The purpose of the research was to assess the impact of Citizen Development activities on digital transformation. The research identified eight categories that contribute to the success of Low-code No-code (LCNC) proj...The purpose of the research was to assess the impact of Citizen Development activities on digital transformation. The research identified eight categories that contribute to the success of Low-code No-code (LCNC) projects: 1) Strategy;2) Infrastructure;3) Technology;4) Processes & Procedures;5) Governance;6) Culture;7) People;8) Goals & Metrics and selected six critical success factors from these categories: 1) Operational Efficiency;2) Time Savings;3) Timeframe to Realize Value;4) Employee Engagement;5) Participation;6) Number of Sponsored Ideas. End users of the digital transformation efforts through Citizen Development were asked to assess the six critical success measures in terms of performance and importance criteria. The research results identified that focus should be applied to improving “Timeframe to Realize Value”, on “Operational Efficiency”, and on “Time Savings” to deliver success.展开更多
Ever-changing market conditions and a rapidly changing IT landscape call for fast and cheap ways to meet software demands. In order to tackle these problems, low-code development platforms (LCDPs) have emerged. These ...Ever-changing market conditions and a rapidly changing IT landscape call for fast and cheap ways to meet software demands. In order to tackle these problems, low-code development platforms (LCDPs) have emerged. These platforms are designed with the idea to limit recurring traditional hand-coding and programming. This article provides a theoretical overview of low-code solutions. The advantages and disadvantages of using LCDP in the creation of automated systems are considered. In conclusion, a conclusion is formulated about the prospects of using low-code technology.展开更多
This paper aims to explore a simpler and more user-friendly way of generating software based on model-driven development.Previous studies have attempted to generate code from domain models,hoping to reduce coding time...This paper aims to explore a simpler and more user-friendly way of generating software based on model-driven development.Previous studies have attempted to generate code from domain models,hoping to reduce coding time by increasing modeling time.However,as code tools become more advanced,it is challenging to improve efficiency because models are abstract while implementations are concrete.This paper proposes a novel approach that integrates ChatGPT as a plug-in into the whole R&D process and combines it with our code generation tool to enhance R&D efficiency.We have developed some demos to demonstrate the effectiveness of our approach.According to our evaluation,our approach can save more than 90%of the work in implementing the code generation tool,leaving only about 10%of the work for code review,code improvement,and unit testing.展开更多
文摘The purpose of the research was to assess the impact of Citizen Development activities on digital transformation. The research identified eight categories that contribute to the success of Low-code No-code (LCNC) projects: 1) Strategy;2) Infrastructure;3) Technology;4) Processes & Procedures;5) Governance;6) Culture;7) People;8) Goals & Metrics and selected six critical success factors from these categories: 1) Operational Efficiency;2) Time Savings;3) Timeframe to Realize Value;4) Employee Engagement;5) Participation;6) Number of Sponsored Ideas. End users of the digital transformation efforts through Citizen Development were asked to assess the six critical success measures in terms of performance and importance criteria. The research results identified that focus should be applied to improving “Timeframe to Realize Value”, on “Operational Efficiency”, and on “Time Savings” to deliver success.
文摘Ever-changing market conditions and a rapidly changing IT landscape call for fast and cheap ways to meet software demands. In order to tackle these problems, low-code development platforms (LCDPs) have emerged. These platforms are designed with the idea to limit recurring traditional hand-coding and programming. This article provides a theoretical overview of low-code solutions. The advantages and disadvantages of using LCDP in the creation of automated systems are considered. In conclusion, a conclusion is formulated about the prospects of using low-code technology.
基金fully supported by the Natural Science Foundation of Hubei Province in China(Grant No.2021CFB482)Basic Research Science and Technology Project of Xiangyang(High-tech Domain 2022ABH007013)Hubei Superior and Distinctive Discipline Group of“New Energy Vehicle and Smart Transportation”。
文摘This paper aims to explore a simpler and more user-friendly way of generating software based on model-driven development.Previous studies have attempted to generate code from domain models,hoping to reduce coding time by increasing modeling time.However,as code tools become more advanced,it is challenging to improve efficiency because models are abstract while implementations are concrete.This paper proposes a novel approach that integrates ChatGPT as a plug-in into the whole R&D process and combines it with our code generation tool to enhance R&D efficiency.We have developed some demos to demonstrate the effectiveness of our approach.According to our evaluation,our approach can save more than 90%of the work in implementing the code generation tool,leaving only about 10%of the work for code review,code improvement,and unit testing.
