VLDB 2026 Research / reviewers in the wild / expert
Jialing Yang
dblp:226/5423
· DBLP profile ↗
7ranked-venue papers
0as first author
7since 2021 · last 2026
—ORCID · conflict
Domains — the database's venue-derived domains; a paper can count in several
Artificial intelligence and machine learning · 2 · 2 since 2021Graphics, computer vision, multimedia, augmented reality and games · 2 · 2 since 2021Systems, architecture and hardware · 1 · 1 since 2021Software engineering, systems software and programming languages · 1 · 1 since 2021Databases, data management, data science and information retrieval · 1 · 1 since 2021
Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.
| Software engineering, system software, and programming languages
1 paper |
Software maintenance and evolution · 80% Requirements engineering and software design · 20% |
Topics — the 5 heaviest of 5, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Software maintenance and evolution › refactoring
architectural refactoring |
1.0 | 1 | 2026 | Weighted Community Division for Automated Software Architecture Refactoring · IEEE Trans. Software Eng. 2026 |
Software maintenance and evolution › refactoring
automated refactoring |
1.0 | 1 | 2026 | Weighted Community Division for Automated Software Architecture Refactoring · IEEE Trans. Software Eng. 2026 |
Software maintenance and evolution
refactoring |
1.0 | 1 | 2026 | Weighted Community Division for Automated Software Architecture Refactoring · IEEE Trans. Software Eng. 2026 |
Requirements engineering and software design
software architecture |
1.0 | 1 | 2026 | Weighted Community Division for Automated Software Architecture Refactoring · IEEE Trans. Software Eng. 2026 |
Software maintenance and evolution
software modularization |
1.0 | 1 | 2026 | Weighted Community Division for Automated Software Architecture Refactoring · IEEE Trans. Software Eng. 2026 |
Methods — techniques the papers use, named apart from their topics
weighted graph clustering · 1.0community detection · 1.0
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2026 | Revisiting unsupervised image stitching via efficient boundary rectification
Yun Zhang 0024, Jialing Yang, Ruiyang Liang, Lang Nie, Xinyuan Zheng |
Comput. Graph. | 2 |
| 2026 | Weighted Community Division for Automated Software Architecture RefactoringabstractAdopting Model-Based Development (MBD) in automotive software becomes necessary because it provides a rigorous development process. As the increase in the number of software components (SWCs) and their interactions, modifications to one part of the software might impact other parts due to the high coupling of SWCs. Developing an automated software refactoring technique to implement high cohesion and low coupling of software is necessary. Software refactoring usually contains code refactoring and architecture refactoring. Code refactoring only modifies the code inside the SWCs without changing its original functionality and external behavior, whereas current architecture refactoring does not consider the interaction weight (strength) between SWCs.In this study, we propose a weighted community division algorithm called Weighted-Girvan-Newman (W-GN) for software architecture refactoring. W-GN algorithm refactors the architecture by dividing SWCs into modules based on the interaction weights of SWCs. We further develop an automated architecture refactoring tool called AutoToolMD. This tool assists engineers in improving development efficiency and ensures the architecture aligns with the requirements of high cohesion and low coupling. Evaluations show that W-GN indicates more suitable modularity values than the traditional Girvan-Newman (GN) algorithm because the former can better reflect the real architecture with interaction weights. We apply AutoToolMD to automatically refactor architecture in automotive industry practice. Case study with the Zone_B PwrSplyMngt and Zone L_Lock modules in the Honda zone control software shows that AutoToolMD effectively refactors architecture with a significant improvement in testing efficiency and readability. Sirong Zhao, Jialing Yang, Jiao Xie, Kaiwei Fan, Jianmei Lei, Guoqi Xie |
IEEE Trans. Software Eng. | 2 |
| 2026 | Rectangling stitched images via unsupervised warping
Yun Zhang 0024, Jialing Yang, Zhe Zhu, Yukun Lai, Xinyuan Zheng |
Vis. Comput. | 3 |
| 2025 | Multi-Exposure image Fusion via distilled 3D LUT grid with editable mode
Xin Su 0009, Zhuoran Zheng, Jialing Yang |
Neurocomputing | 3 |
| 2025 | CT-DDPM: Anomaly detection of multivariate time series with copula and transformer-based denoising diffusion probabilistic models
Chunquan Pan, Liyun Su, Lang Xiong, Jialing Yang, Fenglan Li |
Inf. Sci. | 4 |
| 2025 | TMI: Two-dimensional maintainability index for automotive software maintainability measurement
Jiao Xie, Jialing Yang, Sirong Zhao, Jianmei Lei, Kaiwei Fan, Guoqi Xie |
J. Syst. Archit. | 2 |
| 2022 | P &GGD: A Joint-Way Model Optimization Strategy Based on Filter Pruning and Filter Grafting For Tea Leaves Classification
Zhe Li 0066, Jialing Yang, Fang Qi |
Neural Process. Lett. | 3 |