Search

Your search keyword '"Zhou, Zhide"' showing total 273 results
Start Over Author "Zhou, Zhide" Publication Year Range Last 10 years
273 results on '"Zhou, Zhide"'

3. Isolating Compiler Bugs by Generating Effective Witness Programs with Large Language Models

Author

Tu, Haoxin, Zhou, Zhide, Jiang, He, Yusuf, Imam Nur Bani, Li, Yuxian, and Jiang, Lingxiao

Subjects
Computer Science - Software Engineering
Abstract

Compiler bugs pose a significant threat to safety-critical applications, and promptly as well as effectively isolating these bugs is crucial for assuring the quality of compilers. However, the limited availability of debugging information on reported bugs complicates the compiler bug isolation task. Existing compiler bug isolation approaches convert the problem into a test program mutation problem, but they are still limited by ineffective mutation strategies or high human effort requirements. Drawing inspiration from the recent progress of pre-trained Large Language Models (LLMs), such as ChatGPT, in code generation, we propose a new approach named LLM4CBI to utilize LLMs to generate effective test programs for compiler bug isolation. However, using LLMs directly for test program mutation may not yield the desired results due to the challenges associated with formulating precise prompts and selecting specialized prompts. To overcome the challenges, three new components are designed in LLM4CBI. First, LLM4CBI utilizes a program complexity-guided prompt production component, which leverages data and control flow analysis to identify the most valuable variables and locations in programs for mutation. Second, LLM4CBI employs a memorized prompt selection component, which adopts reinforcement learning to select specialized prompts for mutating test programs continuously. Third, a test program validation component is proposed to select specialized feedback prompts to avoid repeating the same mistakes during the mutation process. Compared with state-of-the-art approaches over 120 real bugs from GCC and LLVM, our evaluation demonstrates the advantages of LLM4CBI: It can isolate 69.70%/21.74% and 24.44%/8.92% more bugs than DiWi and RecBi within Top-1/Top-5 ranked results. We also demonstrate that the LLMs component used in LLM4CBI can be easily replaced while still achieving reasonable results., Comment: Accepted by IEEE Transactions on Software Engineering

Published
2023
Full Text
View/download PDF

10. Determination of the Subjective Application of Punitive Damages for Patent Infringement

Author

Hu, Xiaomin, Zhou, Zhide, Striełkowski, Wadim, Editor-in-Chief, Black, Jessica M., Series Editor, Butterfield, Stephen A., Series Editor, Chang, Chi-Cheng, Series Editor, Cheng, Jiuqing, Series Editor, Dumanig, Francisco Perlas, Series Editor, Al-Mabuk, Radhi, Series Editor, Scheper-Hughes, Nancy, Series Editor, Urban, Mathias, Series Editor, Webb, Stephen, Series Editor, Chen, Youbin, editor, Yacob, Shakila, editor, Rak, Joanna, editor, and Li, Jia, editor

Published
2023
Full Text
View/download PDF

11. Analysis of attribution of liability for ecological damage torts

Author

Yu, Fanfei, Zhou, Zhide, Striełkowski, Wadim, Editor-in-Chief, Black, Jessica M., Series Editor, Butterfield, Stephen A., Series Editor, Chang, Chi-Cheng, Series Editor, Cheng, Jiuqing, Series Editor, Dumanig, Francisco Perlas, Series Editor, Al-Mabuk, Radhi, Series Editor, Scheper-Hughes, Nancy, Series Editor, Urban, Mathias, Series Editor, Webb, Stephen, Series Editor, Chen, Youbin, editor, Yacob, Shakila, editor, Rak, Joanna, editor, and Li, Jia, editor

Published
2023
Full Text
View/download PDF

12. Issues and suggestions on the calculation of patent open license fees

Author

Guo, Xitong, Zhou, Zhide, Striełkowski, Wadim, Editor-in-Chief, Black, Jessica M., Series Editor, Butterfield, Stephen A., Series Editor, Chang, Chi-Cheng, Series Editor, Cheng, Jiuqing, Series Editor, Dumanig, Francisco Perlas, Series Editor, Al-Mabuk, Radhi, Series Editor, Scheper-Hughes, Nancy, Series Editor, Urban, Mathias, Series Editor, Webb, Stephen, Series Editor, Chen, Youbin, editor, Yacob, Shakila, editor, Rak, Joanna, editor, and Li, Jia, editor

Published
2023
Full Text
View/download PDF

13. Copyright Protection of Live Sports Programs

Author

Pan, Yi, Zhou, Zhide, Striełkowski, Wadim, Editor-in-Chief, Black, Jessica M., Series Editor, Butterfield, Stephen A., Series Editor, Chang, Chi-Cheng, Series Editor, Cheng, Jiuqing, Series Editor, Dumanig, Francisco Perlas, Series Editor, Al-Mabuk, Radhi, Series Editor, Scheper-Hughes, Nancy, Series Editor, Urban, Mathias, Series Editor, Webb, Stephen, Series Editor, Chen, Youbin, editor, Yacob, Shakila, editor, Rak, Joanna, editor, and Li, Jia, editor

Published
2023
Full Text
View/download PDF

14. Analysis on the Standard of Deep Link Behavior Infringement

Author

Zhou, Zhide, Li, Xinyang, Striełkowski, Wadim, Editor-in-Chief, Black, Jessica M., Series Editor, Butterfield, Stephen A., Series Editor, Chang, Chi-Cheng, Series Editor, Cheng, Jiuqing, Series Editor, Dumanig, Francisco Perlas, Series Editor, Al-Mabuk, Radhi, Series Editor, Scheper-Hughes, Nancy, Series Editor, Urban, Mathias, Series Editor, Webb, Stephen, Series Editor, Hussain, Rosila Bee Binti Mohd, editor, Parc, Jimmyn, editor, and Li, Jia, editor

Published
2023
Full Text
View/download PDF

15. Research on the Law Application of Retirees’ Re-employment

Author

Zhou, Zhide, Liu, Huaijie, Striełkowski, Wadim, Editor-in-Chief, Black, Jessica M., Series Editor, Butterfield, Stephen A., Series Editor, Chang, Chi-Cheng, Series Editor, Cheng, Jiuqing, Series Editor, Dumanig, Francisco Perlas, Series Editor, Al-Mabuk, Radhi, Series Editor, Scheper-Hughes, Nancy, Series Editor, Urban, Mathias, Series Editor, Webb, Stephen, Series Editor, Hussain, Rosila Bee Binti Mohd, editor, Parc, Jimmyn, editor, and Li, Jia, editor

Published
2023
Full Text
View/download PDF

31. A novel electrochemical aptasensor based on NrGO-H-Mn3O4 NPs integrated CRISPR/Cas12a system for ultrasensitive low-density lipoprotein determination.

Author

Li, Guiyin, Li, Shengnan, Li, Xinhao, He, Wei, Tan, Xiaohong, Liang, Jintao, and Zhou, Zhide

Subjects
CRISPRS, SINGLE-stranded DNA, ELECTRIC conductivity, LOW density lipoproteins, DETECTION limit
Abstract

Atherosclerosis cardiovascular disease (ASCVD) has become one of the leading death causes in humans. Low-density lipoprotein (LDL) is an important biomarker for assessing ASCVD risk level. Thus, monitoring LDL levels can be an important means for early diagnosis of ASCVD. Herein, a novel electrochemical aptasensor for determination LDL was designed based on nitrogen-doped reduced graphene oxide-hemin-manganese oxide nanoparticles (NrGO-H-Mn3O4 NPs) integrated with clustered regularly interspaced short palindromic repeats and associated proteins (CRISPR/Cas12a) system. NrGO-H-Mn3O4 NPs not only have a large surface area and remarkable enhanced electrical conductivity but also the interconversion of different valence states of iron in hemin can provide an electrical signal. Nonspecific single-stranded DNA (ssDNA) was bound to NrGO-H-Mn3O4 NPs to form a signaling probe and was immobilized on the electrode surface. The CRISPR/Cas12a system has excellent trans-cleavage activity, which can be used to cleave ssDNA, thus detaching the NrGO-H-Mn3O4 NPs from the sensing interface and attenuating the electrical signal. Significant signal change triggered by the target was ultimately obtained, thus achieving sensitive detection of the LDL in range from 0.005 to 1000.0 nM with the detection limit of 0.005 nM. The proposed sensor exhibited good stability, selectivity, and stability and achieved reliable detection of LDL in serum samples, demonstrating its promising application prospects for the diagnostic application of LDL. [ABSTRACT FROM AUTHOR]

Published
2024
Full Text
View/download PDF

35. HetFL: Heterogeneous Graph-Based Software Fault Localization

Author

Chen, Xin, Sun, Tian, Zhuang, Dongling, Yu, Dongjin, Jiang, He, Zhou, Zhide, and Li, Sicheng

Abstract

Automated software fault localization has become one of the hot spots on which researchers have focused in recent years. Existing studies have shown that learning-based techniques can effectively localize faults leveraging various information. However, there exist two problems in these techniques. The first is that they simply represent various information without caring the contribution of different information. The second is that the data imbalance problem is not considered in these techniques. Thus, their effectiveness is limited in practice. In this paper, we propose HetFL, a novel heterogeneous graph-based software fault localization technique to aggregate different information into a heterogeneous graph in which program entities and test cases are regarded as nodes, and coverage, change histories, and call relationships are viewed as edges. HetFL first extracts textual and structure information from source code as attributes of nodes and integrates them to form an attribute vector. Then, for a given node, HetFL finds its neighbor nodes based on the types of edges and aggregates corresponding neighbor nodes to form type vectors. After that, the attribute vector and all the type vectors of each node are aggregated to generate the final vector representation by an attention mechanism. Finally, we leverage a convolution neural network (CNN) to obtain the suspicious score of each method. To validate the effectiveness of HetFL, experiments are conducted on the widely used dataset Defects4J (v1.2.0). The experimental results show that HetFL can localize 217 faults within Top-1 that is 25 higher than the state-of-the-art technique DeepFL, and achieve 6.37 and 5.58 in terms of MAR and MFR which improve DeepFL by 9.0% and 5.6%, respectively. In addition, we also perform experiments on the latest version of Defects4J (v2.0.0). The experimental results show that HetFL has better performance than the baseline methods.

Published
2024
Full Text
View/download PDF

44. The Dilemma of Fair Use of Artificial Intelligence Painting and Its Regulations

Author

Zhou Zhide and Ling Xiangxiang

Subjects
Social Sciences
Abstract

At present, artificial intelligence painting technology is in an era of prosperity and development. The “transformation” of artificial intelligence painting works has brought challenges to the traditional fair use system, and characterization as fair use may lead to an imbalance of interests. It is necessary to re-examine the rationality of qualifying the use of artificial intelligence paintings as fair use. At the same time, analyze the infringement risk in the painting process in combination with the painting principles of artificial intelligence, and put forward some regulatory suggestions.

Published
2023
Full Text
View/download PDF

45. Research on Copyright Infringement of Network Remixes Short Video

Author

Niu Mengna and Zhou Zhide

Subjects
Social Sciences
Abstract

The new economic model and the development of the Internet and media technology have bred the network mixed clip video. This new video type not only enriches people’s spiritual and cultural life, but also brings about copyright infringement problems. This article focuses on the copyright issue of Network remixes short video, and also focuses on the issues of whether the Network remixes short video belong to the “Works” stipulated in the Copyright Law of The People’s Republic of China and whether the use of other people’s works in the Network remixes short video can be regarded as reasonable, and hopes to put forward some suggestions for the prevention, solution or regulation of related problems.

Published
2023
Full Text
View/download PDF

Catalog

Books, media, physical & digital resources
See catalog results