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首页> 外文期刊>International journal of open source software & processes >Fault Prediction Modelling in Open Source Software Under Imperfect Debugging and Change-Point
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Fault Prediction Modelling in Open Source Software Under Imperfect Debugging and Change-Point

机译：调试和变更点不完善的开源软件中的故障预测建模

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摘要

Instant demand of products and services by technologically active users has increased the demand for open source software (OSS)-based applications. Unfortunately, with the complexity and lack of understanding of OSS-based systems, it becomes difficult for a testing team to remove the faults and the fault removal rate becomes low in comparison to what it should be. This also results in generating new faults during removal. Also, the rate at which the testing team detects/corrects fault need not be same during the entire process of testing due to various reasons viz. change in testing strategy, understanding of code, change in resources, etc. In the existing literature on OSS, authors have developed many models considering the above aspects separately. In this article, all of the above aspects have been combined to develop a general framework for predicting the number of faults in OSS. The comparison of eight models on the basis of their prediction capability on two well-known Open Source Software datasets is created and then ranked using normalized criteria distance approach.
机译：技术活跃的用户对产品和服务的即时需求增加了对基于开源软件（OSS）的应用程序的需求。不幸的是，由于复杂和缺乏对基于OSS的系统的了解，测试团队很难清除故障，并且故障清除率与应有的水平相比降低了。这也导致在移除期间产生新的故障。同样，由于各种原因，在整个测试过程中，测试团队发现/纠正故障的速率也不必相同。改变测试策略，理解代码，改变资源等。在有关OSS的现有文献中，作者分别考虑上述方面开发了许多模型。在本文中，上述所有方面均已组合在一起，以开发出一个通用框架来预测OSS中的故障数量。创建了基于两个著名的开源软件数据集的预测能力的八个模型的比较，然后使用归一化标准距离方法进行排名。

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