A Defect is Being Born: How Close Are We? A Time Sensitive Forecasting Approach
This addresses the need for proactive defect prediction in evolving software systems for developers and researchers, but appears incremental as it builds on existing just-in-time prediction methods.
The study tackles the problem of forecasting software defects before they manifest by exploring time-sensitive techniques and early indicators, aiming to provide empirical evidence on the effectiveness of early bug proneness estimation.
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.