Survey on software defect prediction

One of the major challenges in modern software development is the extensive time and financial resources required to detect defects during the production process. Even with highly professional teams, software faults are inevitable and must be addressed to ensure product quality. With advancements in artificial intelligence (AI), particularly in machine learning (ML) and deep learning (DL), novel methods have emerged to predict software defects early in the development lifecycle. These technologies enhance the final product's reliability while reducing overall costs and time-to-market.

کلیدواژه ها:

aspect based sentiment analysis ، data augmentation ، back translation ، special character utilization ، software defect prediction ، defect prediction models ، defect types