Duplicate bug reporting is a critical problem in the software repositories’mining area.Duplicate bug reports can lead to redundant efforts,wasted resources,and delayed software releases.Thus,their accurate identifica...Duplicate bug reporting is a critical problem in the software repositories’mining area.Duplicate bug reports can lead to redundant efforts,wasted resources,and delayed software releases.Thus,their accurate identification is essential for streamlining the bug triage process mining area.Several researchers have explored classical information retrieval,natural language processing,text and data mining,and machine learning approaches.The emergence of large language models(LLMs)(ChatGPT and Huggingface)has presented a new line of models for semantic textual similarity(STS).Although LLMs have shown remarkable advancements,there remains a need for longitudinal studies to determine whether performance improvements are due to the scale of the models or the unique embeddings they produce compared to classical encoding models.This study systematically investigates this issue by comparing classical word embedding techniques against LLM-based embeddings for duplicate bug detection.In this study,we have proposed an amalgamation of models to detect duplicate bug reports using textual and non-textual information about bug reports.The empirical evaluation has been performed on the open-source datasets and evaluated based on established metrics using the mean reciprocal rank(MRR),mean average precision(MAP),and recall rate.The experimental results have shown that combined LLMs can outperform(recall-rate@k 68%–74%)other individual=models for duplicate bug detection.These findings highlight the effectiveness of amalgamating multiple techniques in improving the duplicate bug report detection accuracy.展开更多
Tobacco leaf shapes including the length,width,area,perimeter and roundness parameters and so on,Only obtain exact boundaries of the leaf information to calculate a large number of leaf parameters.This paper introduce...Tobacco leaf shapes including the length,width,area,perimeter and roundness parameters and so on,Only obtain exact boundaries of the leaf information to calculate a large number of leaf parameters.This paper introduces the classical edge detection Methods,bug method is used to track the boundaries of tobacco leaf extractly.The test shows that the algorithm has a good edge extraction capability.展开更多
以外接激光测距仪的Pioneer3-AT移动机器人作为物理平台,用ARIA-Matlab接口软件实现对物理平台的控制与通信。通过Simulink自定义模块封装Bug算法,设计Matlab Graphical User Interfaces(GUI)界面设置仿真参数和动态显示仿真结果。经由...以外接激光测距仪的Pioneer3-AT移动机器人作为物理平台,用ARIA-Matlab接口软件实现对物理平台的控制与通信。通过Simulink自定义模块封装Bug算法,设计Matlab Graphical User Interfaces(GUI)界面设置仿真参数和动态显示仿真结果。经由笔者开发的折线Bug与圆弧Bug算法实验表明,该软件可灵活执行纯仿真、半实物仿真与物理执行3种工作方式,实验结果与实际情况吻合,验证了Bug避障算法,对经由传感器实时数据采集的路径规划算法研究具有参考意义。展开更多
文摘Duplicate bug reporting is a critical problem in the software repositories’mining area.Duplicate bug reports can lead to redundant efforts,wasted resources,and delayed software releases.Thus,their accurate identification is essential for streamlining the bug triage process mining area.Several researchers have explored classical information retrieval,natural language processing,text and data mining,and machine learning approaches.The emergence of large language models(LLMs)(ChatGPT and Huggingface)has presented a new line of models for semantic textual similarity(STS).Although LLMs have shown remarkable advancements,there remains a need for longitudinal studies to determine whether performance improvements are due to the scale of the models or the unique embeddings they produce compared to classical encoding models.This study systematically investigates this issue by comparing classical word embedding techniques against LLM-based embeddings for duplicate bug detection.In this study,we have proposed an amalgamation of models to detect duplicate bug reports using textual and non-textual information about bug reports.The empirical evaluation has been performed on the open-source datasets and evaluated based on established metrics using the mean reciprocal rank(MRR),mean average precision(MAP),and recall rate.The experimental results have shown that combined LLMs can outperform(recall-rate@k 68%–74%)other individual=models for duplicate bug detection.These findings highlight the effectiveness of amalgamating multiple techniques in improving the duplicate bug report detection accuracy.
基金Supported by Key Technologies R & D Program of Henan Province(082102210065)Natural Science Research Project of Henan Educational Committee(2007210005)~~
文摘Tobacco leaf shapes including the length,width,area,perimeter and roundness parameters and so on,Only obtain exact boundaries of the leaf information to calculate a large number of leaf parameters.This paper introduces the classical edge detection Methods,bug method is used to track the boundaries of tobacco leaf extractly.The test shows that the algorithm has a good edge extraction capability.
文摘以外接激光测距仪的Pioneer3-AT移动机器人作为物理平台,用ARIA-Matlab接口软件实现对物理平台的控制与通信。通过Simulink自定义模块封装Bug算法,设计Matlab Graphical User Interfaces(GUI)界面设置仿真参数和动态显示仿真结果。经由笔者开发的折线Bug与圆弧Bug算法实验表明,该软件可灵活执行纯仿真、半实物仿真与物理执行3种工作方式,实验结果与实际情况吻合,验证了Bug避障算法,对经由传感器实时数据采集的路径规划算法研究具有参考意义。
