1. Abstract
Intelligent debugging systems have a long history with interesting reports
produced by research prototypes and implemented applications. There has been
still lot of research going on in this field. There has been number of Artificial
Intelligence approaches to the development of Integrated Development
Environment (IDE)s. Modern integrated development environments make
recommendations, and automate common tasks, such as refactoring, auto-
completions, and error corrections. These tools provide the developers comfort
during coding by Tutoring. However, there are programs that have been developed
or generated in different ways like auto generation of source code from an
application, or source file built by scanning a handwritten code, etc.
Hence, there is a need for tools that not only provides recommendations during
programming but also efficiently debug and compile a source file that is given as
input. In this thesis, I have proposed a framework for Automatic compiling using
Pattern matching by Classification using Artificial Intelligence techniques like
Decision trees thus reducing the human interactions to the minimum. Here, the
scope of my work is on Java code as Java is heavily used in a variety of research
applications due to its ease of use, maintainability and reliability.