Bayesian Analysis of Empirical Software Engineering Cost Models

To date many software engineering cost models have been developed to predict the cost, schedule and quality of the software under development. But, the rapidly changing nature of software development has made it extremely difficult to develop empirical models that continue to yield high prediction accuracies. Software development costs continue to increase and practitioners continually express their concerns over their inability to accurately predict the costs involved. Thus, one of the most important objectives of the software engineering community has been to develop useful models that constructively explain the software development life-cycle and accurately predict the cost of developing a software product. To that end, many parametric software estimation models have evolved in the last two decades [Putnam92, Jones97, Park88, Jensen83, Rubin83, Boehm81, Boehm95, Walkerden97, Conte86, Fenton91, Masters85, Mohanty81].