Software effort estimation accuracy is a key factor in effective planning, controlling, and
delivering a successful software project within budget and schedule. The overestimation and …

Software cost models and effort estimates help project managers allocate resources, control
costs and schedule and improve current practices, leading to projects finished on time and …

Software development has become an essential investment for many organizations.
Software engineering practitioners have become more and more concerned about …

This paper tackles two questions related to software effort prediction. First, is it valuable to
combine prediction techniques? Second, if so, how? Many commentators have suggested …

We derive a model for estimating adaptive software maintenance effort in person hours, the
adaptive maintenance effort model (AMEffMo). A number of metrics such as lines of code …

(COCOMO) is considered to be the most widely used model for effort estimation. Cost drivers
have significant influence on the COCOMO and this research investigates the role of cost …

The decision tree (DT) represents a nonparametric estimation method that has been mostly
used for both classification and regression problems. DTs were adopted for software …

Several studies have compared the prediction accuracy of different types of techniques with
emphasis placed on linear and stepwise regressions, and case-based reasoning (CBR). We …

Now a days, software development organizations use machine learning techniques in
different areas to improve decision-making process so that their performance is boosted. In …

We investigate the use of data mining for the analysis of software metric databases, and
some of the issues in this application domain. Software metrics are collected at various …