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Software systems are normally developed in a number of releases. Each release usually modifies existing code. In this study we show that such modified code can be an important source of faults. Since faults are considered major cost drivers of software projects, the ability to identify fault-prone classes before they are implemented would give a chance to(More)
Statistical fault prediction models and expert estimations are two popular methods for deciding where to focus the fault detection efforts when the fault detection budget is limited. In this paper, we present a study in which we empirically compare the accuracy of fault prediction offered by statistical prediction models with the accuracy of expert(More)
In the human organism 58 cytochrome P450 (CYP) isoenzymes belonging to 18 families have been described. These hemoproteins, with enzymatic activity characteristic for monooxygenases, show a broad affinity for chemically differentiated endo- or exogenous compounds, including drugs. CYP isoenzymes participate in metabolic pathways important for proper(More)
Fault prediction models still seem to be more popular in academia than in industry. In industry expert estimations of fault proneness are the most popular methods of deciding where to focus the fault detection efforts. In this paper we present a study in which we empirically evaluate the accuracy of fault prediction offered by statistical models as compared(More)
In this paper we suggest and evaluate a method for predicting fault densities in modified classes early in the development process, i.e., before the modifications are implemented. We start by establishing methods that according to literature are considered the best for predicting fault densities of modified classes. We find that these methods can not be(More)
Many software systems are developed in a number of consecutive releases. In each release not only new code is added but also existing code is often modified. In this study we show that the modified code can be an important source of faults. Faults are widely recognized as one of the major cost drivers in software projects. Therefore, we look for methods(More)