Yongqiang Cheng
University of Hull
Network
Latest external collaboration on country level. Dive into details by clicking on the dots.
Publication
Featured researches published by Yongqiang Cheng.
Security and Communication Networks | 2018
Qian Wang; Jiadong Ren; Xiaoli Yang; Yongqiang Cheng; Darryl N. Davis; Changzhen Hu
The scale and complexity of software systems are constantly increasing, imposing new challenges for software fault location and daily maintenance. In this paper, the Security Feature measurement algorithm of Frequent dynamic execution Paths in Software, SFFPS, is proposed to provide a basis for improving the security and reliability of software. First, the dynamic execution of a complex software system is mapped onto a complex network model and sequence model. This, combined with the invocation and dependency relationships between function nodes, fault cumulative effect, and spread effect, can be analyzed. The function node security features of the software complex network are defined and measured according to the degree distribution and global step attenuation factor. Finally, frequent software execution paths are mined and weighted, and security metrics of the frequent paths are obtained and sorted. The experimental results show that SFFPS has good time performance and scalability, and the security features of the important paths in the software can be effectively measured. This study provides a guide for the research of defect propagation, software reliability, and software integration testing.
Intelligent Automation and Soft Computing | 2018
Qian Wang; Jiadong Ren; Darryl N. Davis; Yongqiang Cheng
Frequent pattern mining usually requires much run time and memory usage. In some applications, only the patterns with top frequency rank are needed. Because of the limited pattern numbers, quality of the results is even more important than time and memory consumption. A Frequent Pattern algorithm for mining Top-rank-K patterns, FP_TopK, is proposed. It is based on a Node-list data structure extracted from FTPP-tree. Each node is with one or more triple sets, which contain supports, preorder and post-order transversal orders for candidate pattern generation and top-rank-k frequent pattern mining. FP_TopK uses the minimal support threshold for pruning strategy to guarantee that each pattern in the top-rank-k table is really frequent and this further improves the efficiency. Experiments are conducted to compare FP_TopK with iNTK and BTK on four datasets. The results show that FP_TopK achieves better performance.
Connection Science | 2017
A. Gning; Darryl N. Davis; Yongqiang Cheng; P. Robinson
ABSTRACT In this paper, we review the five rules published in EPSRC Principles of Robotics with a specific focus on future robotics research topics. It is demonstrated through a pictorial representation of the five rules that these rules are questionably not sufficient, overlapping and not explicitly reflecting the true challenges of robotics ethics in relation to the future of robotics research.
IEEE Access | 2018
Bing Zhang; Zhiyao Wei; Jiadong Ren; Yongqiang Cheng; Zhangqi Zheng
IEEE Access | 2018
Qian Wang; Jiadong Ren; Yu Wang; Bing Zhang; Yongqiang Cheng; Xiaolin Zhao
IEEE Access | 2018
Chenxi Huang; Xiaoying Shan; Yisha Lan; Lu Liu; Haidong Cai; Wenliang Che; Yongtao Hao; Yongqiang Cheng; Yonghong Peng
IEEE Access | 2018
Chengwen Zhang; Zengcheng Li; Tang Li; Yunan Han; Cuicui Wei; Yongqiang Cheng; Yonghong Peng
IEEE Access | 2018
Ke Yu; Yue Liu; Linbo Qing; Binbin Wang; Yongqiang Cheng
IEEE Access | 2018
Shihui Wang; Qijian Zhang; Weihong Huang; Hanzhang Tian; Jianzhong Hu; Yongqiang Cheng; Yonghong Peng
IEEE Access | 2018
Dong Yang; Yongqiang Cheng; Jin Zhu; Dongfei Xue; Grant Abt; Hangyang Ye; Yonghong Peng