D2C Documentation
1. Overview
Our project generates demand text to class diagram. For example, "Teacher is a user. teacher has name. teacher can buy book." generates the class diagram as shown in Figure 1.
2. Tool We Used
2.1 OpenNLP
The Apache OpenNLP library is a machine learning based toolkit for the processing of natural language text. It supports the most common NLP tasks, such as tokenization, sentence segmentation, part-of-speech tagging, named entity extraction, chunking, parsing, and coreference resolution. These tasks are usually required to build more advanced text processing services. OpenNLP also includes maximum entropy and perceptron based machine learning. OpenNLP web page
2.2 JSUML
JS/UML is a plugin for the Eclipse IDE that creates UML models and diagrams from JavaScript code. JSUML web page
3. Our Rules
3.1 Rules for classes
In a sentence (we have limits. The rules can only be used for simple sentences. Nouns in a sentence will be take out as classes.)
3.2 Rules for relationships
If a sentence contains "am/is/are", the relationship will be generalization. If a sentence contains "has/have", the relationship will be aggregation. If a sentence contains other verbs, the relationship will be association.
4. Limits
We can only recognize simple sentences. Complex sentences and clauses will lead to problems. What's more the rules for operations and attributes are not done yet.