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 »

Starting 1 April 2015 I have taken the part-time programmer role in the BAYES-KNOWLEDGE EU-funded project. The project significantly enhances the way of building Bayesian network models by domain experts and, partially, from empirical data. It is managed by Professor Norman Fenton and held at the Queen Mary, University of London. Looking forward to it…

After reviewing the papers presented in this conference, my paper “An Expert-Driven Bayesian Network Model for Simulating and Predicting Software Quality” has been awarded as one of the top papers of the Fifth International Conference on Information, Process, and Knowledge Management (eKNOW 2013).

Please consider submitting a paper to a Polish Conference on Software Engineering (KKIO) and/or the Congress of Young IT Scientists (SMI). Both conferences will take place in Szczecin, Poland on 18-20 Sept. 2013. I am a PC member in both of them. See a flyer for these conferences.

Welcome to my new site! I have just moved old contents to a new domain lukaszradlinski.com. All earlier links should forward you to this new location. I also took this opportunity and refreshed the graphical appearance with a completely new theme called Responsive. Some work is not finished yet but I hope I will manage to do it soon…

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 »