Design And Implementation Of UML Model Generation Tool Based On NLP Technology

In the software development life cycle,software requirements analysis and design are the two initial slow links in the life cycle,and they are also two of the most important links.In the requirements analysis phase,software designers use software engineering-related expertise and multiple relevant knowledge in the software application field to understand and refine the software requirements proposed by users,distinguish between functional and non-functional requirements,and then in the software design phase Outline and detailed design for the functional requirements and construct the corresponding domain model,which is usually represented by UML(Unified Modeling Language)model.However,because software designers usually do not have enough knowledge about the fields to which the software is applied to understand user requirements quickly and completely,software designers also need to spend some time to become familiar with and learn the relevant fields before they can begin Domain modeling.In addition,when the requirements change frequently or the requirements change to a large extent,software designers also need to invest more energy to understand the new needs of users.The emergence of these situations will reduce the efficiency of software designers in software requirements modeling.Therefore,in order to improve the efficiency of the conversion of user requirements in the form of natural language to the Unified Modeling Language(UML)model,this paper uses natural language processing technology(NLP)research to achieve A tool for automatically generating class diagrams and use case diagrams in UML models.This tool uses the implementation ideas of named entity recognition tasks and relationship extraction tasks in natural language processing to automatically generate class diagrams and use case diagrams of software requirements texts proposed by users,so as to provide ideas and references for software requirements personnel to model software requirements in the domain.Help software designers complete software requirements modeling more efficiently.The main work of this article is as follows:1.Constructed a text data set in the software requirements area.By looking for documents for software requirements design analysis on the Internet,and manually inputting software requirements texts in paper books related to software engineering and UML models with the help of library collection resources,software requirements for some practical application projects were also collected Documents,and then preliminary filtering and integration of these text resources to build a text data set.2.Use deep learning models combined with rules to identify the constituent elements of class diagrams and use case diagrams in text.At present,most of the UML model automatic generation tools for published papers in the academic community are based on the method of syntactic analysis and rule matching.This method requires the design of a large number of grammatical rules to achieve high accuracy and poor scalability..This tool uses deep learning-based methods to be more flexible and does not require very specialized grammar knowledge to implement.3.The functional modules of the UML model generation tool based on NLP technology are divided and designed,and the overall development of the tool is completed using the web application development technology separated from the front and back ends,which is currently running smoothly.