arXiv subjects

Mamdouh Alenezi

Publications and source records attributed to Mamdouh Alenezi.

20 records · Page 2Linked to original sources

arXiv2018

Using Categorical Features in Mining Bug Tracking Systems to Assign Bug Reports

Most bug assignment approaches utilize text classification and information retrieval techniques. These approaches use the textual contents of bug reports to build recommendation models. The textual contents of bug reports are usually of high dimension and noisy source of information. These approaches suffer from low accuracy and high computational needs. In this paper, we investigate whether using categorical fields of bug reports, such as component to which the bug belongs, are appropriate to represent bug reports instead of textual description. We build a classification model by utilizing the categorical features, as a representation, for the bug report. The experimental evaluation is conducted using three projects namely NetBeans, Freedesktop, and Firefox. We compared this approach with two machine learning based bug assignment approaches. The evaluation shows that using the textual contents of bug reports is important. In addition, it shows that the categorical features can improve the classification accuracy.

cs.SE↗

arXiv2015

Quality of Open Source Systems from Product Metrics Perspective

Software engineering and information systems practices seek ultimately to create the flawless product. One of the tools used to improve the quality of software development is the use of metrics. In this paper, metrics retrieved from open source software were analyzed for quality attributes. Defect density is considered a strong indication of the quality of software product. Few studies have taken into consideration the density of defects while looking into quality of software and proneness to defects. Analysis of this study has shown that defect density is relevant to different developers and different product sizes. Thus, open source project has shown to have low defect density and the larger the product the lower the defect density is. In addition, this study has shown that there are different metrics that correlate with each other indicating that some of these metrics have conceptual and practical relevance to each other. Another relationship was tested between the number of bugs and the metrics. Results indicated that most attributes had positive correlation with the number of bugs with exception to coupling between cohesion among methods of class.

cs.SE↗