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.

翻译：背景。缺陷预测一直是实证软件工程领域研究者高度关注的主题。已有文献通过即时预测方法，成功实现了对未来故障的最准确预测，并识别了故障发生前的特征与异常。随着软件系统的持续演化，对能够在缺陷显现前进行预测的时间敏感方法的需求日益增长。目标。本研究旨在探索时间敏感技术在缺陷预测中的有效性。此外，我们致力于探究缺陷发生前的早期预警指标。方法。我们将训练多种时间敏感的预测技术，以预测软件项目未来的缺陷密度，并识别缺陷发生前的早期征兆。预期结果。我们的预期结果将转化为关于本方法在早期评估缺陷倾向性方面有效性的实证证据。