Automated Software Design Using Machine Learning with Natural Language Processing

Designing is the most difficult task in software production and development. Researchers are trying to add automation to the software design and development process. This is because of the daily increase of demanding software production; the quality growth of automotive software design makes designers respond more quickly to the refreshed demands. One of the good designing methods is to use of data mining. In this research, the decision tree algorithm method is used to identify classes and detect relationships between classes automatically. The data input is the proposed method is the use case descriptions software and its output is the list of classes with relationships between them. This method has three 3 stages: First, the use case description scenarios are analyzed by natural language processing tools. In the next step, by setting rules, the data set is created, and then the decision tree algorithm is executed on the dataset. Output is the list of classes along with the type of relationship between them. Extracting of association relations one-to-one, one-to-many, and many-to-many and association relationships. ATM, CBS, GDP, and SC case studies have been used. In this research, an attempt has been made to provide a method that has better results than previous methods. The accuracy and F-score of proposed method on the ATM dataset are 90% and 0.93 which is a value of accuracy and F-score is better than similar research and has better results.