Analysis of automated estimation models using machine learning

Plenty of practice based on software estimation has been developed in software industry. Algorithmic models represent the most formal approach that have provided the most reliable results. However, the use of informal practice is still prevalent just like the expert judgment which will not allow Software Engineering grow up. An important activity in big and small companies is to generate reliable estimation models. The development of these models is usually based on information obtained from past projects and requires a deep and precise analysis. This paper presents the application of the automated estimation-model generator system that uses machine learning techniques whit the objective of analysing the accuracy of these models comparing them to the traditional estimation methods using an international database and the internal database of a company.