Predicting Software Defect Complexity and Accuracy using Bug Tracking and Clustering

Swetha. S, A.Poongodi
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Abstract

Many open sources, free and commercial bug tracking tools have been developed and are currently under development. There are number of issues are related to software projects are daily increasing and the developers are started to use bug tracking systems in that order to manages the bug reports. The industry needs that the criteria to select the best system tool among the available set of system tools which will helps to fix and track the progressive report of bug fixes. While, collection of useful information from the large and not organized set of these reports is still difficult problem because there are various bug tracking systems are provide the data via many resources like web interfaces. We try to present these comprehensive classification criteria to manage the reviews for available tools and propose a new modified tool for the bug tracking and reporting system. It also helps in reporting the bugs which are founded by that process, assigning the bug to the developer for monitoring and fixing the progress of bug fixing by various graphical/charting facility and status updates. It also providing the reliability of bug prediction and tries to find the bugs for complexity measurements, and allows to distributing.
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利用 Bug 跟踪和聚类预测软件缺陷复杂性和准确性
许多开源、免费和商业的错误跟踪工具已经开发出来,目前正在开发中。与软件项目相关的问题数量与日俱增,开发人员开始使用错误跟踪系统来管理错误报告。业界需要从现有的系统工具中选择最佳系统工具的标准,这将有助于修复和跟踪错误修复的进展报告。然而,从这些报告中收集有用信息仍然是个难题,因为有各种错误跟踪系统通过网络接口等多种资源提供数据。我们尝试提出这些综合分类标准,以管理对现有工具的审查,并为错误跟踪和报告系统提出一种新的修改工具。它还有助于报告由该过程发现的错误,将错误分配给开发人员,以便通过各种图形/图表设施和状态更新来监控和修复错误的进度。它还能提供可靠的错误预测,并尝试查找复杂性测量的错误,并允许进行分发。
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