With the increasing demand for software systems, the software development industry is also developing rapidly. With the development of information technology, the more functions of the software, the more valuable it is, so the function design of the software becomes more complicated and difficult. The design of software system functions is increasingly large and complex. Scientific and effective use of software configuration management can well deal with collaborative work problems such as version management and change control in the software development process. In the process of software development and configuration, there will always be many problems that are difficult to detect. For example, when inputting the program code, there are not always some letter or space errors, and these errors are difficult to detect in time. For this reason, we need to establish a monitoring and management system for software development. As a computing model of human brain neural network, the artificial neural network can play the role of monitoring and management when it is applied to software development and configuration, which provides support for the security and scientificity of software development and configuration systems. This study studies the role and effectiveness of an artificial neural network in the monitoring and management of software development and configuration and validates it through experiments. The experimental results show that the artificial neural network has a strong ability to identify the problems in the software development configuration, which can improve the software development efficiency by at least 20%. It can improve the quality of software development and then improve the life cycle of software.
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