The aim of this work is to develop an Automatic Programming system drawing inspiration from biological genetic systems. Grammatical Evolution (GE), a system which can generate code in any language from variable length binary strings is the result of this investigation. Using a language definition in the form of a Backus Naur Form grammar permits the generation of programs in any language, of ar...

In a virtual university, advanced support for all aspects of handling assignments is needed. Homework assignments are particularly in need of help because communication between teachers and learners as well as between learners is not as easy as in presence universities. In this paper, we present an overview of the AT(x) approach (analyze-and-test) for automatically analyzing and testing program...

In today’s world study of computer’s language is more important. Effective and good programming skills are need full all computer science students. They can be master in programming, only through intensive exercise practices. Due to day by day increasing number of students in the class, the assessment of programming exercises leads to extensive workload for teacher/instructor, particularly if i...

The research presented in the paper forms part of a larger initiative aimed at automatic algorithm induction using machine learning. This paper compares the performance of two machine learning techniques, namely, genetic programming and a variation of genetic programming, grammatical evolution, for automatic algorithm induction. The application domain used to evaluate both the approaches is the...

This paper describes an approach for automatically decomposing a problem into subproblems, automatically creating reusable subroutines to solve the subproblems, and automatically assembling the results produced by the subroutines in order to solve the problem. The approach uses genetic programming with the recently developed additional facility of automatic function definition. Genetic programm...