Estimating the software effort is a key factor for projects in the IT area, as it encompasses issues such as hours of a contract, workforce, deadlines and costs.
The search for accuracy in the result delivered to the customer can become a major challenge, as erroneous information can bring damage to both the supplier and customer.
Thinking about these issues, student Eliane De Bortoli, aims to develop a way to estimate software using Natural Language Processing techniques and Machine Learning.
CINQ supports the project by giving textual data of project requirements already carried out in the company.
She is graduated in Data Processing by UTFPR, with a specialization in Computer Science by UFSC and Master’s Degree in Electrical Engineering and Industrial Informatics by UTFPR. the researcher states that the interest for questions regarding estimates of software projects arose from the classes, in which she perceived the difficulty in discovering an effective solution for software estimation.