Semantic Rule-based Automatic Code conversion System

Most software employees are facing challenges on integrating programs written in different languages for implementing the techniques for their software development. This can be achieved by automating the conversion of programs using natural language programming techniques. This research presents a novel `Semantic Rule-based Automatic Code conversion System (SRACS)' that uses semantic layering, keyword identification, and a semantic rule-based constructor. The code snippets for `Hello World', `For Loop', `While Loop', `If else', `Factorial' and `Travelling Salesman Program' are converted from Java to Python and vice versa, and the accuracies are presented. An average accuracy of 71.57% is achieved for the conversion of the code snippets from Java to Python, and a 77.07% is achieved for Python to Java. The accuracy is based on the `accuracy in the conversion of the variables', `accuracy in the conversion of the attributes' and on the `proper indentation of the code in the target code'.