Author: Luk

This project aims to improve evidence-based decision-making. What makes it radical is that it plans to do this in situations (common for critical risk assessment problems) where there is little or even no data, and hence where traditional statistics cannot be used. To address this problem Bayesian analysis, which enables domain experts to supplement observed data with subjective probabilities, is …

Effective Bayesian Modelling with Knowledge Before Data Read more »

The aim of the project is to develop a Bayesian net for software quality prediction. This model integrates multiple sources of data/konwledge. It adopts the most important advantages of existing software quality models, results of analyses of empirical data, and expert knowledge. The model provides new functionality by predicting various mutually related software quality factors using rigorous probability calculus. Developed …

Integrated probabilistic model for software quality prediction Read more »

The goal of the project is to develop analytical models for estimating effort, risk and cost/benefit for activities directed toward quality assurance and quality management in large software projects. These models should take into account various factors describing the nature of software projects and the process of its development. They should integrate qualitative expert knowledge and results of empirical analyses, …

Integrated analysis and prediction of software quality effort Read more »

The work will define a risk taxonomy to apply to existing and new models (Bayesian nets) for software project risk assessment. We will also develop a tool to help develop, manage and use models applying the risk taxonomy. We also analyse extending this approach to other disciplines.

The main goal of the project is to develop an integrated ERP-class IT system supporting management of local government’s unit.