Abstract: To identify the incompleteness and ambiguity of software requirements and build a bridge between software requirements and standard specifications,this paper proposed a model of analysis and evaluation based on the Natural Language Processing (NLP) and neural network.Firstly,from ISO,the open-source Web application security plan (OWASP) and the PCI directory,multiple security specification features are identified,and text implication relationships are found.Then,the implication results and text annotations are used to train the neural network model to predict whether a certain statement in the document is available.The proposed model evaluates the performance of each implication configuration.The results show that the average F- score of the implicative configuration 9 is the highest,which is the best completeness predictor.Moreover,the performance of the proposed model is better than that of the null model under optimal and worst allocation.

Key words: Implication relationships, Natural language processing, Neural networks model, Null model, Security, Software requirements