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Software project failures prediction using logistic regression modeling

机译:使用逻辑回归建模的软件项目故障预测

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The prediction of software project failure early can help in taking an enhancement steps that can steer the project outcome from failure to success. A range of risks may affect the software project during the development process and may lead to project failure. This paper presents a software project failure evaluation model developed based on real data collected from different software project reports, surveys and case studies. The constructed dataset describes the relationship between software project failure and independent failure factors. In this paper, the researchers have developed a failure prediction model using logistic regression method. This model can be used by project managers to assess the expected failures. The developed model helps in estimating the project outcome (Failed/Success). Furthermore, the model provides a probability of software project failure. The model is developed to enable the project decision makers to perform evaluation for the project status during any phase of the software development life cycle.
机译:对软件项目失败的早期预测可以帮助您采取增强措施,使项目结果从失败变为成功。一系列风险可能会在开发过程中影响软件项目,并可能导致项目失败。本文提出了一个软件项目失败评估模型,该模型是基于从不同软件项目报告,调查和案例研究中收集的真实数据开发的。构造的数据集描述了软件项目故障和独立故障因素之间的关系。在本文中,研究人员使用逻辑回归方法开发了一个故障预测模型。项目经理可以使用此模型来评估预期的失败。开发的模型有助于估计项目结果(失败/成功)。此外,该模型提供了软件项目失败的可能性。开发该模型是为了使项目决策者能够在软件开发生命周期的任何阶段对项目状态进行评估。

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