Birt_HyLoc_Based_错误定位模型评估数据集

本数据集为错误定位模型HyLoc的评估数据，包含Birt项目相关文件。HyLoc结合深度神经网络（DNN）与信息检索技术rVSM，解决错误报告与源码间的词汇不匹配问题，提升错误定位准确率。数据集含两个文件，用于验证模型在实际项目中的性能表现。

This dataset is the evaluation data for the fault localization model HyLoc, and comprises files related to the Birt project. HyLoc combines Deep Neural Networks (DNN) and the information retrieval technique rVSM to address the lexical mismatch issue between fault reports and source code, thereby enhancing the accuracy of fault localization. The dataset contains two files, which are utilized to validate the model's performance in real-world software projects.