PREDICT AND APPROXIMATE SOFTWARE QUALITY WITH BAYESIAN NETWORKS AND QUALITY FACTORS

Software quality is one of important field in software engineering that related to software satisfaction. Some models and methods have made to calculating quality. Almost all of these models use quality factors or metrics, but calculate them is another problem because we can not calculate them exactly or can not determine some of them in some software project and usually our data about quality factors and metrics are incomplete or uncertain. Also these models can not predict software quality before calculate all of quality metrics and factors. Bayesian Networks have become a popular tool for modeling many kinds of statistical problems over the last decade. In this paper we proposed a model for software quality with BNs and ISO9126 quality model. ISO9126 is one of best and complete quality model. This new model doesn't have last quality model's problems and can predict software quality with incomplete and uncertain data. Also by this model we can reduce time and cost of calculating software quality.

Software Quality Model, Bayesian Networks, ISO9126