A5054854588- Anomaly Detection Techniques and Applications
- Software Testing and Debugging Techniques
- Software Engineering Research
- Adversarial Robustness in Machine Learning
- Flexible and Reconfigurable Manufacturing Systems
- Natural Language Processing Techniques
- Hydrocarbon exploration and reservoir analysis
- Business Process Modeling and Analysis
- Imbalanced Data Classification Techniques
- Algorithms and Data Compression
- Manufacturing Process and Optimization
- Seismic Imaging and Inversion Techniques
- Fault Detection and Control Systems
- Advanced Database Systems and Queries
- Machine Learning and Data Classification
- Hydraulic Fracturing and Reservoir Analysis
- Software System Performance and Reliability
Chongqing University
2023-2024
China National Petroleum Corporation (China)
2020
A test suite is indispensable for fault localization by providing useful execution information of its cases locating suspicious statements being faulty. There exists a type known as coincidental correctness (CC) cases, which executes the faulty statement whereas produces anticipated output. The existing studies have shown CC harmfully impact effectiveness. Therefore, it crucial to detect mitigate adverse on localization.To address this issue, we propose ContraCC: detection method using...
Service-oriented manufacturing (SOM) is a strategy pursued by traditional industries in recent years for sustainable development. SOM combines services and to provide customized products customers, adding value the increasing industrial profits. Business processes are critical aspect of service-oriented manufacturing, involving entire process from customer demand product delivery, finally after-sales service. The success business depends on correctness rationality design. However,...
The high quality of input data serves as the foundation for various tasks. Inaccurate may decrease effectiveness elaborate algorithms and significantly impact output. This also applies to fault localization, accurate reliable is crucial effective localization techniques. Many techniques analyze coverage information detecting bug positions. However, source suffers from problems, such imbalanced coincidental correctness. These problems make unreliable localization. To mitigate potential...
Summary Label and algorithm are two main factors that influence the effect of deep learning inversion (DLI). Most present researches focus on optimizing algorithms, pay less attention to how labels affect effect, which results in application effects same varying with regions. This article highlights importance label conditions DLI. The comparison performed 4 different sets indicates an ideal DL requires a large number high-quality large-diversity labels.1) quality is most important factor,...