Software project effort estimation using genetic programming

Knowing the estimated cost of a software project early in the development cycle is a valuable asset for management. In this paper, an evolutionary computation method, grammar guided genetic programming (GGGP), is used to fit models, with the aim of improving the prediction of software development costs. Valuable results are obtained, significantly better than those obtained by simple linear regression. In this research, GGGP, because of its flexibility and the ability of incorporating background knowledge, also shows great potential in being applied in other software engineering modeling problems.