This paper reviews the use of Bayesian networks (BNs) in predicting software defects and
software reliability. The approach allows analysts to incorporate causal process factors as …

There are lots of different software metrics discovered and used for defect prediction in the
literature. Instead of dealing with so many metrics, it would be practical and easy if we could …

An important decision in software projects is when to stop testing. Decision support tools for
this have been built using causal models represented by Bayesian Networks (BNs) …

Even though the use of agile methods in software development is increasing, the problem of
effort estimation remains quite a challenge, mostly due to the lack of many standard metrics …

In this paper, we present a model for software effort (person-month) estimation based on
three levels Bayesian network and 15 components of COCOMO and software size. The …

Software defect predictors are useful to maintain the high quality of software products
effectively. The early prediction of defective software modules can help the software …

Bayesian Networks (BNs) are probabilistic inference engines that support reasoning under
uncertainty. This article presents a methodology for building an information technology (IT) …

As business transitions into the new economy, e-system successful use has become a
strategic goal. Especially in business to consumer (e-commerce) applications, users highly …

Bayesian networks, which can combine sparse data, prior assumptions and expert judgment
into a single causal model, have already been used to build software effort prediction …

Managing software maintenance is rarely a precise task due to uncertainties concerned with
resources and services descriptions. Even when a well-established maintenance process is …