A5036465380- Software System Performance and Reliability
- Software Reliability and Analysis Research
- Software Engineering Research
- Cloud Computing and Resource Management
- Age of Information Optimization
- Distributed systems and fault tolerance
- Time Series Analysis and Forecasting
- Green IT and Sustainability
- Software Testing and Debugging Techniques
- IoT and Edge/Fog Computing
- Law, logistics, and international trade
- Traffic Prediction and Management Techniques
Wuhan University of Technology
2007-2024
Nanyang Normal University
2024
Software aging, which is caused by the accumulation of errors in system and consumption computing resources, tends to occur long-running cloud service software systems. In practice, aging prediction has proven be useful planning time trigger rejuvenation because it provides a prior estimate future resource consumption. However, indicators (e.g., physical memory) may have characteristics long-term slow growth, medium-term seasonality variations (alternating peaks troughs), short-term...
Cloud infrastructures are designed to provide highly scalable, pay-as-per-use services meet the performance requirements of users. The workload prediction cloud plays a crucial role in proactive auto-scaling and dynamic management resources move toward fine-grained load balancing job scheduling due its ability estimate upcoming workloads. However, users’ diverse usage demands, changing characteristics workloads have become more complex, including not only short-term irregular fluctuation but...
Software aging, which is caused by Aging-Related Bugs (ARBs), refers to the phenomenon of performance degradation and eventual crash in long running systems. In order discover remove ARBs, ARB prediction proposed. However, due low presence reproducing difficulty it usually difficult collect sufficient data within a project. Therefore, cross-project proposed as solution build target project's predictor using labeled from source A key point for reduce distribution difference between existing...
In the Android system, software aging is an essential factor affecting user experience. Its occurrence will lead to poor responsiveness or crash/hang failure of system. Recently, strategies schedule rejuvenation are marching toward a situation that needs consider both usage behavioral aspects its users (i.e., switch between active and sleep modes) two-level process Operating System (OS) Application Software (AS)), because rejuvenating OS AS during time slot contributes terrible To be able...
Software aging refers to system performance degradation and failure due Aging-Related Bugs (ARBs) in long-running software systems. ARB prediction helps identify ARBs prevent aging. However, early project stages often lack data for model training. To address this, cross-project (CPAP) is proposed, where a trained using labeled source projects predict the present target project. In CPAP, distribution discrepancy class imbalance pose challenges, impacting performance. this paper, hybrid CPAP...
Software aging refers to the phenomenon of sys-tem performance degradation and eventual failure caused by Aging-Related Bugs (ARBs). seriously affects reliability availability software systems. To discover remove ARBs, ARBs prediction is presented, most them only employed static code metrics predict those buggy codes. However, do not capture syntactic semantic features code, which are important building accurate models. address this problem, we design a deep neural network combining...
Regression testing is a software type that examines whether updates made in the impact existing functionality of application. Depressingly, long time and high costs make regression very expensive. Test case prioritization (TCP) stands out as one extensively researched techniques. It prioritizes test cases to optimize their execution order, aiming maximize goals reveal faults earlier provide feedback testers. The TCP technique based on log analysis (LogTCP) designs strategy using logs...
Abstract Software aging refers to the accumulation of error conditions over time in long-running software systems, which can lead decreased performance and an increased likelihood failures. Aging-Related Bug Prediction (ARBP) was introduced predict Aging-related Bugs (ARBs) hidden systems by using features extracted from source code. ARBs include memory leaks, storage problems, unreleased files, socket exceptions, file handles, disk fragmentation so on. Previous research Defect (SDP)...
<title>Abstract</title> Software aging refers to the performance degradation and failure crash phenomena in long-running systems. As a proactive remedy, software rejuvenation can be scheduled timely mitigate effects. Inescapably, how accurately predict time (TTAF) of is prerequisite for implementing effective rejuvenation. However, characterization relatively complicated, leading selection indicators case by case, which means that only fitting variation trend single indicator prediction...