提前预测软件缺陷出现时间，识别早期异常信号。
A Defect is Being Born: How Close Are We? A Time Sensitive Forecasting Approach
- 用时间敏感模型预测未来缺陷密度。
- 发现缺陷出现前的早期异常特征。
- 适合关注软件质量预警的开发团队。
缺陷预测是实证软件工程领域的重要研究方向。以往研究已实现对即将出现的缺陷进行精准预测，并通过即时预测识别出其前置特征与异常。随着软件系统持续演化，亟需能够提前预警缺陷的时间敏感方法。本研究旨在探索时间敏感技术在缺陷预测中的有效性，并分析缺陷发生前的早期指标。我们计划训练多种时间敏感预测模型，以预测软件项目的未来缺陷密度，并识别缺陷出现前的早期征兆。预期结果将为缺陷易发性的早期估算提供实证依据。
原文摘要 · Abstract (English)
Background. Defect prediction has been a highly active topic among researchers in the Empirical Software Engineering field. Previous literature has successfully achieved the most accurate prediction of an incoming fault and identified the features and anomalies that precede it through just-in-time prediction. As software systems evolve continuously, there is a growing need for time-sensitive methods capable of forecasting defects before they manifest. Aim. Our study seeks to explore the effectiveness of time-sensitive techniques for defect forecasting. Moreover, we aim to investigate the early indicators that precede the occurrence of a defect. Method. We will train multiple time-sensitive forecasting techniques to forecast the future bug density of a software project, as well as identify the early symptoms preceding the occurrence of a defect. Expected results. Our expected results are translated into empirical evidence on the effectiveness of our approach for early estimation of bug proneness.
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