Finding defects in software is a challenging and time and budget consuming task. Minimizing these adverse effects using software defect prediction models via guiding testers with defective parts of software system is an attractive research area. Previous research emphasized the value of these tools with a mean probability of detection of 71 percent and mean false alarm rates of 25 percent. This...

This paper is concerned with two theories of probability judgment: the Bayesian theory and the theory of belief functions. It illustrates these theories with some simple examples and discusses some of the issues that arise when we try to implement them in expert systems. The Bayesian theory is well known; its main ideas go back to the work of Thomas Bayes (1702-1761). The theory of belief funct...

In pattern analysis, information regarding an object can often be drawn from its surround­ ings. This paper presents a method for handling uncertainty when using context of symbols and texts for analyzing technical drawings. The method is based on Dempster-Shafer theory and possibility theory. 1 Introduction In several pattern analysis problems it is interesting to look at the context in which ...

The present state of development of Dempster-Shafer theory is surveyed and its place among theories of dealing with uncertainty in AI is discussed. No knowledge of the theory is assumed.

We propose an extended relational database model which can model both uncertainty and imprecision in data. This model is based on Dempster-Shafer theory which has become popular in AI as an uncertainty reasoning tool. The definitions of Be1 and Pls functions in Dempster-Shafer theory are extended to compute the beliefs of various comparisons (e.g., equality, less than, etc.) between two basic p...

Automated ontology population using information extraction algorithms can produce inconsistent knowledge bases. Confidence values assigned by the extraction algorithms may serve as evidence helping to repair produced inconsistencies. The Dempster-Shafer theory of evidence is a formalism, which allows appropriate interpretation of extractors’ confidence values. The paper presents an algorithm fo...