Various approaches have been proposed for extracting microservices from the source code of monolithic software systems. the extracted microservices are usually evaluated by using the metrics of the precision and recal...
详细信息
Probabilistic timed systems are increasingly crucial in modern system architecture. Ensuring the correctness of system behavior has become a crucial problem, and model checking offers a solution. However, it is a chal...
详细信息
the proceedings contain 171 papers. the topics discussed include: ImVR: enabling immersive design exploration and process integration for additive manufacturing of complex organic geometries;investigation of distribut...
ISBN:
(纸本)9780791888117
the proceedings contain 171 papers. the topics discussed include: ImVR: enabling immersive design exploration and process integration for additive manufacturing of complex organic geometries;investigation of distributed additive manufacturing for 3D printed headband component during global supply chain disruptions;digitalization of a robot-based directed energy deposition process for in-situ monitoring and post-process data analytics;design for additive manufacturing constrained topology optimization of liquid to-air heat exchangers with ML-based turbulent flow considerations;positioning accuracy in a concurrent robot-CNC hybrid manufacturing system;model development of manufacturing information system for silicon carbide wafer production;design strategy for realizing optimized calibration rod for an end mill cutter based on receptance coupling substructure analysis;and a preliminary investigation of input shaping to reduce the residual vibration of a wafer-handling robot.
the proceedings contain 171 papers. the topics discussed include: ImVR: enabling immersive design exploration and process integration for additive manufacturing of complex organic geometries;investigation of distribut...
ISBN:
(纸本)9780791888100
the proceedings contain 171 papers. the topics discussed include: ImVR: enabling immersive design exploration and process integration for additive manufacturing of complex organic geometries;investigation of distributed additive manufacturing for 3D printed headband component during global supply chain disruptions;digitalization of a robot-based directed energy deposition process for in-situ monitoring and post-process data analytics;design for additive manufacturing constrained topology optimization of liquid to-air heat exchangers with ML-based turbulent flow considerations;positioning accuracy in a concurrent robot-CNC hybrid manufacturing system;model development of manufacturing information system for silicon carbide wafer production;design strategy for realizing optimized calibration rod for an end mill cutter based on receptance coupling substructure analysis;and a preliminary investigation of input shaping to reduce the residual vibration of a wafer-handling robot.
through visual research on the current situation and development trends of China's industrial software industry explore its research hotspots and future directions. A total of 1812 articles were searched on China ...
详细信息
Artificial Intelligence has demonstrated its significance in softwareengineeringthrough notable improvements in productivity, accuracy, collaboration, and learning outcomes. this study examines the impact of generat...
详细信息
LinkedIn is the largest professional network in the world. As such, it can serve to build bridges between practitioners, whose daily work is softwareengineering (SE), and researchers, who work to advance the field of...
详细信息
ISBN:
(纸本)9798400704994
LinkedIn is the largest professional network in the world. As such, it can serve to build bridges between practitioners, whose daily work is softwareengineering (SE), and researchers, who work to advance the field of softwareengineering. We know that such a metaphorical bridge exists: SE research findings are sometimes shared on LinkedIn and commented on by software practitioners. Yet, we do not know what state the bridge is in. therefore, we quantitatively and qualitatively investigate how SE practitioners and researchers approach each other via public LinkedIn discussions and what both sides can contribute to effective science communication. We found that a considerable proportion of LinkedIn posts on SE research are written by people who are not the paper authors (39%). Further, 71% of all comments in our dataset are from people in the industry, but only every second post receives at least one comment at all. Based on our findings, we formulate concrete advice for researchers and practitioners to make sharing new research findings on LinkedIn more fruitful.
Data science is a field of knowledgethat exploits various methods of collecting and analyzing data. Nowadays, data-driven software development is getting more common and multiple experts take part of the process, suc...
详细信息
Developers' technical expertise is crucial for various tasks within open-source communities, such as identifying suitable maintainers or reviewers. However, Github, the world's largest open-source code hosting...
详细信息
ISBN:
(数字)9798400712487
ISBN:
(纸本)9798400712487
Developers' technical expertise is crucial for various tasks within open-source communities, such as identifying suitable maintainers or reviewers. However, Github, the world's largest open-source code hosting platform, does not explicitly display developers' technical expertise. Existing methods fail to fully capture the multifaceted and dynamic nature of their skills and knowledge. To address this problem, we propose a novel approach to derive developers' technical expertise using graph neural networks (GNN). We construct a Github social network to integrate social and development activities and employ a GNN model to learn low-dimensional embedding for developers' technical expertise. We verify the effectiveness of our model on four Github social relationship recommendation tasks. the results demonstrate that our approach performs well in predicting technical preference for repositories and developers.
Despite the promise of automation, general-purpose Large Language Models (LLMs) face difficulties in generating complete and accurate test cases from informal software requirements, primarily due to challenges in inte...
详细信息
ISBN:
(纸本)9798400705021
Despite the promise of automation, general-purpose Large Language Models (LLMs) face difficulties in generating complete and accurate test cases from informal software requirements, primarily due to challenges in interpreting unstructured text and producing diverse, relevant scenarios. this paper argues that incorporating domain knowledge significantly improves LLM performance in test case generation. We report on the successful deployment of our LLM-powered tool, LLM4Fin, in the FinTech domain, showcasing the crucial role of domain knowledge in addressing the aforementioned challenges. We demonstrate two methods for integrating domain knowledge: implicit incorporation through model fine-tuning, and explicit incorporation with algorithm design. this combined approach delivers remarkable results, achieving up to 98.18% improvement in test scenario coverage and reducing generation time from 20 minutes to 7 seconds.
暂无评论