This paper describes a novel approach for detecting faultprone modules using a spam filtering technique. Fault-prone module detection in source code is important for the assurance of software quality. Most previous fault-prone detection approaches have been based on using software metrics. Such approaches, however, have difficulties in collecting the metrics and constructing mathematical models...

The past 20 years have seen the formulation of numerous analytical software reliability models for estimating the reliability growth of a software product. The predictions obtained by applying these models tend to be optimistic due to the inaccuracies in the operational profile, and saturation effect of testing. Incorporating knowledge gained about some structural attribute of the code, such as...

Machine learning techniques have been dominating in the last two decades. The recently published comprehensive state-of-the-art review (Mohanty et al., 2010) justifies this issue. The ability of software quality models to accurately identify critical faulty components allows for the application of focused verification activities ranging from manual inspection to automated formal analysis method...

The past 20 years have seen the formulation of numerous analytical software reliability models for estimating the reliability growth of a software product. The predictions obtained by applying these models tend to be optimistic due to the inaccuracies in the operational pro le, and saturation e ect of testing. Incorporating knowledge gained about some structural attribute of the code such as te...

A number of papers have investigated the relationships between design metrics and the detection of faults in objectoriented software. Several of these studies have shown that such models can be accurate in predicting faulty classes within one particular software product. In practice, however, prediction models are built on certain products to be used on subsequent software development projects....

Defect prediction models are significantly beneficial for software systems, where testing experts need to focus their attention and resources on problematic areas in the software under development. In this paper we find the relation between object oriented metrics and fault proneness using logistic regression method. The results are analyzed using open source software. The performance of the pr...

Defect prediction includes tasks that are based on methods gener ated using software fault data sets and requires much effort to be completed. In defect prediction, although there are methods to conduct an analysis involving the classification of data sets and localisation of defects, those methods are not sufficient without eliminating repeated data points. The NASA Metrics Data Program (Nasa ...

In this paper, we critically analyze the success of the traditional reliability models built to measure and estimate software reliability. We further propose that a Finite State Automata (FSA) based reliability model can serve as a befitting solution to all existing software reliability challenges. The proposed model estimates actual system reliability at runtime. The main advantage of this mod...