulaic data fields with additional information that contains (non-data derived) human generated values. Upon selection among the fields, the method includes automatically populating into the starting position in the spreadsheet formula.

Various embodiments facilitate a user to program and control one or more devices through a control system. In some embodiments, an interface is provided to enable the user to manipulate one or more program elements graphically. The one or more program elements include a first program element corresponding to the task, and a user input is provided by the user through a user manipulation of the first program element in the interface. The user manipulation comprises drag and drop, voice control, gesture control and/or any other mode of control. In those embodiments, the user input is then converted a first code understandable to the control system. The first code is then transmitted to the control system through a communication protocol. After the first code is received, a first instruction is generated by the control system and is transmitted to an end device for execution by the first instruction.

Implementations are described herein for leveraging prior source code transformations to facilitate automatic creation and/or recommendation of tools for automating aspects of source code transformations captured in real time. In various implementations, a transformation made by a programmer to a source code snipped may be captured in a source code editor application in real time. Based on the transformation and the intent, one or more candidate source code transformations may be identified from one or more repositories of prior source code transformations made by one or more other programmers. The source code editor application may be caused to provide output indicative of a tool that is operable to automate one or more edits associated with both the transformation made by the programmer to the source code snippet and with one or more of the candidate source code transformations.

How to correctly understand natural language query and catch the useful information from it is a long-standing research question in the chatbot field. However, in many cases only a small set of words are sufficient for closed-domain tasks. In this paper, we propose Minimal Dictionary Language (MDL): a simple language architecture which allows users to express their needs through certain basic syntax. For the pilot study, we selected Enron email open dataset[2] for our experimental use and apply MDL as the language for email retrieval task. We also built a front-end search interface by Python Flask and Vue.js for test and evaluation purposes.

How to correctly understand natural language query and catch the useful information from it is a long-standing research question in the chatbot field. However, in many cases only a small set of words are sufficient for closed-domain tasks. In this paper, we propose Minimal Dictionary Language (MDL): a simple language architecture which allows users to express their needs through certain basic syntax. For the pilot study, we selected Enron email open dataset[2] for our experimental use and apply MDL as the language for email retrieval task. We also built a front-end search interface by Python Flask and Vue.js for test and evaluation purposes.

Code may be analyzed according to natural language descriptions of coding practices. A practice for code written in a natural language description may be received. An embedding of the natural language description may be generated using a machine learning model trained to detect examples of practices. The embedding may be compared with embeddings of code portions stored in an index to detect one or more portions of code that satisfy a facet of the practice. The detected portions of code may be identified.

Code may be analyzed according to natural language descriptions of coding practices. A practice for code written in a natural language description may be received. An embedding of the natural language description may be generated using a machine learning model trained to detect examples of practices. The embedding may be compared with embeddings of code portions stored in an index to detect one or more portions of code that satisfy a facet of the practice. The detected portions of code may be identified.

An embodiment of the present invention is directed to a Mainframe CI/CD design solution and pattern that provides a complete end to end process for Mainframe application. This enables faster time to market by performing critical SDLC processes, including build, test, scan and deployment in an automated fashion on a regular basis. An embodiment of the present invention is directed to a CI/CD approach that journeys from receiving requirements to final deployment. For any new application onboarding, teams may implement the CI/CD approach that may be customized per requirements of each LOB/Application.

An embodiment of the present invention is directed to a Mainframe CI/CD design solution and pattern that provides a complete end to end process for Mainframe application. This enables faster time to market by performing critical SDLC processes, including build, test, scan and deployment in an automated fashion on a regular basis. An embodiment of the present invention is directed to a CI/CD approach that journeys from receiving requirements to final deployment. For any new application onboarding, teams may implement the CI/CD approach that may be customized per requirements of each LOB/Application.

This application discloses method, an apparatus, a storage medium, and an electronic device for bar code generation and display. The method includes: obtaining a target code by compiling a source code, the target code being self-contained executable code comprising target computer readable instructions and comprising logic functions, wherein the target computer readable instructions are executable by a processor; and generating a target bar code embedded with the target code by encoding the target code, wherein the target code comprises at least one of the following logical functions: a first logical function for allowing a scanning device with a read permission to run the target code, a second logical function for allowing the target code to be run within a validity period, and a third logical function for calling and configuring target hardware in the scanning device to execute a target operation.